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Izmailova ES, Wagner JