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Pellerine LP, Courish MK, Petterson JL, Shivgulam ME, Johansson PJ, Hettiarachchi P, Kimmerly DS, O'Brien MW. Assessing the criterion validity of the activPAL CREA v1.3 algorithm and ActiPASS 2023.12 software for detecting steps during a progressive treadmill-based laboratory protocol. J Sports Sci 2024:1-8. [PMID: 39450997 DOI: 10.1080/02640414.2024.2419222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 10/14/2024] [Indexed: 10/26/2024]
Abstract
Thigh-worn accelerometry is commonly implemented to measure step cadence. The default activPAL CREA algorithm is a valid measure of cadence during walking, but its validity during running is unknown. The ActiPASS software is designed to analyse tri-axial accelerometry data from various brands. We tested the validity of CREA v1.3 and ActiPASS 2023.12 to measure step cadence against manually-counted steps. Forty-five participants (26♀, 23.4 ± 4.6 years) completed 5 walking (6 min each, 2-4 mph) and 5 running treadmill (5-7 mph) stages (423 total stages completed). Based on equivalence testing, walking cadence (stages 1-5: 92-124 steps/min) from CREA was statistically equivalent (zone: <±2.2% of the manually-counted mean) to manual counts (92-125 steps/min). However, CREA underpredicted cadence during running stages (stages 6-10: 143-135 steps/min) by ~ 11-20 steps/min (p < 0.001). The ActiPASS-derived cadences were equivalent (zone: <±3.3%) to manual counts for all walking stages (99-127 steps/min) except Stage 1 (zone: ±10.5%). ActiPASS underpredicted cadences during running (stages 6-10: 137-153 steps/min) by ~ 10-16 steps/min (p < 0.001) compared to manual counts (stages 6-10: 154-164 steps/min). The CREA v1.3 algorithm is a valid measure of cadence during walking while ActiPASS 2023.12 is a valid measure of cadence during medium-fast walking. Further research is required to improve step cadence estimation across ambulation speeds.
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Affiliation(s)
- Liam P Pellerine
- Division of Kinesiology, Dalhousie University, Halifax, NS, Canada
| | - Molly K Courish
- Division of Kinesiology, Dalhousie University, Halifax, NS, Canada
| | | | | | - Peter J Johansson
- Occupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Occupational and Environmental Medicine, Uppsala University Hospital, Uppsala, Sweden
| | - Pasan Hettiarachchi
- Occupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Derek S Kimmerly
- Division of Kinesiology, Dalhousie University, Halifax, NS, Canada
| | - Myles W O'Brien
- School of Physiotherapy, Faculty of Health, Dalhousie University, Halifax, NS, Canada
- Division of Geriatric Medicine, Department of Medicine, Dalhousie University, Halifax, NS, Canada
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Ars J, Calderón-Larrañaga A, Beridze G, Laukka EJ, Farrés-Godayol P, Pérez LM, Inzitari M, Welmer AK. Association Between Accelerometer-Assessed Physical Activity and Cognitive Function in Older Adults: A Cross-Sectional Study. Am J Geriatr Psychiatry 2024:S1064-7481(24)00481-0. [PMID: 39428265 DOI: 10.1016/j.jagp.2024.09.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 08/28/2024] [Accepted: 09/24/2024] [Indexed: 10/22/2024]
Abstract
OBJECTIVE Research suggests that physical activity (PA) improves cognitive function across various domains. However, the specific role of different PA measures, including step count, remains to be explored. Our aim was to assess the correlation between objectively measured PA and cognitive function. METHODS We included 663 adults, aged ≥66 years, from the Swedish SNAC-K study (2016-2019). Global cognition and three cognitive domains (processing speed, executive function, and episodic memory) were assessed with validated tests. PA was measured through ActivPAL3 accelerometers. We applied age-stratified (<70 vs. ≥80 years), multi-adjusted, quantile regression to examine the cross-sectional associations between cognitive function and PA, considering steps/day and time spent in moderate-to-vigorous PA (MVPA). RESULTS Each 1000-step increment (β = 0.04; 95% CI: 0.01, 0.07) and each additional hour of MVPA per day (β = 0.28; 95% CI: 0.02, 0.54) were correlated with better processing speed in the youngest-old, but not in the oldest-old. When further stratifying by MVPA (<60 min vs. ≥60 min/week), each 1000-step increment was associated with better processing speed in the youngest-old, regardless of their MVPA levels. CONCLUSION Our study links accelerometer-assessed PA (steps and MVPA) with better processing speed in the youngest-old adults. Step count correlated with processing speed regardless of intensity. Further research is needed to determine the directionality of these associations.
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Affiliation(s)
- Joan Ars
- Aging Research Center, Department of Neurobiology, Care Sciences and Society (NVS), (JA, ACL, GB, EJL, AKW), Karolinska Institutet and Stockholm University, Stockholm, Sweden; RE-FiT Barcelona Research group (JA, LMP, MI), Vall d'Hebron Institute of Research (VHIR) and Parc Sanitari Pere Virgili, Barcelona, Spain.
| | - Amaia Calderón-Larrañaga
- Aging Research Center, Department of Neurobiology, Care Sciences and Society (NVS), (JA, ACL, GB, EJL, AKW), Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center (ACL, EJL, AKW), Stockholm, Sweden
| | - Giorgi Beridze
- Aging Research Center, Department of Neurobiology, Care Sciences and Society (NVS), (JA, ACL, GB, EJL, AKW), Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Erika J Laukka
- Aging Research Center, Department of Neurobiology, Care Sciences and Society (NVS), (JA, ACL, GB, EJL, AKW), Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center (ACL, EJL, AKW), Stockholm, Sweden
| | - Pau Farrés-Godayol
- Research group on Methodology (PFG), Methods, Models and Outcomes of Health and Social Sciences (M(3)O), Faculty of Health Sciences and Welfare, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain
| | - Laura M Pérez
- RE-FiT Barcelona Research group (JA, LMP, MI), Vall d'Hebron Institute of Research (VHIR) and Parc Sanitari Pere Virgili, Barcelona, Spain
| | - Marco Inzitari
- RE-FiT Barcelona Research group (JA, LMP, MI), Vall d'Hebron Institute of Research (VHIR) and Parc Sanitari Pere Virgili, Barcelona, Spain; Faculty of Health Sciences (MI), Universitat Oberta de Catalunya (UOC), Barcelona, Spain
| | - Anna-Karin Welmer
- Aging Research Center, Department of Neurobiology, Care Sciences and Society (NVS), (JA, ACL, GB, EJL, AKW), Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center (ACL, EJL, AKW), Stockholm, Sweden; Division of Physiotherapy (AKW), Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Women´s Health and Allied Health Professionals Theme (AKW), Medical Unit Medical Psychology, Karolinska University Hospital, Stockholm, Sweden
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Hu X, Sgherza TR, Nothrup JB, Fresco DM, Naragon-Gainey K, Bylsma LM. From lab to life: Evaluating the reliability and validity of psychophysiological data from wearable devices in laboratory and ambulatory settings. Behav Res Methods 2024; 56:1-20. [PMID: 38528248 DOI: 10.3758/s13428-024-02387-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/02/2024] [Indexed: 03/27/2024]
Abstract
Despite the increasing popularity of ambulatory assessment, the reliability and validity of psychophysiological signals from wearable devices is unproven in daily life settings. We evaluated the reliability and validity of physiological signals (electrocardiogram, ECG; photoplethysmography, PPG; electrodermal activity, EDA) collected from two wearable devices (Movisens EcgMove4 and Empatica E4) in the lab (N = 67) and daily life (N = 20) among adults aged 18-64 with Mindware as the laboratory gold standard. Results revealed that both wearable devices' valid data rates in daily life were lower than in the laboratory (Movisens ECG 82.94 vs. 93.10%, Empatica PPG 8.79 vs. 26.14%, and Empatica EDA 41.16 vs. 42.67%, respectively). The poor valid data rates of Empatica PPG signals in the laboratory could be partially attributed to participants' hand movements (r = - .27, p = .03). In laboratory settings, heart rate (HR) derived from both wearable devices exhibited higher concurrent validity than heart rate variability (HRV) metrics (ICCs 0.98-1.00 vs. 0.75-0.97). The number of skin conductance responses (SCRs) derived from Empatica showed higher concurrent validity than skin conductance level (SCL, ICCs 0.38 vs. 0.09). Movisens EcgMove4 provided more reliable and valid HRV measurements than Empatica E4 in both laboratory (split-half reliability: 0.95-0.99 vs. 0.85-0.98; concurrent validity: 0.95-1.00 vs. 0.75-0.98; valid data rate: 93.10 vs. 26.14%) and ambulatory settings (split-half reliability: 0.99-1.00 vs. 0.89-0.98; valid data rate: 82.94 vs. 8.79%). Although the reliability and validity of wearable devices are improving, findings suggest researchers should select devices that yield consistently robust and valid data for their measures of interest.
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Affiliation(s)
- Xin Hu
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Tanika R Sgherza
- School of Psychological Science, University of Western Australia, Perth, Australia
| | - Jessie B Nothrup
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - David M Fresco
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | | | - Lauren M Bylsma
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
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Hibbing PR, Khan MM. Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors. JMIR Mhealth Uhealth 2024; 12:e57158. [PMID: 39331461 PMCID: PMC11470225 DOI: 10.2196/57158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 07/09/2024] [Accepted: 08/26/2024] [Indexed: 09/28/2024] Open
Abstract
Wearable monitors continue to play a critical role in scientific assessments of physical activity. Recently, research-grade monitors have begun providing raw data from photoplethysmography (PPG) alongside standard raw data from inertial sensors (accelerometers and gyroscopes). Raw PPG enables granular and transparent estimation of cardiovascular parameters such as heart rate, thus presenting a valuable alternative to standard PPG methodologies (most of which rely on consumer-grade monitors that provide only coarse output from proprietary algorithms). The implications for physical activity assessment are tremendous, since it is now feasible to monitor granular and concurrent trends in both movement and cardiovascular physiology using a single noninvasive device. However, new users must also be aware of challenges and limitations that accompany the use of raw PPG data. This viewpoint paper therefore orients new users to the opportunities and challenges of raw PPG data by presenting its mechanics, pitfalls, and availability, as well as its parallels and synergies with inertial sensors. This includes discussion of specific applications to the prediction of energy expenditure, activity type, and 24-hour movement behaviors, with an emphasis on areas in which raw PPG data may help resolve known issues with inertial sensing (eg, measurement during cycling activities). We also discuss how the impact of raw PPG data can be maximized through the use of open-source tools when developing and disseminating new methods, similar to current standards for raw accelerometer and gyroscope data. Collectively, our comments show the strong potential of raw PPG data to enhance the use of research-grade wearable activity monitors in science over the coming years.
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Affiliation(s)
- Paul R Hibbing
- Department of Kinesiology and Nutrition, University of Illinois Chicago, Chicago, IL, United States
| | - Maryam Misal Khan
- Department of Kinesiology and Nutrition, University of Illinois Chicago, Chicago, IL, United States
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada
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5
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Firkin CJ, Obrusnikova I, Koch LC. Quantifying Physical Activity and Sedentary Behavior in Adults with Intellectual Disability: A Scoping Review of Assessment Methodologies. Healthcare (Basel) 2024; 12:1912. [PMID: 39408092 PMCID: PMC11476182 DOI: 10.3390/healthcare12191912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2024] [Revised: 09/14/2024] [Accepted: 09/19/2024] [Indexed: 10/20/2024] Open
Abstract
Background/Objectives: Methodologies for assessing behavior form the foundation of health promotion and disease prevention. Physical activity (PA) and sedentary behavior (SB) assessment methodologies have predominantly been developed for adults without an intellectual disability (ID), raising credibility concerns for adults with ID. The purpose was to synthesize the current state of assessment methodologies for quantifying PA and SB volume in the free-living setting for adults with an ID. Methods: Following PRISMA guidelines, eleven databases were searched through December 2023, yielding 8174 records. Data were extracted in Covidence (v.2.0), obtaining quantified PA and SB volume and assessment methodology characteristics across data collection and analysis, including tool(s) and technique(s) used, preparatory actions taken, instructions provided, and behavioral strategies employed during data collection. Results: Of the 8174 articles screened, 91 met the inclusion criteria. Common metrics included minutes/hours per day/week and steps per day/week. Despite 80% of the studies using objective techniques, substantial variation existed across studies regarding wearable models, sampling frequency and epoch length settings, calibration protocols, wearable placements, and data processing techniques. Limited studies provided instructions that did not exclusively rely on spoken language. Behavioral strategies varied, including self-monitoring, providing assistance or supervision, administering questionnaires verbally, issuing reminders, and offering monetary incentives. Conclusions: This review underscores the need for greater consistency and accessibility in PA and SB assessment methodology for adults with ID. Tailored preparation, instruction, and behavioral strategies may enhance assessment viability and suitability for adults with ID, with or without caregiver or researcher involvement in the free-living setting.
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Affiliation(s)
- Cora J. Firkin
- Department of Health Behavior and Nutrition Sciences, University of Delaware, Newark, DE 19716, USA;
| | - Iva Obrusnikova
- Department of Health Behavior and Nutrition Sciences, University of Delaware, Newark, DE 19716, USA;
| | - Laura C. Koch
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada;
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6
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Cao Z, Min J, Hou Y, Si K, Wang M, Xu C. Association of accelerometer-derived physical activity with all-cause and cause-specific mortality among individuals with cardiovascular diseases: A prospective cohort study. Eur J Prev Cardiol 2024:zwae248. [PMID: 39087659 DOI: 10.1093/eurjpc/zwae248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2024] [Revised: 07/04/2024] [Accepted: 07/26/2024] [Indexed: 08/02/2024]
Abstract
AIMS To investigate the association of accelerometer-measured intensity-specific physical activity (PA) with all-cause and cause-specific mortality among individuals with cardiovascular disease (CVD). METHODS In this prospective cohort study, 8,024 individuals with pre-existing CVD (mean age: 66.6 years, female: 34.1%) from the UK Biobank had their PA measured using wrist-worn accelerometers over a 7-day period in 2013-2015. All-cause, cancer, and CVD mortality was ascertained from death registries. Cox regression modelling and restricted cubic splines were used to assess the associations. Population-attributable fractions (PAFs) were used to estimate the proportion of preventable deaths if more PA were undertaken. RESULTS During an average of 6.8 years of follow-up, 691 deaths (273 from cancer and 219 from CVD) were recorded. An inverse non-linear association was found between PA duration and all-cause mortality risk, irrespective of PA intensity. The hazard ratio (HR) of all-cause mortality plateaued at 1800 minutes/week for light-intensity PA (LPA), 320 minutes/week for moderate-intensity PA (MPA) and 15 minutes/week for vigorous-intensity PA (VPA). The highest quartile of PA associated lower risks for all-cause mortality, with HRs of 0.63 (95% confidence interval [CI]: 0.51-0.79), 0.42 (0.33-0.54) and 0.47 (0.37-0.60) for LPA, MPA, and VPA, respectively. Similar associations were observed for cancer and CVD mortality. Additionally, the highest PAF were noted for VPA, followed by MPA. CONCLUSION We found an inverse non-linear association between all intensities of PA (LPA, MPA, VPA, and MVPA) and mortality risk in CVD patients using accelerometer-derived data, but with larger magnitude of the associations than that in previous studies based on self-reported PA.
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Affiliation(s)
- Zhi Cao
- School of Public Health, Hangzhou Normal University, Hangzhou, China
- School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiahao Min
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Yabing Hou
- Yanjing medical college, Capital Medical University, Beijing, China
| | - Keyi Si
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mingwei Wang
- Department of Cardiology, Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
- Institute of Cardiovascular Diseases, Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, China
| | - Chenjie Xu
- School of Public Health, Hangzhou Normal University, Hangzhou, China
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Monnaatsie M, Mielke GI, Biddle SJH, Kolbe-Alexander TL. Ecological momentary assessment of physical activity and sedentary behaviour in shift workers and non-shift workers: Validation study. J Sports Sci 2024:1-10. [PMID: 38899730 DOI: 10.1080/02640414.2024.2369443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 06/11/2024] [Indexed: 06/21/2024]
Abstract
This study examined the criterion validity of an ecological momentary assessment (EMA)-reported physical activity and sedentary time compared with accelerometry in shift workers and non-shift workers. Australian workers (n = 102) received prompts through a mobile EMA app and wore the Actigraph accelerometer on the right hip for 7-10 days. Participants received five EMA prompts per day at 3-hour intervals on their mobile phones. EMA prompts sent to shift workers (SW-T) were tailored according to their work schedule. Non-shift workers (NSW-S) received prompts at standardised times. To assess criterion validity, the association of EMA-reported activities and the Actigraph accelerometer activity counts and number of steps were used. Participants were 36 ± 11 years and 58% were female. On occasions where participants reported physical activity, acceleration counts per minute (CPM) and steps were significantly higher (β = 1184 CPM, CI 95%: 1034, 1334; β = 20.9 steps, CI 95%: 18.2, 23.6) than each of the other EMA activities. Acceleration counts and steps were lower when sitting was reported than when no sitting was reported by EMA. Our study showed that EMA-reported physical activity and sedentary time was significantly associated with accelerometer-derived data. Therefore, EMA can be considered to assess shift workers' movement-related behaviours with accelerometers to provide rich contextual data.
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Affiliation(s)
- Malebogo Monnaatsie
- School of Health and Medical Sciences, Faculty of Health, Engineering and Sciences, University of Southern Queensland, Ipswich, Queensland, Australia
- Centre for Health Research, University of Southern Queensland, Springfield, Queensland, Australia
- Department of Sport Science, Faculty of Education, University of Botswana, Gaborone, Botswana
| | - Gregore I Mielke
- School of Public Health, University of Queensland, Brisbane, Australia
| | - Stuart J H Biddle
- Centre for Health Research, University of Southern Queensland, Springfield, Queensland, Australia
- Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Tracy L Kolbe-Alexander
- School of Health and Medical Sciences, Faculty of Health, Engineering and Sciences, University of Southern Queensland, Ipswich, Queensland, Australia
- Centre for Health Research, University of Southern Queensland, Springfield, Queensland, Australia
- Division of Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
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8
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Cao Z, Min J, Chen H, Hou Y, Yang H, Si K, Xu C. Accelerometer-derived physical activity and mortality in individuals with type 2 diabetes. Nat Commun 2024; 15:5164. [PMID: 38886353 PMCID: PMC11183112 DOI: 10.1038/s41467-024-49542-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 06/10/2024] [Indexed: 06/20/2024] Open
Abstract
Physical activity (PA) has been shown to reduce diabetes mortality, but largely based on imprecise self-reported data, which may hinder the development of related recommendations. Here, we perform a prospective cohort study of 19,624 individuals with type 2 diabetes (T2D) from the UK Biobank with a median follow-up of 6.9 years. Duration and intensity of PA are measured by wrist-worn accelerometers over a 7-day period. We observe L-shaped associations of longer duration of PA, regardless of PA intensity, with risks of all-cause and cancer mortality, as well as a negatively linear association with cardiovascular disease mortality. 12.7%, 15.8%, and 22.3% of deaths are attributable to the lowest level of light-intensity, moderate-intensity PA, and vigorous-intensity PA, respectively. Collectively, our findings provide insights for clinical guidelines that should highlight the potential value of adherence to greater intensity and duration of PA for patients with T2D.
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Affiliation(s)
- Zhi Cao
- School of Public Health, Hangzhou Normal University, Hangzhou, China
- School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiahao Min
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Han Chen
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Yabing Hou
- Yanjing Medical College, Capital Medical University, Beijing, China
| | - Hongxi Yang
- School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Keyi Si
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Chenjie Xu
- School of Public Health, Hangzhou Normal University, Hangzhou, China.
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Armstrong B, Weaver RG, McAninch J, Smith MT, Parker H, Lane AD, Wang Y, Pate R, Rahman M, Matolak D, Chandrashekhar MVS. Development and Calibration of a PATCH Device for Monitoring Children's Heart Rate and Acceleration. Med Sci Sports Exerc 2024; 56:1196-1207. [PMID: 38377012 PMCID: PMC11096080 DOI: 10.1249/mss.0000000000003404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
INTRODUCTION Current wearables that collect heart rate and acceleration were not designed for children and/or do not allow access to raw signals, making them fundamentally unverifiable. This study describes the creation and calibration of an open-source multichannel platform (PATCH) designed to measure heart rate and acceleration in children ages 3-8 yr. METHODS Children (N = 63; mean age, 6.3 yr) participated in a 45-min protocol ranging in intensities from sedentary to vigorous activity. Actiheart-5 was used as a comparison measure. We calculated mean bias, mean absolute error (MAE) mean absolute percent error (MA%E), Pearson correlations, and Lin's concordance correlation coefficient (CCC). RESULTS Mean bias between PATCH and Actiheart heart rate was 2.26 bpm, MAE was 6.67 bpm, and M%E was 5.99%. The correlation between PATCH and Actiheart heart rate was 0.89, and CCC was 0.88. For acceleration, mean bias was 1.16 mg and MAE was 12.24 mg. The correlation between PATCH and Actiheart was 0.96, and CCC was 0.95. CONCLUSIONS The PATCH demonstrated clinically acceptable accuracies to measure heart rate and acceleration compared with a research-grade device.
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Affiliation(s)
- Bridget Armstrong
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | - R. Glenn Weaver
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | - Jonas McAninch
- Department of Electrical Engineering, University of South Carolina, Columbia, SC
| | - Michal T. Smith
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | - Hannah Parker
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | - Abbi D. Lane
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | - Yuan Wang
- Epidemiology and Biostatistics at the University of South Carlina, Columbia, SC
| | - Russ Pate
- Department of Exercise Science, University of South Carolina, Columbia, SC
| | - Mafruda Rahman
- Department of Electrical Engineering, University of South Carolina, Columbia, SC
| | - David Matolak
- Department of Electrical Engineering, University of South Carolina, Columbia, SC
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Finnegan OL, White JW, Armstrong B, Adams EL, Burkart S, Beets MW, Nelakuditi S, Willis EA, von Klinggraeff L, Parker H, Bastyr M, Zhu X, Zhong Z, Weaver RG. The utility of behavioral biometrics in user authentication and demographic characteristic detection: a scoping review. Syst Rev 2024; 13:61. [PMID: 38331893 PMCID: PMC10851515 DOI: 10.1186/s13643-024-02451-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/03/2024] [Indexed: 02/10/2024] Open
Abstract
BACKGROUND Objective measures of screen time are necessary to better understand the complex relationship between screen time and health outcomes. However, current objective measures of screen time (e.g., passive sensing applications) are limited in identifying the user of the mobile device, a critical limitation in children's screen time research where devices are often shared across a family. Behavioral biometrics, a technology that uses embedded sensors on modern mobile devices to continuously authenticate users, could be used to address this limitation. OBJECTIVE The purpose of this scoping review was to summarize the current state of behavioral biometric authentication and synthesize these findings within the scope of applying behavioral biometric technology to screen time measurement. METHODS We systematically searched five databases (Web of Science Core Collection, Inspec in Engineering Village, Applied Science & Technology Source, IEEE Xplore, PubMed), with the last search in September of 2022. Eligible studies were on the authentication of the user or the detection of demographic characteristics (age, gender) using built-in sensors on mobile devices (e.g., smartphone, tablet). Studies were required to use the following methods for authentication: motion behavior, touch, keystroke dynamics, and/or behavior profiling. We extracted study characteristics (sample size, age, gender), data collection methods, data stream, model evaluation metrics, and performance of models, and additionally performed a study quality assessment. Summary characteristics were tabulated and compiled in Excel. We synthesized the extracted information using a narrative approach. RESULTS Of the 14,179 articles screened, 122 were included in this scoping review. Of the 122 included studies, the most highly used biometric methods were touch gestures (n = 76) and movement (n = 63), with 30 studies using keystroke dynamics and 6 studies using behavior profiling. Of the studies that reported age (47), most were performed exclusively in adult populations (n = 34). The overall study quality was low, with an average score of 5.5/14. CONCLUSION The field of behavioral biometrics is limited by the low overall quality of studies. Behavioral biometric technology has the potential to be used in a public health context to address the limitations of current measures of screen time; however, more rigorous research must be performed in child populations first. SYSTEMATIC REVIEW REGISTRATION The protocol has been pre-registered in the Open Science Framework database ( https://doi.org/10.17605/OSF.IO/92YCT ).
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Affiliation(s)
- O L Finnegan
- Department of Exercise Science, University of South Carolina, Columbia, USA.
| | - J W White
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - B Armstrong
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - E L Adams
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - S Burkart
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - M W Beets
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - S Nelakuditi
- Department of Computer Science and Engineering, University of South Carolina, Columbia, USA
| | - E A Willis
- Center for Health Promotion and Disease Prevention, University of North Carolina Chapel Hill, Chapel Hill, USA
| | - L von Klinggraeff
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - H Parker
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - M Bastyr
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - X Zhu
- Department of Exercise Science, University of South Carolina, Columbia, USA
| | - Z Zhong
- Department of Computer Science and Engineering, University of South Carolina, Columbia, USA
| | - R G Weaver
- Department of Exercise Science, University of South Carolina, Columbia, USA
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Weaver RG, White J, Finnegan O, Nelakuditi S, Zhu X, Burkart S, Beets M, Brown T, Pate R, Welk GJ, de Zambotti M, Ghosal R, Wang Y, Armstrong B, Adams EL, Reesor-Oyer L, Pfledderer CD, Bastyr M, von Klinggraeff L, Parker H. A Device Agnostic Approach to Predict Children's Activity from Consumer Wearable Accelerometer Data: A Proof-of-Concept Study. Med Sci Sports Exerc 2024; 56:370-379. [PMID: 37707503 PMCID: PMC10841245 DOI: 10.1249/mss.0000000000003294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
INTRODUCTION This study examined the potential of a device agnostic approach for predicting physical activity from consumer wearable accelerometry compared with a research-grade accelerometry. METHODS Seventy-five 5- to 12-year-olds (58% male, 63% White) participated in a 60-min protocol. Children wore wrist-placed consumer wearables (Apple Watch Series 7 and Garmin Vivoactive 4) and a research-grade device (ActiGraph GT9X) concurrently with an indirect calorimeter (COSMED K5). Activity intensities (i.e., inactive, light, moderate-to-vigorous physical activity) were estimated via indirect calorimetry (criterion), and the Hildebrand thresholds were applied to the raw accelerometer data from the consumer wearables and research-grade device. Epoch-by-epoch (e.g., weighted sensitivity, specificity) and discrepancy (e.g., mean bias, absolute error) analyses evaluated agreement between accelerometry-derived and criterion estimates. Equivalence testing evaluated the equivalence of estimates produced by the consumer wearables and ActiGraph. RESULTS Estimates produced by the raw accelerometry data from ActiGraph, Apple, and Garmin produced similar criterion agreement with weighted sensitivity = 68.2% (95% confidence interval (CI), 67.1%-69.3%), 73.0% (95% CI, 71.8%-74.3%), and 66.6% (95% CI, 65.7%-67.5%), respectively, and weighted specificity = 84.4% (95% CI, 83.6%-85.2%), 82.0% (95% CI, 80.6%-83.4%), and 75.3% (95% CI, 74.7%-75.9%), respectively. Apple Watch produced the lowest mean bias (inactive, -4.0 ± 4.5; light activity, 2.1 ± 4.0) and absolute error (inactive, 4.9 ± 3.4; light activity, 3.6 ± 2.7) for inactive and light physical activity minutes. For moderate-to-vigorous physical activity, ActiGraph produced the lowest mean bias (1.0 ± 2.9) and absolute error (2.8 ± 2.4). No ActiGraph and consumer wearable device estimates were statistically significantly equivalent. CONCLUSIONS Raw accelerometry estimated inactive and light activity from wrist-placed consumer wearables performed similarly to, if not better than, a research-grade device, when compared with indirect calorimetry. This proof-of-concept study highlights the potential of device-agnostic methods for quantifying physical activity intensity via consumer wearables.
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Affiliation(s)
| | | | | | | | | | | | | | - Trey Brown
- University of South Carolina, Columbia, SC
| | - Russ Pate
- University of South Carolina, Columbia, SC
| | | | | | | | - Yuan Wang
- University of South Carolina, Columbia, SC
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12
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White JW, Pfledderer CD, Kinard P, Beets MW, VON Klinggraeff L, Armstrong B, Adams EL, Welk GJ, Burkart S, Weaver RG. Estimating Physical Activity and Sleep using the Combination of Movement and Heart Rate: A Systematic Review and Meta-Analysis. INTERNATIONAL JOURNAL OF EXERCISE SCIENCE 2024; 16:1514-1539. [PMID: 38287938 PMCID: PMC10824314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
The purpose of this meta-analysis was to quantify the difference in physical activity and sleep estimates assessed via 1) movement, 2) heart rate (HR), or 3) the combination of movement and HR (MOVE+HR) compared to criterion indicators of the outcomes. Searches in four electronic databases were executed September 21-24 of 2021. Weighted mean was calculated from standardized group-level estimates of mean percent error (MPE) and mean absolute percent error (MAPE) of the proxy signal compared to the criterion measurement method for physical activity, HR, or sleep. Standardized mean difference (SMD) effect sizes between the proxy and criterion estimates were calculated for each study across all outcomes, and meta-regression analyses were conducted. Two-One-Sided-Tests method were conducted to metaanalytically evaluate the equivalence of the proxy and criterion. Thirty-nine studies (physical activity k = 29 and sleep k = 10) were identified for data extraction. Sample size weighted means for MPE were -38.0%, 7.8%, -1.4%, and -0.6% for physical activity movement only, HR only, MOVE+HR, and sleep MOVE+HR, respectively. Sample size weighted means for MAPE were 41.4%, 32.6%, 13.3%, and 10.8% for physical activity movement only, HR only, MOVE+HR, and sleep MOVE+HR, respectively. Few estimates were statistically equivalent at a SMD of 0.8. Estimates of physical activity from MOVE+HR were not statistically significantly different from estimates based on movement or HR only. For sleep, included studies based their estimates solely on the combination of MOVE+HR, so it was impossible to determine if the combination produced significantly different estimates than either method alone.
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Affiliation(s)
- James W White
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Christopher D Pfledderer
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Parker Kinard
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Michael W Beets
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Lauren VON Klinggraeff
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Bridget Armstrong
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Elizabeth L Adams
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - Gregory J Welk
- Department of Kinesiology, College of Human Sciences, Iowa State University, Ames, Iowa, USA
| | - Sarah Burkart
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
| | - R Glenn Weaver
- Arnold School of Public Health, Department of Exercise Science, University of South Carolina, Columbia, SC, USA
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13
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Carrier B, Salatto RW, Davis DW, Sertic JVL, Barrios B, McGinnis GR, Girouard TJ, Burroughs B, Navalta JW. Assessing the Validity of Several Heart Rate Monitors in Wearable Technology While Mountain Biking. INTERNATIONAL JOURNAL OF EXERCISE SCIENCE 2023; 16:1440-1450. [PMID: 38287935 PMCID: PMC10824301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Purpose This study sought to assess the validity of several heart rate (HR) monitors in wearable technology during mountain biking (MTB), compared to the Polar H7® HR monitor, used as the criterion device. Methods A total of 20 participants completed two MTB trials while wearing six HR monitors (5 test devices, 1 criterion). HR was recorded on a second-by-second basis for all devices analyzed. After data processing, validity measures were calculated, including 1. error analysis: mean absolute percentage errors (MAPE), mean absolute error (MAE), and mean error (ME), and 2. Correlation analysis: Lin's concordance correlation coefficient (CCC) and Pearson's correlation coefficient (r). Thresholds for validity were set at MAPE < 10% and CCC > 0.7. Results The only device that was found to be valid during mountain biking was the Suunto Spartan Sport watch with accompanying HR monitor, with a MAPE of 0.66% and a CCC of 0.99 for the overall, combined data. Conclusion If a person would like to track their HR during mountain biking, for pacing, training, or other reasons, the devices best able to produce valid results are chest-based, wireless electrocardiogram (ECG) monitors, secured by elastic straps to minimize the movement of the device, such as the Suunto chest-based HR monitor.
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Affiliation(s)
- Bryson Carrier
- University of Nevada, Las Vegas; Department of Kinesiology and Nutrition Sciences
| | - R W Salatto
- Vanguard University; Department of Kinesiology
| | - Dustin W Davis
- University of Nevada, Las Vegas; Department of Kinesiology and Nutrition Sciences
| | | | - Brenna Barrios
- University of Nevada, Las Vegas; Department of Kinesiology and Nutrition Sciences
| | - Graham R McGinnis
- University of Nevada, Las Vegas; Department of Kinesiology and Nutrition Sciences
| | - Tedd J Girouard
- University of Nevada, Las Vegas; Department of Kinesiology and Nutrition Sciences
| | - Benjamin Burroughs
- University of Nevada, Las Vegas; Department of Journalism and Media Studies
| | - James W Navalta
- University of Nevada, Las Vegas; Department of Kinesiology and Nutrition Sciences
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14
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Milther C, Winther L, Stahlhut M, Curtis DJ, Aadahl M, Kristensen MT, Sørensen JL, Dall CH. Validation of an accelerometer system for measuring physical activity and sedentary behavior in healthy children and adolescents. Eur J Pediatr 2023; 182:3639-3647. [PMID: 37258775 PMCID: PMC10460328 DOI: 10.1007/s00431-023-05014-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 04/28/2023] [Accepted: 05/01/2023] [Indexed: 06/02/2023]
Abstract
The study aims to assess the concurrent validity of the SENS motion® accelerometer system for device-based measurement of physical activity and sedentary behavior in healthy children and adolescents. Thirty-six healthy children and adolescents (mean ± standard deviation (SD) age, 10.2 ± 2.3 years) were fitted with three SENS sensors while performing standardized activities including walking, fast walking, sitting/lying, and arm movements. Data from the sensors were compared with video observations (reference criteria). The agreement between SENS motion® and observation was analyzed using Student's t-test and illustrated in Bland-Altman plots. The concurrent validity was further evaluated using intraclass correlation coefficient (ICC) and was expressed as standard error of measurement (SEM) and minimal detectable change (MDC). Strong agreement was found between SENS and observation for walking time, sedentary time, and lying time. In contrast, moderate agreement was observed for number of steps, sitting time, and time with and without arm movement. ICC2.1 values were overall moderate to excellent (0.5-0.94), with correspondingly low SEM% for walking time, sedentary time, lying time, and time with arm movement (2-9%). An acceptable SEM% level was reached for both steps and sitting time (11% and 12%). For fast walking time, the results showed a weak agreement between the measurement methods, and the ICC value was poor. CONCLUSION SENS motion® seems valid for detecting physical activity and sedentary behavior in healthy children and adolescents with strong agreement and moderate to excellent ICC values. Furthermore, the explorative results on arm movements seem promising. WHAT IS KNOWN • Inactivity and sedentary behavior follow an increasing trend among children and adolescents. • SENS motion® seems to be valid for measuring physical activity and sedentary behavior in adults and elderly patients. WHAT IS NEW • SENS motion® seems valid with strong agreement between video observations and SENS measurement, and ICC values are moderate to excellent when measuring physical activity and sedentary behavior in healthy children and adolescents. • SENS motion® seems promising for detection of arm movements.
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Affiliation(s)
- Camilla Milther
- Juliane Marie Centre and Mary Elizabeths Hospital, Rigshospitalet, Copenhagen, Denmark.
| | - Lærke Winther
- Juliane Marie Centre and Mary Elizabeths Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Michelle Stahlhut
- Center for Clinical Research and Prevention, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark
| | - Derek John Curtis
- Child Centre Copenhagen, The Child and Youth Administration, City of Copenhagen, Denmark
| | - Mette Aadahl
- Center for Clinical Research and Prevention, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Morten Tange Kristensen
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Physical and Occupational Therapy, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark
| | - Jette Led Sørensen
- Juliane Marie Centre and Mary Elizabeths Hospital, Rigshospitalet, Copenhagen, Denmark
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christian Have Dall
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Physical and Occupational Therapy, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Denmark
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15
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Navalta JW, Davis DW, Malek EM, Carrier B, Bodell NG, Manning JW, Cowley J, Funk M, Lawrence MM, DeBeliso M. Heart rate processing algorithms and exercise duration on reliability and validity decisions in biceps-worn Polar Verity Sense and OH1 wearables. Sci Rep 2023; 13:11736. [PMID: 37474743 PMCID: PMC10359261 DOI: 10.1038/s41598-023-38329-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 07/06/2023] [Indexed: 07/22/2023] Open
Abstract
Consumer wearable technology use is widespread and there is a need to validate measures obtained in uncontrolled settings. Because no standard exists for the treatment of heart rate data during exercise, the effect of different approaches on reliability (Coefficient of Variation [CV], Intraclass Correlation Coefficient [ICC]) and validity (Mean Absolute Percent Error [MAPE], Lin's Concordance Correlation Coefficient [CCC)] were determined in the Polar Verity Sense and OH1 during trail running. The Verity Sense met the reliability (CV < 5%, ICC > 0.7) and validity thresholds (MAPE < 5%, CCC > 0.9) in all cases. The OH1 met reliability thresholds in all cases except entire session average (ICC = 0.57). The OH1 met the validity MAPE threshold in all cases (3.3-4.1%), but not CCC (0.6-0.86). Despite various heart rate data processing methods, the approach may not affect reliability and validity interpretation provided adequate data points are obtained. It is also possible that a large volume of data will artificially inflate metrics.
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Affiliation(s)
- James W Navalta
- Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Las Vegas, NV, USA.
| | - Dustin W Davis
- Interdisciplinary Health Sciences, University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Elias M Malek
- Interdisciplinary Health Sciences, University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Bryson Carrier
- Interdisciplinary Health Sciences, University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Nathaniel G Bodell
- Department of Kinesiology, California State University, San Bernardino, San Bernardino, CA, USA
| | - Jacob W Manning
- Department of Kinesiology and Outdoor Recreation, Southern Utah University, Cedar City, UT, USA
| | - Jeffrey Cowley
- Department of Kinesiology and Outdoor Recreation, Southern Utah University, Cedar City, UT, USA
| | - Merrill Funk
- Department of Kinesiology and Outdoor Recreation, Southern Utah University, Cedar City, UT, USA
| | - Marcus M Lawrence
- Department of Kinesiology and Outdoor Recreation, Southern Utah University, Cedar City, UT, USA
| | - Mark DeBeliso
- Department of Kinesiology and Outdoor Recreation, Southern Utah University, Cedar City, UT, USA
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Radeschi DJ, Senechal E, Tao L, Lv S, Shalish W, Sant'Anna G, Kearney RE. Comparison of Wired and Wireless Heart Rate Monitoring in the Neonatal Intensive Care Unit. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38082891 DOI: 10.1109/embc40787.2023.10340972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
In the Neonatal Intensive Care Unit (NICU), infants' vital signs are monitored on a continuous basis via wired devices. These often interfere with patient care and pose increased risks of skin damage, infection, and tangling around the body. Recently, a wireless system for neonatal monitoring called ANNEⓇ One (Sibel Health, Chicago, USA) was developed. We designed an ongoing study to evaluate the feasibility, reliability and accuracy, of using this system in the NICU. Vital signals were simultaneously acquired by using the standard, wired clinical monitor and the ANNEⓇ device. Data from 10 NICU infants were recorded for 8 hours per day during 4 consecutive days. Initial analysis of the heart rate (HR) data revealed four problems in comparing the signals: 1) gaps in the signals - periods of time for which data were unavailable, 2) wired and wireless signals were sampled at different rates, 3) a delay between the sampled values of wired and wireless signals, and 4) this delay increased with time. To address these problems, we developed a pre-processing algorithm that interpolated samples in short gaps, resampled the signals to an equal rate, estimated the delay and drift rate between corresponding signals, and aligned the signals. Applications of the pre-processing algorithm to 40 recordings demonstrated that it was very effective. A strong agreement between wireless and wired HR signals was seen, with an average correlation of 0.95±0.04, a slope of 1.00, and a variance accounted for 89.56±7.62%. Bland-Altman analysis showed a low bias across the ensemble, with an average difference of 0.11 (95% confidence interval of -0.02 to 0.24) bpm.Clinical relevance- This algorithm provides the means for a detailed comparison of wired and wireless monitors in the NICU.
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O’Brien MW, Neyedli HF, Bosquet L, Leadbetter B, Smith A, Gallant F, Tanguay P, Bélanger M, Mekari S. Convergent validity and inter-rater reliability of a lower-limb multimodal physical function assessment in community-dwelling older adults. FRONTIERS IN AGING 2023; 4:1196389. [PMID: 37408773 PMCID: PMC10318151 DOI: 10.3389/fragi.2023.1196389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 05/22/2023] [Indexed: 07/07/2023]
Abstract
Introduction: Lower-limb physical function declines with age and contributes to a greater difficulty in performing activities of daily living. Existing assessments of lower-limb function assess one dimension of movement in isolation or are not time-efficient, which discourages their use in community and clinical settings. We aimed to address these limitations by assessing the inter-rater reliability and convergent validity of a new multimodal functional lower-limb assessment (FLA). Methods: FLA consists of five major functional movement tasks (rising from a chair, walking gait, stair ascending/descending, obstacle avoidance, and descending to a chair) performed consecutively. A total of 48 community-dwelling older adults (32 female participants; age: 71 ± 6 years) completed the FLA as well as timed up-and-go, 30-s sit-to-stand, and 6-min walk tests. Results: Slower FLA time was correlated with a slower timed up-and-go test (ρ = 0.70), less sit-to-stand repetitions (ρ = -0.65), and a shorter distance in the 6-min walk test (ρ = -0.69; all, p < 0.001). Assessments by two raters were not different (12.28 ± 3.86 s versus 12.29 ± 3.83 s, p = 0.98; inter-rater reliability ρ = 0.993, p < 0.001) and were statistically equivalent (via equivalence testing). Multiple regression and relative weights analyses demonstrated that FLA times were most predicted by the timed up-and-go performance [adjusted R 2 = 0.75; p < 0.001; raw weight 0.42 (95% CI: 0.27, 0.53)]. Discussion: Our findings document the high inter-rater reliability and moderate-strong convergent validity of the FLA. These findings warrant further investigation into the predictive validity of the FLA for its use as an assessment of lower-limb physical function among community-dwelling older adults.
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Affiliation(s)
- Myles W. O’Brien
- School of Physiotherapy (Faculty of Health), Department of Medicine (Faculty of Medicine), Dalhousie University, Halifax, NS, Canada
- Geriatric Medicine Research, Dalhousie University & Nova Scotia Health, Halifax, NS, Canada
| | - Heather F. Neyedli
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, NS, Canada
| | - Laurent Bosquet
- Laboratoire MOVE (UR20296), Université de Poitiers, Faculté des Sciences Du Sport, Poitiers, France
| | - Brianna Leadbetter
- School of Kinesiology, Faculty of Professional Studies, Acadia University, Wolfville, NS, Canada
| | - Alex Smith
- School of Kinesiology, Faculty of Professional Studies, Acadia University, Wolfville, NS, Canada
| | - Francois Gallant
- Department of Family Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Formation Médicale Du Nouveau-Brunswick, Université de Sherbrooke, Moncton, NB, Canada
| | - Pamela Tanguay
- Department of Family Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Formation Médicale Du Nouveau-Brunswick, Université de Sherbrooke, Moncton, NB, Canada
| | - Mathieu Bélanger
- Department of Family Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Formation Médicale Du Nouveau-Brunswick, Université de Sherbrooke, Moncton, NB, Canada
| | - Said Mekari
- Department of Family Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de Formation Médicale Du Nouveau-Brunswick, Université de Sherbrooke, Moncton, NB, Canada
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Giurgiu M, Ketelhut S, Kubica C, Nissen R, Doster AK, Thron M, Timm I, Giurgiu V, Nigg CR, Woll A, Ebner-Priemer UW, Bussmann JBJ. Assessment of 24-hour physical behaviour in adults via wearables: a systematic review of validation studies under laboratory conditions. Int J Behav Nutr Phys Act 2023; 20:68. [PMID: 37291598 DOI: 10.1186/s12966-023-01473-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 05/31/2023] [Indexed: 06/10/2023] Open
Abstract
BACKGROUND Wearable technology is used by consumers and researchers worldwide for continuous activity monitoring in daily life. Results of high-quality laboratory-based validation studies enable us to make a guided decision on which study to rely on and which device to use. However, reviews in adults that focus on the quality of existing laboratory studies are missing. METHODS We conducted a systematic review of wearable validation studies with adults. Eligibility criteria were: (i) study under laboratory conditions with humans (age ≥ 18 years); (ii) validated device outcome must belong to one dimension of the 24-hour physical behavior construct (i.e., intensity, posture/activity type, and biological state); (iii) study protocol must include a criterion measure; (iv) study had to be published in a peer-reviewed English language journal. Studies were identified via a systematic search in five electronic databases as well as back- and forward citation searches. The risk of bias was assessed based on the QUADAS-2 tool with eight signaling questions. RESULTS Out of 13,285 unique search results, 545 published articles between 1994 and 2022 were included. Most studies (73.8% (N = 420)) validated an intensity measure outcome such as energy expenditure; only 14% (N = 80) and 12.2% (N = 70) of studies validated biological state or posture/activity type outcomes, respectively. Most protocols validated wearables in healthy adults between 18 and 65 years. Most wearables were only validated once. Further, we identified six wearables (i.e., ActiGraph GT3X+, ActiGraph GT9X, Apple Watch 2, Axivity AX3, Fitbit Charge 2, Fitbit, and GENEActiv) that had been used to validate outcomes from all three dimensions, but none of them were consistently ranked with moderate to high validity. Risk of bias assessment resulted in 4.4% (N = 24) of all studies being classified as "low risk", while 16.5% (N = 90) were classified as "some concerns" and 79.1% (N = 431) as "high risk". CONCLUSION Laboratory validation studies of wearables assessing physical behaviour in adults are characterized by low methodological quality, large variability in design, and a focus on intensity. Future research should more strongly aim at all components of the 24-hour physical behaviour construct, and strive for standardized protocols embedded in a validation framework.
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Affiliation(s)
- Marco Giurgiu
- Department of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Hertzstr. 16, 76187, Karlsruhe, Germany.
- Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany.
| | - Sascha Ketelhut
- Health Science Department, Institute of Sport Science, University of Bern, Bern, Switzerland
| | - Claudia Kubica
- Health Science Department, Institute of Sport Science, University of Bern, Bern, Switzerland
| | - Rebecca Nissen
- Department of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Hertzstr. 16, 76187, Karlsruhe, Germany
| | - Ann-Kathrin Doster
- Department of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Hertzstr. 16, 76187, Karlsruhe, Germany
| | - Maximiliane Thron
- Department of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Hertzstr. 16, 76187, Karlsruhe, Germany
| | - Irina Timm
- Department of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Hertzstr. 16, 76187, Karlsruhe, Germany
| | - Valeria Giurgiu
- Baden-Wuerttemberg Cooperative State University (DHBW), Karlsruhe, Germany
| | - Claudio R Nigg
- Sport Pedagogy Department, Institute of Sport Science, University of Bern, Bern, Switzerland
| | - Alexander Woll
- Department of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Hertzstr. 16, 76187, Karlsruhe, Germany
| | - Ulrich W Ebner-Priemer
- Department of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Hertzstr. 16, 76187, Karlsruhe, Germany
- Department of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Heidelberg, Germany
| | - Johannes B J Bussmann
- Erasmus MC, Department of Rehabilitation medicine, University Medical Center Rotterdam, Rotterdam, Netherlands
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O’Brien MW, Pellerine LP, Shivgulam ME, Kimmerly DS. Disagreements in physical activity monitor validation study guidelines create challenges in conducting validity studies. Front Digit Health 2023; 4:1063324. [PMID: 36703940 PMCID: PMC9871762 DOI: 10.3389/fdgth.2022.1063324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 12/28/2022] [Indexed: 01/11/2023] Open
Affiliation(s)
- Myles W. O’Brien
- School of Physiotherapy (Faculty of Health) & Division of Geriatric Medicine (Faculty of Medicine), Dalhousie University, Halifax, NS, Canada,Geriatric Medicine Research, Dalhousie University & Nova Scotia Health, Halifax, NS, Canada,Correspondence: Myles W. O'Brien
| | - Liam P. Pellerine
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, NS, Canada
| | - Madeline E. Shivgulam
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, NS, Canada
| | - Derek S. Kimmerly
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, NS, Canada
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Clevenger KA, Mackintosh KA, McNarry MA, Pfeiffer KA, Nelson MB, Bock JM, Imboden MT, Kaminsky LA, Montoye AHK. A consensus method for estimating physical activity levels in adults using accelerometry. J Sports Sci 2022; 40:2393-2400. [PMID: 36576125 DOI: 10.1080/02640414.2022.2159117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Identifying the best analytical approach for capturing moderate-to-vigorous physical activity (MVPA) using accelerometry is complex but inconsistent approaches employed in research and surveillance limits comparability. We illustrate the use of a consensus method that pools estimates from multiple approaches for characterising MVPA using accelerometry. Participants (n = 30) wore an accelerometer on their right hip during two laboratory visits. Ten individual classification methods estimated minutes of MVPA, including cut-point, two-regression, and machine learning approaches, using open-source count and raw inputs and several epoch lengths. Results were averaged to derive the consensus estimate. Mean MVPA ranged from 33.9-50.4 min across individual methods, but only one (38.9 min) was statistically equivalent to the criterion of direct observation (38.2 min). The consensus estimate (39.2 min) was equivalent to the criterion (even after removal of the one individual method that was equivalent to the criterion), had a smaller mean absolute error (4.2 min) compared to individual methods (4.9-12.3 min), and enabled the estimation of participant-level variance (mean standard deviation: 7.7 min). The consensus method allows for addition/removal of methods depending on data availability or field progression and may improve accuracy and comparability of device-based MVPA estimates while limiting variability due to convergence between estimates.
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Affiliation(s)
- Kimberly A Clevenger
- Health Behavior Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland, United States
| | - Kelly A Mackintosh
- Applied Sports, Technology, Exercise and Medicine Research Centre , Swansea University, Swansea, Wales, United Kingdom
| | - Melitta A McNarry
- Applied Sports, Technology, Exercise and Medicine Research Centre , Swansea University, Swansea, Wales, United Kingdom
| | - Karin A Pfeiffer
- Department of Kinesiology, Michigan State University, East Lansing, Michigan, United States
| | - M Benjamin Nelson
- Clinical Exercise Physiology Program, Ball State University, Muncie, Indiana, United States.,Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest University, Winston-Salem, North Carolina, United States
| | - Joshua M Bock
- Clinical Exercise Physiology Program, Ball State University, Muncie, Indiana, United States.,Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, United States
| | - Mary T Imboden
- Clinical Exercise Physiology Program, Ball State University, Muncie, Indiana, United States.,Health & Human Performance Department, George Fox University, Newberg, Oregon, United States.,Health Enhancement Research Organization, Raleigh, North Carolina, United States
| | - Leonard A Kaminsky
- Clinical Exercise Physiology Program, Ball State University, Muncie, Indiana, United States.,Healthy Living for Pandemic Event Protection Network, Chigaco, Illinois, United States
| | - Alexander H K Montoye
- Clinical Exercise Physiology Program, Ball State University, Muncie, Indiana, United States.,Integrative Physiology and Health Science Department, Alma College,Alma, Michigan, United States
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21
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Rissanen APE, Rottensteiner M, Kujala UM, Kurkela JLO, Wikgren J, Laukkanen JA. Cardiorespiratory Fitness Estimation Based on Heart Rate and Body Acceleration in Adults With Cardiovascular Risk Factors: Validation Study. JMIR Cardio 2022; 6:e35796. [PMID: 36282560 PMCID: PMC9644248 DOI: 10.2196/35796] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 08/17/2022] [Accepted: 09/08/2022] [Indexed: 12/05/2022] Open
Abstract
Background Cardiorespiratory fitness (CRF) is an independent risk factor for cardiovascular morbidity and mortality. Adding CRF to conventional risk factors (eg, smoking, hypertension, impaired glucose metabolism, and dyslipidemia) improves the prediction of an individual’s risk for adverse health outcomes such as those related to cardiovascular disease. Consequently, it is recommended to determine CRF as part of individualized risk prediction. However, CRF is not determined routinely in everyday clinical practice. Wearable technologies provide a potential strategy to estimate CRF on a daily basis, and such technologies, which provide CRF estimates based on heart rate and body acceleration, have been developed. However, the validity of such technologies in estimating individual CRF in clinically relevant populations is poorly known. Objective The objective of this study is to evaluate the validity of a wearable technology, which provides estimated CRF based on heart rate and body acceleration, in working-aged adults with cardiovascular risk factors. Methods In total, 74 adults (age range 35-64 years; n=56, 76% were women; mean BMI 28.7, SD 4.6 kg/m2) with frequent cardiovascular risk factors (eg, n=64, 86% hypertension; n=18, 24% prediabetes; n=14, 19% type 2 diabetes; and n=51, 69% metabolic syndrome) performed a 30-minute self-paced walk on an indoor track and a cardiopulmonary exercise test on a treadmill. CRF, quantified as peak O2 uptake, was both estimated (self-paced walk: a wearable single-lead electrocardiogram device worn to record continuous beat-to-beat R-R intervals and triaxial body acceleration) and measured (cardiopulmonary exercise test: ventilatory gas analysis). The accuracy of the estimated CRF was evaluated against that of the measured CRF. Results Measured CRF averaged 30.6 (SD 6.3; range 20.1-49.6) mL/kg/min. In all participants (74/74, 100%), mean difference between estimated and measured CRF was −0.1 mL/kg/min (P=.90), mean absolute error was 3.1 mL/kg/min (95% CI 2.6-3.7), mean absolute percentage error was 10.4% (95% CI 8.5-12.5), and intraclass correlation coefficient was 0.88 (95% CI 0.80-0.92). Similar accuracy was observed in various subgroups (sexes, age, BMI categories, hypertension, prediabetes, and metabolic syndrome). However, mean absolute error was 4.2 mL/kg/min (95% CI 2.6-6.1) and mean absolute percentage error was 16.5% (95% CI 8.6-24.4) in the subgroup of patients with type 2 diabetes (14/74, 19%). Conclusions The error of the CRF estimate, provided by the wearable technology, was likely below or at least very close to the clinically significant level of 3.5 mL/kg/min in working-aged adults with cardiovascular risk factors, but not in the relatively small subgroup of patients with type 2 diabetes. From a large-scale clinical perspective, the findings suggest that wearable technologies have the potential to estimate individual CRF with acceptable accuracy in clinically relevant populations.
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Affiliation(s)
- Antti-Pekka E Rissanen
- Central Finland Health Care District, Jyväskylä, Finland
- Department of Sports and Exercise Medicine, Clinicum, University of Helsinki, Helsinki, Finland
- HULA - Helsinki Sports and Exercise Medicine Clinic, Foundation for Sports and Exercise Medicine, Helsinki, Finland
| | - Mirva Rottensteiner
- Central Finland Health Care District, Jyväskylä, Finland
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Jari L O Kurkela
- Centre for Interdisciplinary Brain Research, Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
| | - Jan Wikgren
- Centre for Interdisciplinary Brain Research, Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
| | - Jari A Laukkanen
- Central Finland Health Care District, Jyväskylä, Finland
- Institute of Clinical Medicine, Department of Medicine, University of Eastern Finland, Kuopio, Finland
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22
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Validity of the activPAL monitor to measure stepping activity and activity intensity: A systematic review. Gait Posture 2022; 97:165-173. [PMID: 35964334 DOI: 10.1016/j.gaitpost.2022.08.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/24/2022] [Accepted: 08/04/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Accumulating step counts and engaging in moderate-to-vigorous intensity physical activity is positively associated with numerous health benefits. The activPAL is a thigh-worn monitor that is frequently used to measure physical activity. RESEARCH QUESTION Can the activPAL accurately measure stepping activity and identify physical activity intensity? METHODS We systematically reviewed validation studies examining the accuracy of activPAL physical activity outcomes relative to a criterion measure in adults (>18 years). Citations were not restricted to language or date of publication. Sources were searched up to May 16, 2021 and included Scopus, EMBASE, MEDLINE, CINAHL, and Academic Search Premier. The study was pre-registered in Prospero (ID# CRD42021248240). Study quality was determined using a modified Hagströmer Bowles checklist. RESULTS Thirty-nine studies (20 laboratory arms, 17 semi-structured arms, 11 uncontrolled protocol arms; 1272 total participants) met the inclusion criteria. Most studies demonstrated a high validity of the activPAL to measure steps across laboratory (12/15 arms), semi-structured (10/13 arms) and uncontrolled conditions (5/7 arms). Studies that demonstrated low validity were generally conducted in unhealthy populations, included slower walking speeds, and/or short walking distances. Few studies indicated that the activPAL accurately measured physical activity intensity across laboratory (0/6 arms), semi-structured (0/5 arms) and uncontrolled conditions (2/5 arms). Using the default settings, the activPAL overestimates light-intensity activity but underestimates moderate-to-vigorous intensity activity. The overall study quality was 11.5 ± 2.0 out of 19. CONCLUSION Despite heterogeneous methodological and statistical approaches, the included studies generally provide supporting evidence that the activPAL can accurately detect stepping activity but not physical activity intensity. Strategies that use alternative data processing methods have been developed to better characterize physical activity intensity, but all methods still underestimate vigorous-intensity activity.
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23
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Martinko A, Karuc J, Jurić P, Podnar H, Sorić M. Accuracy and Precision of Consumer-Grade Wearable Activity Monitors for Assessing Time Spent in Sedentary Behavior in Children and Adolescents: Systematic Review. JMIR Mhealth Uhealth 2022; 10:e37547. [PMID: 35943763 PMCID: PMC9399884 DOI: 10.2196/37547] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 06/06/2022] [Accepted: 06/10/2022] [Indexed: 11/13/2022] Open
Abstract
Background A large number of wearable activity monitor models are released and used each year by consumers and researchers. As more studies are being carried out on children and adolescents in terms of sedentary behavior (SB) assessment, knowledge about accurate and precise monitoring devices becomes increasingly important. Objective The main aim of this systematic review was to investigate and communicate findings on the accuracy and precision of consumer-grade physical activity monitors in assessing the time spent in SB in children and adolescents. Methods Searches of PubMed (MEDLINE), Scopus, SPORTDiscus (full text), ProQuest, Open Access Theses and Dissertations, DART Europe E-theses Portal, and Networked Digital Library of Theses and Dissertations electronic databases were performed. All relevant studies that compared different types of consumer-grade monitors using a comparison method in the assessment of SB, published in European languages from 2015 onward were considered for inclusion. The risk of bias was estimated using Consensus-Based Standards for the Selection of Health Status Measurement Instruments. For enabling comparisons of accuracy measures within the studied outcome domain, measurement accuracy interpretation was based on group mean or percentage error values and 90% CI. Acceptable limits were predefined as –10% to +10% error in controlled and free-living settings. For determining the number of studies with group error percentages that fall within or outside one of the sides from previously defined acceptable limits, two 1-sided tests of equivalence were carried out, and the direction of measurement error was examined. Results A total of 8 studies complied with the predefined inclusion criteria, and 3 studies provided acceptable data for quantitative analyses. In terms of the presented accuracy comparisons, 14 were subsequently identified, with 6 of these comparisons being acceptable in terms of quantitative analysis. The results of the Cochran Q test indicated that the included studies did not share a common effect size (Q5=82.86; P<.001). I2, which represents the percentage of total variation across studies due to heterogeneity, amounted to 94%. The summary effect size based on the random effects model was not statistically significant (effect size=14.36, SE 12.04, 90% CI −5.45 to 34.17; P=.23). According to the equivalence test results, consumer-grade physical activity monitors did not generate equivalent estimates of SB in relation to the comparison methods. Majority of the studies (3/7, 43%) that reported the mean absolute percentage errors have reported values of <30%. Conclusions This is the first study that has attempted to synthesize available evidence on the accuracy and precision of consumer-grade physical activity monitors in measuring SB in children and adolescents. We found very few studies on the accuracy and almost no evidence on the precision of wearable activity monitors. The presented results highlight the large heterogeneity in this area of research. Trial Registration PROSPERO CRD42021251922; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=251922
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Affiliation(s)
| | - Josip Karuc
- Faculty of Kinesiology, University of Zagreb, Zagreb, Croatia
- Proprio Centre, Physical Rehabilitation Centre, Zadar, Croatia
| | - Petra Jurić
- Faculty of Kinesiology, University of Zagreb, Zagreb, Croatia
| | - Hrvoje Podnar
- Faculty of Kinesiology, University of Zagreb, Zagreb, Croatia
| | - Maroje Sorić
- Faculty of Kinesiology, University of Zagreb, Zagreb, Croatia
- Faculty of Sport, University of Ljubljana, Ljubljana, Slovenia
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24
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Giurgiu M, Timm I, Becker M, Schmidt S, Wunsch K, Nissen R, Davidovski D, Bussmann JBJ, Nigg CR, Reichert M, Ebner-Priemer UW, Woll A, von Haaren-Mack B. Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review. JMIR Mhealth Uhealth 2022; 10:e36377. [PMID: 35679106 PMCID: PMC9227659 DOI: 10.2196/36377] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/27/2022] [Accepted: 04/29/2022] [Indexed: 12/13/2022] Open
Abstract
Background Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking. Objective This study aimed to raise researchers’ and consumers’ attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies. Methods Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time). Results Of the 13,285 unique search results, 222 (1.67%) articles were included. Most studies (153/237, 64.6%) validated an intensity measure outcome such as energy expenditure. However, only 19.8% (47/237) validated biological state and 15.6% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1%), Fitbit Flex (20/163, 12.3%), and ActivPAL (12/163, 7.4%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8% (92/237) to 92.4% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6% (11/237) of studies were classified as low risk. Furthermore, 16% (38/237) of studies were classified as having some concerns, and 72.9% (173/237) of studies were classified as high risk. Conclusions Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity.
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Affiliation(s)
- Marco Giurgiu
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Irina Timm
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Marlissa Becker
- Unit Physiotherapy, Department of Orthopedics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Steffen Schmidt
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Kathrin Wunsch
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Rebecca Nissen
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Denis Davidovski
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Johannes B J Bussmann
- Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Claudio R Nigg
- Health Science Department, Institute of Sport Science, University of Bern, Bern, Switzerland
| | - Markus Reichert
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Department of eHealth and Sports Analytics, Faculty of Sport Science, Ruhr-University Bochum, Bochum, Germany
| | - Ulrich W Ebner-Priemer
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Alexander Woll
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Birte von Haaren-Mack
- Department of Health and Social Psychology, Institute of Psychology, German Sport University, Cologne, Germany
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25
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Giurgiu M, Kolb S, Nigg C, Burchartz A, Timm I, Becker M, Rulf E, Doster AK, Koch E, Bussmann JBJ, Nigg C, Ebner-Priemer UW, Woll A. Assessment of 24-hour physical behaviour in children and adolescents via wearables: a systematic review of free-living validation studies. BMJ Open Sport Exerc Med 2022; 8:e001267. [PMID: 35646389 PMCID: PMC9109110 DOI: 10.1136/bmjsem-2021-001267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/19/2022] [Indexed: 11/17/2022] Open
Abstract
Objectives Studies that assess all three dimensions of the integrative 24-hour physical behaviour (PB) construct, namely, intensity, posture/activity type and biological state, are on the rise. However, reviews on validation studies that cover intensity, posture/activity type and biological state assessed via wearables are missing. Design Systematic review. The risk of bias was evaluated by using the QUADAS-2 tool with nine signalling questions separated into four domains (ie, patient selection/study design, index measure, criterion measure, flow and time). Data sources Peer-reviewed validation studies from electronic databases as well as backward and forward citation searches (1970–July 2021). Eligibility criteria for selecting studies Wearable validation studies with children and adolescents (age <18 years). Required indicators: (1) study protocol must include real-life conditions; (2) validated device outcome must belong to one dimension of the 24-hour PB construct; (3) the study protocol must include a criterion measure; (4) study results must be published in peer-reviewed English language journals. Results Out of 13 285 unique search results, 76 articles with 51 different wearables were included and reviewed. Most studies (68.4%) validated an intensity measure outcome such as energy expenditure, but only 15.9% of studies validated biological state outcomes, while 15.8% of studies validated posture/activity type outcomes. We identified six wearables that had been used to validate outcomes from two different dimensions and only two wearables (ie, ActiGraph GT1M and ActiGraph GT3X+) that validated outcomes from all three dimensions. The percentage of studies meeting a given quality criterion ranged from 44.7% to 92.1%. Only 18 studies were classified as ‘low risk’ or ‘some concerns’. Summary Validation studies on biological state and posture/activity outcomes are rare in children and adolescents. Most studies did not meet published quality principles. Standardised protocols embedded in a validation framework are needed. PROSPERO registration number CRD42021230894.
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Affiliation(s)
- Marco Giurgiu
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany
| | - Simon Kolb
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Carina Nigg
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Sport Pedagogy, University of Bern, Bern, Switzerland
| | - Alexander Burchartz
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Irina Timm
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Marlissa Becker
- Department of Orthopedics, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ellen Rulf
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Ann-Kathrin Doster
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Elena Koch
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Johannes B J Bussmann
- Department of Rehabilitation Medicine and Physical Therapy, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Claudio Nigg
- Department of Health Science, University of Bern, Bern, Switzerland
| | - Ulrich W Ebner-Priemer
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Germany.,Department of Sports and Sports Science, Institute of Sports and Sports Science, Karlsruhe, Germany
| | - Alexander Woll
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
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26
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Albrecht BM, Flaßkamp FT, Koster A, Eskofier BM, Bammann K. Cross-sectional survey on researchers' experience in using accelerometers in health-related studies. BMJ Open Sport Exerc Med 2022; 8:e001286. [PMID: 35601138 PMCID: PMC9086608 DOI: 10.1136/bmjsem-2021-001286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/07/2022] [Indexed: 11/17/2022] Open
Abstract
Objectives Accelerometers are widely applied in health studies, but lack of standardisation regarding device placement, sampling and data processing hampers comparability between studies. The objectives of this study were to assess how accelerometers are applied in health-related research and problems with accelerometer hardware and software encountered by researchers. Methods Researchers applying accelerometry in a health context were invited to a cross-sectional web-based survey (August 2020–September 2020). The questionnaire included quantitative questions regarding the application of accelerometers and qualitative questions on encountered hardware and software problems. Descriptive statistics were calculated for quantitative data and content analysis was applied to qualitative data. Results In total, 116 health researchers were included in the study (response: 13.7%). The most used brand was ActiGraph (67.2%). Independently of brand, the main reason for choosing a device was that it was the standard in the field (57.1%–83.3%). In children and adolescent populations, sampling frequency was higher (mean: 73.3 Hz ±29.9 Hz vs 47.6 Hz ±29.4 Hz) and epoch length (15.0s±15.6s vs 30.1s±25.9s) and non-wear time (42.9 min ±23.7 min vs 65.3 min ±35.4 min) were shorter compared with adult populations. Content analysis revealed eight categories of hardware problems (battery problems, compliance issues, data loss, mechanical problems, electronic problems, sensor problems, lacking waterproofness, other problems) and five categories of software problems (lack of user-friendliness, limited possibilities, bugs, high computational burden, black box character). Conclusions The study confirms heterogeneity regarding accelerometer use in health-related research. Moreover, several hardware and software problems were documented. Both aspects must be tackled to increase validity, practicability and comparability of research.
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Affiliation(s)
- Birte Marie Albrecht
- Institute for Public Health and Nursing Research (IPP), University of Bremen, Bremen, Germany.,Leibniz ScienceCampus Digital Public Health, Bremen, Germany
| | - Fabian Tristan Flaßkamp
- Institute for Public Health and Nursing Research (IPP), University of Bremen, Bremen, Germany.,Leibniz ScienceCampus Digital Public Health, Bremen, Germany
| | - Annemarie Koster
- Department of Social Medicine, CAPHRI, Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands
| | - Bjoern M Eskofier
- Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander University Erlangen-Nuernberg, Erlangen, Germany
| | - Karin Bammann
- Institute for Public Health and Nursing Research (IPP), University of Bremen, Bremen, Germany.,Leibniz ScienceCampus Digital Public Health, Bremen, Germany
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27
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O'Brien MW, Petterson JL, Johns JA, Mekary S, Kimmerly DS. The impact of different step rate threshold methods on physical activity intensity in older adults. Gait Posture 2022; 94:51-57. [PMID: 35247825 DOI: 10.1016/j.gaitpost.2022.02.030] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 02/04/2022] [Accepted: 02/24/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Older adults benefit most from engaging in higher-intensity physical activity, which is often determined using step rate thresholds. Fixed step rate thresholds that correspond to moderate (MPA) and vigorous-intensity physical activity (VPA) have been developed for heuristic activity promotion. The activPAL monitor uses step rate thresholds to determine activity intensity. Stepping thresholds may also vary based on body mass index (BMI) or aerobic fitness level in older adults. Despite the various thresholds used in the literature, it is unclear whether they produce similar outcomes. RESEARCH QUESTION How does time spent in physical activity intensities compare between different step rate thresholds in older adults? METHODS Thirty-eight participants (24♀; 67 ± 4 years; BMI: 26.6 ± 4.4 kg/m2) wore an activPAL monitor 24-hr/day for up to 7-d (total: 205-d). Aerobic fitness (V̇O2max: 23 ± 8 ml/kg/min) was determined via indirect calorimetry during a maximal, graded cycling test. Time spent in each intensity category (light-physical-activity [LPA], MPA, VPA) was determined using the fixed (MPA/VPA) 100/130, 110/130, and activPAL step rate thresholds (74/212), as well as BMI-adjusted absolute (108.5 ± 2.5/134.0 ± 4.8) and BMI-adjusted relative (40%/60% V̇O2max; 111.4 ± 14.7/132.0 ± 19.0) cut-offs. Times spent in each intensity category were compared between methods. RESULTS The activPAL and 100/130 thresholds yielded less LPA and more MPA than all other methods. The activPAL had no time spent in VPA at all. The BMI-adjusted absolute and relative thresholds produced statistically equivalent time in LPA and MPA (via equivalence testing), but not VPA. No two methods yielded similar time spent in LPA, MPA, or VPA. SIGNIFICANCE The choice of step rate threshold has a major impact on physical activity intensity outcomes in older adults. Inherently, strategies that adjust for older adults' body size and/or aerobic fitness level provide a more individualized data processing strategy than fixed thresholds that assume the same threshold for all older adults.
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Affiliation(s)
- Myles W O'Brien
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada.
| | - Jennifer L Petterson
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Jarrett A Johns
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Said Mekary
- Department of Family Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | - Derek S Kimmerly
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada
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Validity of the ActivPAL monitor to distinguish postures: A systematic review. Gait Posture 2022; 94:107-113. [PMID: 35276456 DOI: 10.1016/j.gaitpost.2022.03.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 02/13/2022] [Accepted: 03/03/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Posture has been recently integrated into activity guidelines, advising people to limit their sedentary time and break up sedentary postures with standing/stepping as much as possible. The thigh-worn activPAL is a frequently used objective measure of posture, but its validity has only been investigated by individual studies and has not been systematically reviewed. RESEARCH QUESTION Can the activPAL accurately characterize different postures? METHODS A rigorous systematic review protocol was conducted, including multiple study screeners and determiners of study quality. To be included, validation studies had to examine the accuracy of an activPAL posture outcome relative to a criterion measure (e.g., direct observation) in adults (>18 years). Citations were not restricted to language or date of publication. Sources were searched on May 16, 2021 and included Scopus, EMBASE, MEDLINE, CINAHL, and Academic Search Premier. The study was pre-registered in Prospero (ID# CRD42021248240). Study quality was determined using a modified Hagströmer Bowles checklist. The results are presented narratively. RESULTS Twenty-four studies (18 semi-structured laboratory arms, 8 uncontrolled protocol arms; 476 participants) met the inclusion criteria. Some studies (5/24) incorporated dual-monitor (trunk: 4/5; shin: 1/5) configurations. While heterogenous statistical procedures were implemented, most studies (n = 22/24) demonstrated a high validity (e.g., percent agreement >90%, no fixed bias, etc.) of the activPAL to measure sedentary and/or upright postures across semi-structured (17/18 arms) and uncontrolled study designs (7/8 arms). Specific experimental protocol factors (i.e., seat height, fidgeting, non-direct observation criterion comparator) likely explain the divergent reports that observed valid versus invalid findings. The study quality was 11.3 (standard deviation: 2.3) out of 19. CONCLUSION Despite heterogeneous methodological and statistical approaches, the included studies generally provide supporting evidence that the activPAL can accurately distinguish between sedentary and standing postures. Multiple activPAL monitor configurations (e.g., thigh and torso) are needed to better characterize sitting versus lying postures.
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Chevance G, Golaszewski NM, Tipton E, Hekler EB, Buman M, Welk GJ, Patrick K, Godino JG. Accuracy and Precision of Energy Expenditure, Heart Rate, and Steps Measured by Combined-Sensing Fitbits Against Reference Measures: Systematic Review and Meta-analysis. JMIR Mhealth Uhealth 2022; 10:e35626. [PMID: 35416777 PMCID: PMC9047731 DOI: 10.2196/35626] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/27/2022] [Accepted: 02/10/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Although it is widely recognized that physical activity is an important determinant of health, assessing this complex behavior is a considerable challenge. OBJECTIVE The purpose of this systematic review and meta-analysis is to examine, quantify, and report the current state of evidence for the validity of energy expenditure, heart rate, and steps measured by recent combined-sensing Fitbits. METHODS We conducted a systematic review and Bland-Altman meta-analysis of validation studies of combined-sensing Fitbits against reference measures of energy expenditure, heart rate, and steps. RESULTS A total of 52 studies were included in the systematic review. Among the 52 studies, 41 (79%) were included in the meta-analysis, representing 203 individual comparisons between Fitbit devices and a criterion measure (ie, n=117, 57.6% for heart rate; n=49, 24.1% for energy expenditure; and n=37, 18.2% for steps). Overall, most authors of the included studies concluded that recent Fitbit models underestimate heart rate, energy expenditure, and steps compared with criterion measures. These independent conclusions aligned with the results of the pooled meta-analyses showing an average underestimation of -2.99 beats per minute (k comparison=74), -2.77 kcal per minute (k comparison=29), and -3.11 steps per minute (k comparison=19), respectively, of the Fitbit compared with the criterion measure (results obtained after removing the high risk of bias studies; population limit of agreements for heart rate, energy expenditure, and steps: -23.99 to 18.01, -12.75 to 7.41, and -13.07 to 6.86, respectively). CONCLUSIONS Fitbit devices are likely to underestimate heart rate, energy expenditure, and steps. The estimation of these measurements varied by the quality of the study, age of the participants, type of activities, and the model of Fitbit. The qualitative conclusions of most studies aligned with the results of the meta-analysis. Although the expected level of accuracy might vary from one context to another, this underestimation can be acceptable, on average, for steps and heart rate. However, the measurement of energy expenditure may be inaccurate for some research purposes.
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Affiliation(s)
| | - Natalie M Golaszewski
- Herbert Wertheim School of Public Health and Longevity Science, University of California, San Diego, La Jolla, CA, United States
- Center for Wireless & Population Health Systems, University of California, San Diego, La Jolla, CA, United States
| | - Elizabeth Tipton
- Department of Statistics, Northwestern University, Evanston, IL, United States
| | - Eric B Hekler
- Herbert Wertheim School of Public Health and Longevity Science, University of California, San Diego, La Jolla, CA, United States
- Center for Wireless & Population Health Systems, University of California, San Diego, La Jolla, CA, United States
- Exercise and Physical Activity Resource Center, University of California, San Diego, La Jolla, CA, United States
| | - Matthew Buman
- School of Nutrition & Health Promotion, Arizona State University, Phoenix, AZ, United States
| | - Gregory J Welk
- Department of Kinesiology, Iowa State University, Ames, IA, United States
| | - Kevin Patrick
- Center for Wireless & Population Health Systems, University of California, San Diego, La Jolla, CA, United States
| | - Job G Godino
- Herbert Wertheim School of Public Health and Longevity Science, University of California, San Diego, La Jolla, CA, United States
- Center for Wireless & Population Health Systems, University of California, San Diego, La Jolla, CA, United States
- Exercise and Physical Activity Resource Center, University of California, San Diego, La Jolla, CA, United States
- Laura Rodriguez Research Institute, Family Health Centers of San Diego, San Diego, CA, United States
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Molina-Garcia P, Notbohm HL, Schumann M, Argent R, Hetherington-Rauth M, Stang J, Bloch W, Cheng S, Ekelund U, Sardinha LB, Caulfield B, Brønd JC, Grøntved A, Ortega FB. Validity of Estimating the Maximal Oxygen Consumption by Consumer Wearables: A Systematic Review with Meta-analysis and Expert Statement of the INTERLIVE Network. Sports Med 2022; 52:1577-1597. [PMID: 35072942 PMCID: PMC9213394 DOI: 10.1007/s40279-021-01639-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/20/2021] [Indexed: 11/27/2022]
Abstract
Background Technological advances have recently made possible the estimation of maximal oxygen consumption (VO2max) by consumer wearables. However, the validity of such estimations has not been systematically summarized using meta-analytic methods and there are no standards guiding the validation protocols. Objective The aim was to (1) quantitatively summarize previous studies investigating the validity of the VO2max estimated by consumer wearables and (2) provide best-practice recommendations for future validation studies. Methods First, we conducted a systematic review and meta-analysis of studies validating the estimation of VO2max by wearables. Second, based on the state of knowledge (derived from the systematic review) combined with the expert discussion between the members of the Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) consortium, we provided a set of best-practice recommendations for validation protocols. Results Fourteen validation studies were included in the systematic review and meta-analysis. Meta-analysis results revealed that wearables using resting condition information in their algorithms significantly overestimated VO2max (bias 2.17 ml·kg−1·min−1; limits of agreement − 13.07 to 17.41 ml·kg−1·min−1), while devices using exercise-based information in their algorithms showed a lower systematic and random error (bias − 0.09 ml·kg−1·min−1; limits of agreement − 9.92 to 9.74 ml·kg−1·min−1). The INTERLIVE consortium proposed six key domains to be considered for validating wearable devices estimating VO2max, concerning the following: the target population, reference standard, index measure, testing conditions, data processing, and statistical analysis. Conclusions Our meta-analysis suggests that the estimations of VO2max by wearables that use exercise-based algorithms provide higher accuracy than those based on resting conditions. The exercise-based estimation seems to be optimal for measuring VO2max at the population level, yet the estimation error at the individual level is large, and, therefore, for sport/clinical purposes these methods still need improvement. The INTERLIVE network hereby provides best-practice recommendations to be used in future protocols to move towards a more accurate, transparent and comparable validation of VO2max derived from wearables. PROSPERO ID CRD42021246192. Supplementary Information The online version contains supplementary material available at 10.1007/s40279-021-01639-y.
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Affiliation(s)
- Pablo Molina-Garcia
- PROFITH (PROmoting FITness and Health Through Physical Activity) Research Group, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Carretera de Alfacar s/n, 18071, Granada, Spain. .,Physical Medicine and Rehabilitation Service, Biohealth Research Institute, Virgen de Las Nieves University Hospital, Jaén Street, s/n, 18013, Granada, Spain.
| | - Hannah L Notbohm
- Institute of Cardiovascular Research and Sports Medicine, Department of Molecular and Cellular Sports Medicine, German Sport University, Cologne, Germany
| | - Moritz Schumann
- Institute of Cardiovascular Research and Sports Medicine, Department of Molecular and Cellular Sports Medicine, German Sport University, Cologne, Germany.,Department of Physical Education, Exercise Translational Medicine Centre, The Key Laboratory of Systems Biomedicine, Ministry of Education, and Exercise, Health and Technology Centre, Shanghai Jiao Tong University, Shanghai, China
| | - Rob Argent
- Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland.,School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland.,School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Megan Hetherington-Rauth
- Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universida de de Lisboa, Lisbon, Portugal
| | - Julie Stang
- Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway
| | - Wilhelm Bloch
- Institute of Cardiovascular Research and Sports Medicine, Department of Molecular and Cellular Sports Medicine, German Sport University, Cologne, Germany
| | - Sulin Cheng
- Institute of Cardiovascular Research and Sports Medicine, Department of Molecular and Cellular Sports Medicine, German Sport University, Cologne, Germany.,Department of Physical Education, Exercise Translational Medicine Centre, The Key Laboratory of Systems Biomedicine, Ministry of Education, and Exercise, Health and Technology Centre, Shanghai Jiao Tong University, Shanghai, China
| | - Ulf Ekelund
- Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway
| | - Luis B Sardinha
- Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universida de de Lisboa, Lisbon, Portugal
| | - Brian Caulfield
- Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland.,School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland
| | - Jan Christian Brønd
- Department of Sports Science and Clinical Biomechanics, Research Unit for Exercise Epidemiology, Centre of Research in Childhood Health, University of Southern Denmark, Odense M, Denmark
| | - Anders Grøntved
- Department of Sports Science and Clinical Biomechanics, Research Unit for Exercise Epidemiology, Centre of Research in Childhood Health, University of Southern Denmark, Odense M, Denmark
| | - Francisco B Ortega
- PROFITH (PROmoting FITness and Health Through Physical Activity) Research Group, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Carretera de Alfacar s/n, 18071, Granada, Spain. .,Faculty of Sport and Health Sciences, University of Jyväskylä, Jyvaskyla, Finland. .,Department of Bioscience and Nutrition, Karolinska Institutet, Huddinge, Sweden.
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Argent R, Hetherington-Rauth M, Stang J, Tarp J, Ortega FB, Molina-Garcia P, Schumann M, Bloch W, Cheng S, Grøntved A, Brønd JC, Ekelund U, Sardinha LB, Caulfield B. Recommendations for Determining the Validity of Consumer Wearables and Smartphones for the Estimation of Energy Expenditure: Expert Statement and Checklist of the INTERLIVE Network. Sports Med 2022; 52:1817-1832. [PMID: 35260991 PMCID: PMC9325806 DOI: 10.1007/s40279-022-01665-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2022] [Indexed: 01/22/2023]
Abstract
BACKGROUND Consumer wearables and smartphone devices commonly offer an estimate of energy expenditure (EE) to assist in the objective monitoring of physical activity to the general population. Alongside consumers, healthcare professionals and researchers are seeking to utilise these devices for the monitoring of training and improving human health. However, the methods of validation and reporting of EE estimation in these devices lacks rigour, negatively impacting on the ability to make comparisons between devices and provide transparent accuracy. OBJECTIVES The Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The network was founded in 2019 and strives towards developing best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice validation protocol for consumer wearables and smartphones in the estimation of EE. METHODS The recommendations were developed through (1) a systematic literature review; (2) an unstructured review of the wider literature discussing the potential factors that may introduce bias during validation studies; and (3) evidence-informed expert opinions from members of the INTERLIVE network. RESULTS The systematic literature review process identified 1645 potential articles, of which 62 were deemed eligible for the final dataset. Based on these studies and the wider literature search, a validation framework is proposed encompassing six key domains for validation: the target population, criterion measure, index measure, testing conditions, data processing and the statistical analysis. CONCLUSIONS The INTERLIVE network recommends that the proposed protocol, and checklists provided, are used to standardise the testing and reporting of the validation of any consumer wearable or smartphone device to estimate EE. This in turn will maximise the potential utility of these technologies for clinicians, researchers, consumers, and manufacturers/developers, while ensuring transparency, comparability, and replicability in validation. TRIAL REGISTRATION PROSPERO ID: CRD42021223508.
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Affiliation(s)
- Rob Argent
- Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland ,School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland ,School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Megan Hetherington-Rauth
- Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
| | - Julie Stang
- Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway
| | - Jakob Tarp
- Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway
| | - Francisco B. Ortega
- PROFITH (PROmoting FITness and Health Through Physical Activity) Research Group, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain ,Department of Bioscience and Nutrition, Karolinska Institutet, Solna, Sweden
| | - Pablo Molina-Garcia
- PROFITH (PROmoting FITness and Health Through Physical Activity) Research Group, Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Granada, Spain
| | - Moritz Schumann
- Institute of Cardiovascular Research and Sports Medicine, Department of Molecular and Cellular Sports Medicine, German Sport University, Cologne, Germany ,Exercise Translational Medicine Centre, the Key Laboratory of Systems Biomedicine, Ministry of Education, and Exercise, Health and Technology Centre, Department of Physical Education, Shanghai Jiao Tong University, Shanghai, China
| | - Wilhelm Bloch
- Institute of Cardiovascular Research and Sports Medicine, Department of Molecular and Cellular Sports Medicine, German Sport University, Cologne, Germany
| | - Sulin Cheng
- Institute of Cardiovascular Research and Sports Medicine, Department of Molecular and Cellular Sports Medicine, German Sport University, Cologne, Germany ,Exercise Translational Medicine Centre, the Key Laboratory of Systems Biomedicine, Ministry of Education, and Exercise, Health and Technology Centre, Department of Physical Education, Shanghai Jiao Tong University, Shanghai, China ,Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Anders Grøntved
- Department of Sports Science and Clinical Biomechanics, Research Unit for Exercise Epidemiology, Centre of Research in Childhood Health, University of Southern Denmark, Odense M, Denmark
| | - Jan Christian Brønd
- Department of Sports Science and Clinical Biomechanics, Research Unit for Exercise Epidemiology, Centre of Research in Childhood Health, University of Southern Denmark, Odense M, Denmark
| | - Ulf Ekelund
- Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway
| | - Luis B. Sardinha
- Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
| | - Brian Caulfield
- Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland ,School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland
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A Transparent Method for Step Detection using an Acceleration Threshold. JOURNAL FOR THE MEASUREMENT OF PHYSICAL BEHAVIOUR 2021; 4:311-320. [PMID: 36274923 PMCID: PMC9586317 DOI: 10.1123/jmpb.2021-0011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Step-based metrics provide simple measures of ambulatory activity, yet device software either includes undisclosed proprietary step detection algorithms or simply do not compute step-based metrics. We aimed to develop and validate a simple algorithm to accurately detect steps across various ambulatory and non-ambulatory activities. Seventy-five adults (21-39 years) completed seven simulated activities of daily living (e.g., sitting, vacuuming, folding laundry) and an incremental treadmill protocol from 0.22-2.2ms-1. Directly observed steps were hand-tallied. Participants wore GENEActiv and ActiGraph accelerometers, one of each on their waist and on their non-dominant wrist. Raw acceleration (g) signals from the anterior-posterior, medial-lateral, vertical, and vector magnitude (VM) directions were assessed separately for each device. Signals were demeaned across all activities and bandpass filtered [0.25, 2.5Hz]. Steps were detected via peak picking, with optimal thresholds (i.e., minimized absolute error from accumulated hand counted) determined by iterating minimum acceleration values to detect steps. Step counts were converted into cadence (steps/minute), and k-fold cross-validation quantified error (root mean squared error [RMSE]). We report optimal thresholds for use of either device on the waist (threshold=0.0267g) and wrist (threshold=0.0359g) using the VM signal. These thresholds yielded low error for the waist (RMSE<173 steps, ≤2.28 steps/minute) and wrist (RMSE<481 steps, ≤6.47 steps/minute) across all activities, and outperformed ActiLife's proprietary algorithm (RMSE=1312 and 2913 steps, 17.29 and 38.06 steps/minute for the waist and wrist, respectively). The thresholds reported herein provide a simple, transparent framework for step detection using accelerometers during treadmill ambulation and activities of daily living for waist- and wrist-worn locations.
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Kwon S, Kim Y, Bai Y, Burns RD, Brusseau TA, Byun W. Validation of the Apple Watch for Estimating Moderate-to-Vigorous Physical Activity and Activity Energy Expenditure in School-Aged Children. SENSORS 2021; 21:s21196413. [PMID: 34640733 PMCID: PMC8512453 DOI: 10.3390/s21196413] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 09/08/2021] [Accepted: 09/19/2021] [Indexed: 12/18/2022]
Abstract
The Apple Watch is one of the most popular wearable devices designed to monitor physical activity (PA). However, it is currently unknown whether the Apple Watch accurately estimates children’s free-living PA. Therefore, this study assessed the concurrent validity of the Apple Watch 3 in estimating moderate-to-vigorous physical activity (MVPA) time and active energy expenditure (AEE) for school-aged children under a simulated and a free-living condition. Twenty elementary school students (Girls: 45%, age: 9.7 ± 2.0 years) wore an Apple Watch 3 device on their wrist and performed prescribed free-living activities in a lab setting. A subgroup of participants (N = 5) wore the Apple Watch for seven consecutive days in order to assess the validity in free-living condition. The K5 indirect calorimetry (K5) and GT3X+ were used as the criterion measure under simulated free-living and free-living conditions, respectively. Mean absolute percent errors (MAPE) and Bland-Altman (BA) plots were conducted to assess the validity of the Apple Watch 3 compared to those from the criterion measures. Equivalence testing determined the statistical equivalence between the Apple Watch and K5 for MVPA time and AEE. The Apple Watch provided comparable estimates for MVPA time (mean bias: 0.3 min, p = 0.91, MAPE: 1%) and for AEE (mean bias: 3.8 kcal min, p = 0.75, MAPE: 4%) during the simulated free-living condition. The BA plots indicated no systematic bias for the agreement in MVPA and AEE estimates between the K5 and Apple Watch 3. However, the Apple Watch had a relatively large variability in estimating AEE in children. The Apple Watch was statistically equivalent to the K5 within ±17.7% and ±20.8% for MVPA time and AEE estimates, respectively. Our findings suggest that the Apple Watch 3 has the potential to be used as a PA assessment tool to estimate MVPA in school-aged children.
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Affiliation(s)
- Sunku Kwon
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (Y.B.); (R.D.B.); (T.A.B.)
| | - Youngwon Kim
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China;
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SL, UK
| | - Yang Bai
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (Y.B.); (R.D.B.); (T.A.B.)
| | - Ryan D. Burns
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (Y.B.); (R.D.B.); (T.A.B.)
| | - Timothy A. Brusseau
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (Y.B.); (R.D.B.); (T.A.B.)
| | - Wonwoo Byun
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (Y.B.); (R.D.B.); (T.A.B.)
- Correspondence: ; Tel.: +1-801-583-1119
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Validity, Reliability and Sensitivity to Change of Three Consumer-Grade Activity Trackers in Controlled and Free-Living Conditions among Older Adults. SENSORS 2021; 21:s21186245. [PMID: 34577457 PMCID: PMC8473032 DOI: 10.3390/s21186245] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/05/2021] [Accepted: 09/13/2021] [Indexed: 12/16/2022]
Abstract
Wrist-worn consumer-grade activity trackers are popular devices, developed mainly for personal use. This study aimed to explore the validity, reliability and sensitivity to change of movement behaviors metrics from three activity trackers (Polar Vantage M, Garmin Vivoactive 4s and Garmin Vivosport) in controlled and free-living conditions when worn by older adults. Participants (n = 28; 74 ± 5 years) underwent a videotaped laboratory protocol while wearing all three trackers. On a separate occasion, participants (n = 17 for each of the trackers) wore one (randomly assigned) tracker and a research-grade activity monitor ActiGraph wGT3X-BT simultaneously for six consecutive days. Both Garmin trackers showed excellent performance for step counts, with a mean absolute percentage error (MAPE) below 20% and intraclass correlation coefficient (ICC2,1) above 0.90 (p < 0.05). The MAPE for sleep time was within 10% for all the trackers tested, while it was far beyond 20% for all other movement behaviors metrics. The results suggested that all three trackers could be used for measuring sleep time with a high level of accuracy, and both Garmin trackers could also be used for step counts. All other output metrics should be used with caution. The results provided in this study could be used to guide choice on activity trackers aiming for different purposes—individual use, longitudinal monitoring or in clinical trial setting.
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O'Brien MW, Wu Y, Johns JA, Poitras J, Kimmerly DS. Development and validation of an activPAL accelerometry count-based model of physical activity intensity in adults. Med Eng Phys 2021; 95:45-50. [PMID: 34479692 DOI: 10.1016/j.medengphy.2021.07.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/08/2021] [Accepted: 07/19/2021] [Indexed: 11/16/2022]
Abstract
The activPAL linear cadence-metabolic equivalents (METs) equation poorly estimates activity intensity. The magnitude of acceleration in three directional planes may be a superior predictor of activity intensity than stepping cadence, with accelerometry count thresholds developed in children/adolescent populations. We extracted the proprietary accelerometer-derived information to develop a counts-METs model and cross-validates it in laboratory and free-living conditions. Forty adults (25±6 years) wore an activPAL during a 7-stage progressive treadmill protocol (criterion: indirect calorimetry). Tri-axial accelerometry-derived activity counts (vector magnitude) and METs data from a subset of participants (n = 20) were modelled (R2=0.76) and the regression equation evaluated in the remaining participants (n = 20). Thirty-two of these participants wore the activPAL during free-living conditions (n = 192-d; criterion: PiezoRxD monitor). The absolute percent error of the counts-METs model in the laboratory cross-validation was 18±13%, with equivalence testing determinining equivalent MET values to indirect calorimetry during the slowest (1.5 mph) and fastest (4.0-4.5 mph) stages. In free-living conditions, the model accurately quantified light- and moderate-intensity physical activity but underestimated vigorous-intensity activity (6.5±11.3 vs. 5.5±20.8 mins/day; p < 0.001). We developed and present a data analysis method using the activPAL tri-axial accelerometry counts to improve estimations of physical activity intensity in controlled laboratory settings and uncontrolled free-living settings.
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Affiliation(s)
- Myles W O'Brien
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada.
| | - Yanlin Wu
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Jarrett A Johns
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Justine Poitras
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Derek S Kimmerly
- Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Nova Scotia, Canada
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Welk GJ, Saint-Maurice PF, Dixon PM, Hibbing PR, Bai Y, McLoughlin GM, da Silva MP. Calibration of the Online Youth Activity Profile Assessment for School-Based Applications. JOURNAL FOR THE MEASUREMENT OF PHYSICAL BEHAVIOUR 2021; 4:236-246. [PMID: 38223785 PMCID: PMC10785831 DOI: 10.1123/jmpb.2020-0048] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
A balance between the feasibility and validity of measures is an important consideration for physical activity research - particularly in school-based research with youth. The present study extends previously tested calibration methods to develop and test new equations for an online version of the Youth Activity Profile (YAP) tool, a self-report tool designed for school applications. Data were collected across different regions and seasons to develop more robust, generalizable equations. The study involved a total of 717 youth from 33 schools (374 elementary (ages 9-11), 224 middle (ages 11-14), and 119 high school (ages 14-18)) in two different states in the U.S. Participants wore a Sensewear monitor for a full week and then completed the online YAP at school to report physical activity (PA) and sedentary behaviors (SB) in school and at home. Accelerometer data were processed using an R-based segmentation program to compute PA and SB levels. Quantile regression models were used with half of the sample to develop item-specific YAP calibration equations and these were cross validated with the remaining half of the sample. Computed values of Mean Absolute Percent Error (MAPE) ranged from 15-25% with slightly lower error observed for the middle school sample. The new equations had improved precision compared to the previous versions when tested on the same sample. The online version of the YAP provides an efficient and effective way to capture school level estimates of PA and SB in youth.
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Agreement Between StepWatch3 and ActiGraph wGT3X+ for Measuring Step-Based Metrics in People With Peripheral Artery Disease. J Aging Phys Act 2021; 30:225-236. [PMID: 34438366 DOI: 10.1123/japa.2020-0499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 04/10/2021] [Accepted: 04/18/2021] [Indexed: 11/18/2022]
Abstract
The authors investigated the agreement between StepWatch3™ (SW3) and ActiGraph™ wGT3X+ monitors for measuring step-based metrics in patients with peripheral artery disease and older adults. In 23 patients with peripheral artery disease and 38 older participants, the authors compared the metrics obtained during an outdoor (400-m track) walking session (step count) and a 7-day free-living period (step count and 60/30/5/1-min maximal or peak step accumulation) using the SW3 (ankle) and the wGT3X+ (hip) with the low-frequency extension filter enabled (wGT3X+/LFE) or not (wGT3X+/N). During outdoor walking session, agreement was high, particularly for wGT3X+/LFE: correlations ≥.98, median absolute percentage errors <1%, and significant equivalence using a ± 15% equivalence zone or narrower. In free living, no wGT3X+ method was equivalent to SW3 for step count. The wGT3X+/LFE was equivalent to SW3 regarding all step accumulation metrics using a ± 20% equivalence zone or narrower, with median absolute percentage errors <11%. The wGT3X+/LFE method is the best option for comparisons with SW3 in peripheral artery disease and older adults.
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Gould ZR, Mora-Gonzalez J, Aguiar EJ, Schuna JM, Barreira TV, Moore CC, Staudenmayer J, Tudor-Locke C. A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-Kids study. Int J Behav Nutr Phys Act 2021; 18:97. [PMID: 34271922 PMCID: PMC8283935 DOI: 10.1186/s12966-021-01167-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 06/30/2021] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND Wearable technologies play an important role in measuring physical activity (PA) and promoting health. Standardized validation indices (i.e., accuracy, bias, and precision) compare performance of step counting wearable technologies in young people. PURPOSE To produce a catalog of validity indices for step counting wearable technologies assessed during different treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]), wear locations (waist, wrist/arm, thigh, and ankle), and age groups (children, 6-12 years; adolescents, 13-17 years; young adults, 18-20 years). METHODS One hundred seventeen individuals (13.1 ± 4.2 years, 50.4% female) participated in this cross-sectional study and completed 5-min treadmill bouts (0.8 km/h to 8.0 km/h) while wearing eight devices (Waist: Actical, ActiGraph GT3X+, NL-1000, SW-200; Wrist: ActiGraph GT3X+; Arm: SenseWear; Thigh: activPAL; Ankle: StepWatch). Directly observed steps served as the criterion measure. Accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV) were computed. RESULTS Five of the eight tested wearable technologies (i.e., Actical, waist-worn ActiGraph GT3X+, activPAL, StepWatch, and SW-200) performed at < 5% MAPE over the range of normal speeds. More generally, waist (MAPE = 4%), thigh (4%) and ankle (5%) locations displayed higher accuracy than the wrist location (23%) at normal speeds. On average, all wearable technologies displayed the lowest accuracy across slow speeds (MAPE = 50.1 ± 35.5%), and the highest accuracy across normal speeds (MAPE = 15.9 ± 21.7%). Speed and wear location had a significant effect on accuracy and bias (P < 0.001), but not on precision (P > 0.05). Age did not have any effect (P > 0.05). CONCLUSIONS Standardized validation indices focused on accuracy, bias, and precision were cataloged by speed, wear location, and age group to serve as important reference points when selecting and/or evaluating device performance in young people moving forward. Reduced performance can be expected at very slow walking speeds (0.8 to 3.2 km/h) for all devices. Ankle-worn and thigh-worn devices demonstrated the highest accuracy. Speed and wear location had a significant effect on accuracy and bias, but not precision. TRIAL REGISTRATION Clinicaltrials.gov NCT01989104 . Registered November 14, 2013.
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Affiliation(s)
- Zachary R. Gould
- grid.266683.f0000 0001 2184 9220Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA USA
| | - Jose Mora-Gonzalez
- grid.266859.60000 0000 8598 2218College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223 USA
| | - Elroy J. Aguiar
- grid.411015.00000 0001 0727 7545Department of Kinesiology, The University of Alabama, Tuscaloosa, AL USA
| | - John M. Schuna
- grid.4391.f0000 0001 2112 1969School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR USA
| | - Tiago V. Barreira
- grid.264484.80000 0001 2189 1568Exercise Science Department, Syracuse University, Syracuse, NY USA
| | - Christopher C. Moore
- grid.10698.360000000122483208Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - John Staudenmayer
- grid.266683.f0000 0001 2184 9220Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA USA
| | - Catrine Tudor-Locke
- grid.266859.60000 0000 8598 2218College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223 USA
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Ehrlich SF, Maples JM, Barroso CS, Brown KC, Bassett DR, Zite NB, Fortner KB. Using a consumer-based wearable activity tracker for physical activity goal setting and measuring steps in pregnant women with gestational diabetes mellitus: exploring acceptance and validity. BMC Pregnancy Childbirth 2021; 21:420. [PMID: 34103002 PMCID: PMC8188700 DOI: 10.1186/s12884-021-03900-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 05/19/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Activity monitoring devices may be used to facilitate goal-setting, self-monitoring, and feedback towards a step-based physical activity (PA) goal. This study examined the performance of the wrist-worn Fitbit Charge 3™ (FC3) and sought opinions on walking and stepping-in-place from women with gestational diabetes (GDM). METHODS Participants completed six 2-min metronome-assisted over ground bouts that varied by cadence (67, 84, or 100 steps per minute) and mode (walking or stepping-in-place; N = 15), with the sequence randomized. Steps were estimated by FC3 and measured, in duplicate, by direct observation (hand-tally device, criterion). Equivalence testing by the two one-sided tests (TOST) method assessed agreement within ± 15%. Mean absolute percent error (MAPE) of steps were compared to 10%, the accuracy standard of the Consumer Technology Association (CTA)™. A subset (n = 10) completed a timed, 200-m self-paced walk to assess natural walking pace and cadence. All participants completed semi-structured interviews, which were transcribed and analyzed using descriptive and interpretive coding. RESULTS Mean age was 27.0 years (SD 4.2), prepregnancy BMI 29.4 kg/m2 (8.3), and gestational age 32.8 weeks (SD 2.6). The FC3 was equivalent to hand-tally for bouts of metronome-assisted walking and stepping-in-place at 84 and 100 steps per minute (i.e., P < .05), although walking at 100 steps per minute (P = .01) was no longer equivalent upon adjustment for multiple comparisons (i.e., at P < .007). The FC3 was equivalent to hand-tally during the 200-m walk (i.e., P < .001), in which mean pace was 68.2 m per minute (SD 10.7), or 2.5 miles per hour, and mean cadence 108.5 steps per minute (SD 6.5). For walking at 84 and 100 steps per minute, stepping-in-place at 100 steps per minute, and the 200-m walk, MAPE was within 10%, the accuracy standard of the CTA™. Interviews revealed motivation for PA, that stepping-in-place was an acceptable alternative to walking, and competing responsibilities made it difficult to find time for PA. CONCLUSIONS The FC3 appears to be a valid step counter during the third trimester, particularly when walking or stepping-in-place at or close to women's preferred cadence.
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Affiliation(s)
- Samantha F Ehrlich
- Department of Public Health, The University of Tennessee, Knoxville, 390 HPER, 1914 Andy Holt Ave, Knoxville, TN, 37996, USA.
| | - Jill M Maples
- The University of Tennessee, Graduate School of Medicine, 1924 Alcoa Highway, Knoxville, TN, 37920, USA
| | - Cristina S Barroso
- College of Nursing, The University of Tennessee, Knoxville, 1200 Volunteer Blvd, Knoxville, TN, 37996, USA
| | - Kathleen C Brown
- Department of Public Health, The University of Tennessee, Knoxville, 390 HPER, 1914 Andy Holt Ave, Knoxville, TN, 37996, USA
| | - David R Bassett
- Department of Kinesiology, Recreation, and Sport Studies, The University of Tennessee, Knoxville, 1914 Andy Holt Ave, Knoxville, TN, 37996, USA
| | - Nikki B Zite
- The University of Tennessee, Graduate School of Medicine, 1924 Alcoa Highway, Knoxville, TN, 37920, USA
| | - Kimberly B Fortner
- The University of Tennessee, Graduate School of Medicine, 1924 Alcoa Highway, Knoxville, TN, 37920, USA
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Claudel SE, Tamura K, Troendle J, Andrews MR, Ceasar JN, Mitchell VM, Vijayakumar N, Powell-Wiley TM. Comparing Methods to Identify Wear-Time Intervals for Physical Activity With the Fitbit Charge 2. J Aging Phys Act 2021; 29:529-535. [PMID: 33326935 PMCID: PMC8493649 DOI: 10.1123/japa.2020-0059] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 07/22/2020] [Accepted: 08/26/2020] [Indexed: 01/28/2023]
Abstract
There is no established method for processing data from commercially available physical activity trackers. This study aims to develop a standardized approach to defining valid wear time for use in future interventions and analyses. Sixteen African American women (mean age = 62.1 years and mean body mass index = 35.5 kg/m2) wore the Fitbit Charge 2 for 20 days. Method 1 defined a valid day as ≥10-hr wear time with heart rate data. Method 2 removed minutes without heart rate data, minutes with heart rate ≤ mean - 2 SDs below mean and ≤2 steps, and nighttime. Linear regression modeled steps per day per week change. Using Method 1 (n = 292 person-days), participants had 20.5 (SD = 4.3) hr wear time per day compared with 16.3 (SD = 2.2) hr using Method 2 (n = 282) (p < .0001). With Method 1, participants took 7,436 (SD = 3,543) steps per day compared with 7,298 (SD = 3,501) steps per day with Method 2 (p = .64). The proposed algorithm represents a novel approach to standardizing data generated by physical activity trackers. Future studies are needed to improve the accuracy of physical activity data sets.
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Bai Y, Tompkins C, Gell N, Dione D, Zhang T, Byun W. Comprehensive comparison of Apple Watch and Fitbit monitors in a free-living setting. PLoS One 2021; 16:e0251975. [PMID: 34038458 PMCID: PMC8153432 DOI: 10.1371/journal.pone.0251975] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 05/07/2021] [Indexed: 02/06/2023] Open
Abstract
Objectives The aim of this study was to evaluate the accuracy of three consumer-based activity monitors, Fitbit Charge 2, Fitbit Alta, and the Apple Watch 2, all worn on the wrist, in estimating step counts, moderate-to-vigorous minutes (MVPA), and heart rate in a free-living setting. Methods Forty-eight participants (31 females, 17 males; ages 18–59) were asked to wear the three consumer-based monitors mentioned above on the wrist, concurrently with a Yamax pedometer as the criterion for step count, an ActiGraph GT3X+ (ActiGraph) for MVPA, and a Polar H7 chest strap for heart rate. Participants wore the monitors for a 24-hour free-living condition without changing their usual active routine. MVPA was calculated in bouts of ≥10 minutes. Pearson correlation, mean absolute percent error (MAPE), and equivalence testing were used to evaluate the measurement agreement. Results The average step counts recorded for each device were as follows: 11,734 (Charge2), 11,922 (Alta), 11,550 (Apple2), and 10,906 (Yamax). The correlations in steps for the above monitors ranged from 0.84 to 0.95 and MAPE ranged from 17.1% to 35.5%. For MVPA minutes, the average were 76.3 (Charge2), 63.3 (Alta), 49.5 (Apple2), and 47.8 (ActiGraph) minutes accumulated in bouts of 10 or greater minutes. The correlation from MVPA estimation for above monitors were 0.77, 0.91, and 0.66. MAPE from MVPA estimation ranged from 44.7% to 55.4% compared to ActiGraph. For heart rate, correlation for Charge2 and Apple2 was higher for sedentary behavior and lower for MVPA. The MAPE ranged from 4% to 16%. Conclusion All three consumer monitors estimated step counts fairly accurately, and both the Charge2 and Apple2 reported reasonable heart rate estimation. However, all monitors substantially underestimated MVPA in free-living settings.
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Affiliation(s)
- Yang Bai
- Department of Health, Kinesiology, and Recreation, University of Utah, Salt Lake City, UT, United States of America
- Department of Rehabilitation and Movement Science, University of Vermont, Burlington, VT, United States of America
- * E-mail:
| | - Connie Tompkins
- Department of Rehabilitation and Movement Science, University of Vermont, Burlington, VT, United States of America
| | - Nancy Gell
- Department of Rehabilitation and Movement Science, University of Vermont, Burlington, VT, United States of America
| | - Dakota Dione
- Department of Physical Therapy, Arcadia University, Glenside, PA, United States of America
| | - Tao Zhang
- Department of Kinesiology, Health Promotion, and Recreation, University of North Texas, Denton, Texas, United States of America
| | - Wonwoo Byun
- Department of Health, Kinesiology, and Recreation, University of Utah, Salt Lake City, UT, United States of America
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Wing D, Godino JG, Vo A, Moran R, Graham S, Nichols JF. Quantification of Scan Analysis Errors in GE Lunar DXA Visceral Adiposity in Adults. J Clin Densitom 2021; 24:287-293. [PMID: 32709552 DOI: 10.1016/j.jocd.2020.06.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 06/18/2020] [Accepted: 06/19/2020] [Indexed: 11/25/2022]
Abstract
Utilization of dual-energy X-ray absorptiometry is increasing in clinical settings and the fitness industry as a viable tool to assess total and regional body composition, including visceral adiposity. Previous research using small samples (<50) has described several pitfalls in patient positioning, scan acquisition, and/or analysis that alter regional body composition values. Our aim was to quantify the largest probable error in measures of total, android, gynoid, and visceral fat caused by incorrect placement of the head cut-line, in a large sample of adults. Total body images (N = 436) from 196 women and 67 men (20-85 years) scanned on a GE Lunar Prodigy densitometer were analyzed using enCORE software in 2 ways: (1) placing the head cut-line just beneath the bony protuberance of the chin according to manufacturer recommendation (correct method); (2) placing the head cut-line at the lowest point below the chin and just above the soft tissue at the shoulders (incorrect method). All other cut-lines were fixed. Mean differences in adiposity were examined using Lin's concordance correlation coefficient; equality of means and variances were evaluated using Bradley-Blackwood F-tests. The limits of agreement were displayed as Bland-Altman plots and calculated as the mean difference ±1.96 times the standard deviation of the difference. Correlation coefficients for paired comparisons of adiposity for correct vs incorrect cut-line placement ranged from 0.983-0.999 for all variables (all p < 0.001). Significant mean differences were 172 ± 130, 201 ± 168, 65 ± 122, and -143 ± 336 g for android, gynoid, visceral, and total fat mass, respectively (all p < 0.0001). These differences exceeded our site's least significant change in 66%, 37%, 29%, and 4% of participant scans for android, gynoid, visceral, and total fat mass, respectively. Our findings underscore the importance of careful review of the manufacturer's auto analysis and consistency in conducting serial scans to ensure accurate and precise measures of regional body fat.
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Affiliation(s)
- David Wing
- Exercise and Physical Activity Resource Center (EPARC), Department of Family Medicine and Public Health, University of California, San Diego (UCSD), La Jolla, CA, USA; UCSD Bone Densitometry School, La Jolla, CA, USA
| | - Job G Godino
- Exercise and Physical Activity Resource Center (EPARC), Department of Family Medicine and Public Health, University of California, San Diego (UCSD), La Jolla, CA, USA
| | - Anh Vo
- Exercise and Physical Activity Resource Center (EPARC), Department of Family Medicine and Public Health, University of California, San Diego (UCSD), La Jolla, CA, USA
| | - Ryan Moran
- Exercise and Physical Activity Resource Center (EPARC), Department of Family Medicine and Public Health, University of California, San Diego (UCSD), La Jolla, CA, USA; UCSD Bone Densitometry School, La Jolla, CA, USA
| | - Sarah Graham
- Exercise and Physical Activity Resource Center (EPARC), Department of Family Medicine and Public Health, University of California, San Diego (UCSD), La Jolla, CA, USA; Department of Psychiatry, UCSD, La Jolla, CA, USA; Sam and Rose Stein Institute for Research on Aging, UCSD, La Jolla, CA, USA
| | - Jeanne F Nichols
- Exercise and Physical Activity Resource Center (EPARC), Department of Family Medicine and Public Health, University of California, San Diego (UCSD), La Jolla, CA, USA; UCSD Bone Densitometry School, La Jolla, CA, USA.
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Congruence and trajectories of device-measured and self-reported physical activity during therapy for early breast cancer. Breast Cancer Res Treat 2021; 188:351-359. [PMID: 33788134 PMCID: PMC8260526 DOI: 10.1007/s10549-021-06195-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 03/13/2021] [Indexed: 11/12/2022]
Abstract
Purpose This study examines congruence between self-reported and device-measured physical activity data in women with early breast cancer and compares trajectories under different treatments. Methods Women with non-metastatic breast cancer were recruited before primary therapy. In four weeks distributed over six months after treatment start, patients reported time spent on work, transport, chores and sports via diary and wore Garmin® vivofit 3 accelerometers to assess steps taken. Associations between these measures and agreement regarding guideline adherence were tested with Spearman’s Correlation Coefficient and Weighted Kappa statistic. Effects of time and treatment were evaluated using mixed analyses of variance. Results Ninety-nine participants (median age = 50) were treated with adjuvant (N= 23), neoadjuvant (N= 21) or without chemotherapy (N= 55). Coherence between self-report and device data was strong (r = 0.566). Agreement about reaching recommendations was only “fair” (kappa coefficient = 0.321 and 0.249, resp.). Neither treatment or week nor their interaction had effects on step counts (all p > 0.05). Self-reported activity time was lower for patients with chemotherapy than for those without (adjuvant: ∆ = 69min, p= 0.006, neoadjuvant: ∆ = 45min, p= 0.038) and lower in week 18 than in week 3 (∆ = 43min, p= 0.010). Conclusion Results show that consumer-grade activity monitors and self-reports correlate but show different perspectives on physical activity in breast cancer patients. In general, patients perceive some decline regardless of primary treatment regimen. Those affected should be offered assistance to gain the benefits of activity. Accelerometers may help professionals to identify these individuals and patients to verify appraisal of their activity levels. Supplementary Information The online version contains supplementary material available at 10.1007/s10549-021-06195-7.
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Optimization and Validation of a Classification Algorithm for Assessment of Physical Activity in Hospitalized Patients. SENSORS 2021; 21:s21051652. [PMID: 33673447 PMCID: PMC7956397 DOI: 10.3390/s21051652] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 02/19/2021] [Accepted: 02/22/2021] [Indexed: 11/17/2022]
Abstract
Low amounts of physical activity (PA) and prolonged periods of sedentary activity are common in hospitalized patients. Objective PA monitoring is needed to prevent the negative effects of inactivity, but a suitable algorithm is lacking. The aim of this study is to optimize and validate a classification algorithm that discriminates between sedentary, standing, and dynamic activities, and records postural transitions in hospitalized patients under free-living conditions. Optimization and validation in comparison to video analysis were performed in orthopedic and acutely hospitalized elderly patients with an accelerometer worn on the upper leg. Data segmentation window size (WS), amount of PA threshold (PA Th) and sensor orientation threshold (SO Th) were optimized in 25 patients, validation was performed in another 25. Sensitivity, specificity, accuracy, and (absolute) percentage error were used to assess the algorithm’s performance. Optimization resulted in the best performance with parameter settings: WS 4 s, PA Th 4.3 counts per second, SO Th 0.8 g. Validation showed that all activities were classified within acceptable limits (>80% sensitivity, specificity and accuracy, ±10% error), except for the classification of standing activity. As patients need to increase their PA and interrupt sedentary behavior, the algorithm is suitable for classifying PA in hospitalized patients.
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Kwon S, Wan N, Burns RD, Brusseau TA, Kim Y, Kumar S, Ertin E, Wetter DW, Lam CY, Wen M, Byun W. The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings. SENSORS 2021; 21:s21041411. [PMID: 33670507 PMCID: PMC7922785 DOI: 10.3390/s21041411] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 02/05/2021] [Accepted: 02/10/2021] [Indexed: 12/12/2022]
Abstract
MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland–Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes.
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Affiliation(s)
- Sunku Kwon
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (R.D.B.); (T.A.B.)
| | - Neng Wan
- Department of Geography, University of Utah, Salt Lake City, UT 84112, USA;
| | - Ryan D. Burns
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (R.D.B.); (T.A.B.)
| | - Timothy A. Brusseau
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (R.D.B.); (T.A.B.)
| | - Youngwon Kim
- School of Public Health, The University of Hong Kong Li Ka Shing Faculty of Medicine, Hong Kong;
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge CB2 0SL, UK
| | - Santosh Kumar
- Department of Computer Science, University of Memphis, Memphis, TN 38152, USA;
| | - Emre Ertin
- Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA;
| | - David W. Wetter
- Department of Population Health Sciences and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84132, USA; (D.W.W.); (C.Y.L.)
| | - Cho Y. Lam
- Department of Population Health Sciences and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84132, USA; (D.W.W.); (C.Y.L.)
| | - Ming Wen
- Department of Sociology, University of Utah, Salt Lake City, UT 84112, USA;
| | - Wonwoo Byun
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA; (S.K.); (R.D.B.); (T.A.B.)
- Correspondence: ; Tel.: +1-801-585-1119
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Sjöberg V, Westergren J, Monnier A, Lo Martire R, Hagströmer M, Äng BO, Vixner L. Wrist-Worn Activity Trackers in Laboratory and Free-Living Settings for Patients With Chronic Pain: Criterion Validity Study. JMIR Mhealth Uhealth 2021; 9:e24806. [PMID: 33433391 PMCID: PMC7838001 DOI: 10.2196/24806] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 12/06/2020] [Accepted: 12/12/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Physical activity is evidently a crucial part of the rehabilitation process for patients with chronic pain. Modern wrist-worn activity tracking devices seemingly have a great potential to provide objective feedback and assist in the adoption of healthy physical activity behavior by supplying data of energy expenditure expressed as metabolic equivalent of task units (MET). However, no studies of any wrist-worn activity tracking devices' have examined criterion validity in estimating energy expenditure, heart rate, or step count in patients with chronic pain. OBJECTIVE The aim was to determine the criterion validity of wrist-worn activity tracking devices for estimations of energy expenditure, heart rate, and step count in a controlled laboratory setting and free-living settings for patients with chronic pain. METHODS In this combined laboratory and field validation study, energy expenditure, heart rate, and step count were simultaneously estimated by a wrist-worn activity tracker (Fitbit Versa), indirect calorimetry (Jaeger Oxycon Pro), and a research-grade hip-worn accelerometer (ActiGraph GT3X) during treadmill walking at 3 speeds (3.0 km/h, 4.5 km/h, and 6.0 km/h) in the laboratory setting. Energy expenditure and step count were also estimated by the wrist-worn activity tracker in free-living settings for 72 hours. The criterion validity of each measure was determined using intraclass and Spearman correlation, Bland-Altman plots, and mean absolute percentage error. An analysis of variance was used to determine whether there were any significant systematic differences between estimations. RESULTS A total of 42 patients (age: 25-66 years; male: 10/42, 24%; female: 32/42, 76%), living with chronic pain (duration, in years: mean 9, SD 6.72) were included. At baseline, their mean pain intensity was 3.5 (SD 1.1) out of 6 (Multidimensional Pain Inventory, Swedish version). Results showed that the wrist-worn activity tracking device (Fitbit Versa) systematically overestimated energy expenditure when compared to the criterion standard (Jaeger Oxycon Pro) and the relative criterion standard (ActiGraph GT3X). Poor agreement and poor correlation were shown between Fitbit Versa and both Jaeger Oxycon Pro and ActiGraph GT3X for estimated energy expenditure at all treadmill speeds. Estimations of heart rate demonstrated poor to fair agreement during laboratory-based treadmill walks. For step count, the wrist-worn devices showed fair agreement and fair correlation at most treadmill speeds. In free-living settings; however, the agreement for step count between the wrist-worn device and waist-worn accelerometer was good, and the correlation was excellent. CONCLUSIONS The wrist-worn device systematically overestimated energy expenditure and showed poor agreement and correlation compared to the criterion standard (Jaeger Oxycon Pro) and the relative criterion standard (ActiGraph GT3X), which needs to be considered when used clinically. Step count measured with a wrist-worn device, however, seemed to be a valid estimation, suggesting that future guidelines could include such variables in this group with chronic pain.
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Affiliation(s)
- Veronica Sjöberg
- School of Education, Health and Social Studies, Dalarna University, Falun, Sweden
| | - Jens Westergren
- School of Education, Health and Social Studies, Dalarna University, Falun, Sweden
| | - Andreas Monnier
- School of Education, Health and Social Studies, Dalarna University, Falun, Sweden.,Military Academy Karlberg, Swedish Armed Forces, Solna, Sweden.,Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet, Huddinge, Sweden
| | - Riccardo Lo Martire
- Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet, Huddinge, Sweden
| | - Maria Hagströmer
- Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet, Huddinge, Sweden.,Academic Primary Health Care Centre, Region Stockholm, Stockholm, Sweden
| | - Björn Olov Äng
- School of Education, Health and Social Studies, Dalarna University, Falun, Sweden.,Department of Neurobiology, Care Sciences and Society, Division of Physiotherapy, Karolinska Institutet, Huddinge, Sweden.,Center for Clinical Research Dalarna, Uppsala University, Region Dalarna, Falun, Sweden
| | - Linda Vixner
- School of Education, Health and Social Studies, Dalarna University, Falun, Sweden
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Hao Y, Ma XK, Zhu Z, Cao ZB. Validity of Wrist-Wearable Activity Devices for Estimating Physical Activity in Adolescents: Comparative Study. JMIR Mhealth Uhealth 2021; 9:e18320. [PMID: 33410757 PMCID: PMC7819784 DOI: 10.2196/18320] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 10/20/2020] [Accepted: 12/02/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND The rapid advancements in science and technology of wrist-wearable activity devices offer considerable potential for clinical applications. Self-monitoring of physical activity (PA) with activity devices is helpful to improve the PA levels of adolescents. However, knowing the accuracy of activity devices in adolescents is necessary to identify current levels of PA and assess the effectiveness of intervention programs designed to increase PA. OBJECTIVE The study aimed to determine the validity of the 11 commercially available wrist-wearable activity devices for monitoring total steps and total 24-hour total energy expenditure (TEE) in healthy adolescents under simulated free-living conditions. METHODS Nineteen (10 male and 9 female) participants aged 14 to 18 years performed a 24-hour activity cycle in a metabolic chamber. Each participant simultaneously wore 11 commercial wrist-wearable activity devices (Mi Band 2 [XiaoMi], B2 [Huawei], Bong 2s [Meizu], Amazfit [Huamei], Flex [Fitbit], UP3 [Jawbone], Shine 2 [Misfit], GOLiFE Care-X [GoYourLife], Pulse O2 [Withings], Vivofit [Garmin], and Loop [Polar Electro]) and one research-based triaxial accelerometer (GT3X+ [ActiGraph]). Criterion measures were total EE from the metabolic chamber (mcTEE) and total steps from the GT3X+ (AGsteps). RESULTS Pearson correlation coefficients r for 24-hour TEE ranged from .78 (Shine 2, Amazfit) to .96 (Loop) and for steps ranged from 0.20 (GOLiFE) to 0.57 (Vivofit). Mean absolute percent error (MAPE) for TEE ranged from 5.7% (Mi Band 2) to 26.4% (Amazfit) and for steps ranged from 14.2% (Bong 2s) to 27.6% (Loop). TEE estimates from the Mi Band 2, UP3, Vivofit, and Bong 2s were equivalent to mcTEE. Total steps from the Bong 2s were equivalent to AGsteps. CONCLUSIONS Overall, the Bong 2s had the best accuracy for estimating TEE and total steps under simulated free-living conditions. Further research is needed to examine the validity of these devices in different types of physical activities under real-world conditions.
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Affiliation(s)
- Yingying Hao
- School of Kinesiology, Shanghai University of Sport, Shanghai, China
| | - Xiao-Kai Ma
- School of Kinesiology, Shanghai University of Sport, Shanghai, China
| | - Zheng Zhu
- School of Kinesiology, Shanghai University of Sport, Shanghai, China
| | - Zhen-Bo Cao
- School of Kinesiology, Shanghai University of Sport, Shanghai, China
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48
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Courtney JB, Nuss K, Lyden K, Harrall KK, Glueck DH, Villalobos A, Hamman RF, Hebert JR, Hurley TG, Leiferman J, Li K, Alaimo K, Litt JS. Comparing the activPAL software's Primary Time in Bed Algorithm against Self-Report and van der Berg's Algorithm. MEASUREMENT IN PHYSICAL EDUCATION AND EXERCISE SCIENCE 2020; 25:212-226. [PMID: 34326627 PMCID: PMC8315620 DOI: 10.1080/1091367x.2020.1867146] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The purpose of this study was to compare activPAL algorithm-estimated values for time in bed (TIB), wake time (WT) and bedtime (BT) against self-report and an algorithm developed by van der Berg and colleagues. Secondary analyses of baseline data from the Community Activity for Prevention Study (CAPS) were used in which adults ≥ 18 years wore the activPAL for seven days. Mixed-effects models compared differences between TIB, WT, and BT for all three methods. Bland-Altman plots examined agreement and the two-one-sided test examined equivalence. activPAL was not equivalent to self-report or van der Berg in estimating TIB, but was equivalent to self-report for estimating BT, and was equivalent to van der Berg for estimating WT. The activPAL algorithm requires adjustments before researchers can use it to estimate TIB. However, researchers can use activPAL's option to manually enter self-reported BT and WT to estimate TIB and better understand 24-hour movement patterns.
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Affiliation(s)
- J B Courtney
- Colorado State University, Fort Collins, Colorado
| | - K Nuss
- Colorado State University, Fort Collins, Colorado
| | - K Lyden
- University of Massachusetts, Amherst, Massachusetts
| | - K K Harrall
- University of Colorado School of Medicine, Aurora, Colorado
| | - D H Glueck
- University of Colorado School of Medicine, Aurora, Colorado
| | - A Villalobos
- Colorado School of Public Health, Aurora, Colorado
| | - R F Hamman
- Colorado School of Public Health, Aurora, Colorado
| | - J R Hebert
- University of South Carolina, Columbia, South Carolina
| | - T G Hurley
- University of South Carolina, Columbia, South Carolina
| | - J Leiferman
- Colorado School of Public Health, Aurora, Colorado
| | - K Li
- Colorado State University, Fort Collins, Colorado
| | - K Alaimo
- Michigan State University, East Lansing, Michigan
| | - J S Litt
- University of Colorado Boulder, Boulder, Colorado
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Validation of Garmin Fenix 3 HR Fitness Tracker Biomechanics and Metabolics (VO2max). ACTA ACUST UNITED AC 2020. [DOI: 10.1123/jmpb.2019-0066] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The purpose of this study was to determine the validity of the Garmin fēnix® 3 HR fitness tracker. Methods: A total of 34 healthy recreational runners participated in biomechanical or metabolic testing. Biomechanics participants completed three running conditions (flat, incline, and decline) at a self-selected running pace, on an instrumented treadmill while running biomechanics were tracked using a motion capture system. Variables extracted were compared with data collected by the Garmin fēnix 3 HR (worn on the wrist) that was paired with a chest heart rate monitor and a Garmin Foot Pod (worn on the shoe). Metabolic testing involved two separate tests; a graded exercise test to exhaustion utilizing a metabolic cart and treadmill, and a 15-min submaximal outdoor track session while wearing the Garmin. 2 × 3 analysis of variances with post hoc t tests, mean absolute percentage errors, Pearson’s correlation (R), and a t test were used to determine validity. Results: The fēnix kinematics had a mean absolute percentage errors of 9.44%, 0.21%, 26.38%, and 5.77% for stride length, run cadence, vertical oscillation, and ground contact time, respectively. The fēnix overestimated (p < .05) VO2max with a mean absolute percentage error of 8.05% and an R value of .917. Conclusion: The Garmin fēnix 3 HR appears to produce a valid measure of run cadence and ground contact time during running, while it overestimated vertical oscillation in every condition (p < .05) and should be used with caution when determining stride length. The fēnix appears to produce a valid VO2max estimate and may be used when more accurate methods are not available.
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Validity and Reliability of Physiological Data in Applied Settings Measured by Wearable Technology: A Rapid Systematic Review. TECHNOLOGIES 2020. [DOI: 10.3390/technologies8040070] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The purpose of this review was to evaluate the current state of the literature and to identify the types of study designs, wearable devices, statistical tests, and exercise modes used in validation and reliability studies conducted in applied settings/outdoor environments. This was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We identified nine articles that fit our inclusion criteria, eight of which tested for validity and one tested for reliability. The studies tested 28 different devices with exercise modalities of running, walking, cycling, and hiking. While there were no universally common analytical techniques used to measure accuracy or validity, correlative measures were used in 88% of studies, mean absolute percentage error (MAPE) in 75%, and Bland–Altman plots in 63%. Intra-class correlation was used to determine reliability. There were not any universally common thresholds to determine validity, however, of the studies that used MAPE and correlation, there were only five devices that had a MAPE of < 10% and a correlation value of > 0.7. Overall, the current review establishes the need for greater testing in applied settings when validating wearables. Researchers should seek to incorporate multiple intensities, populations, and modalities into their study designs while utilizing appropriate analytical techniques to measure and determine validity and reliability.
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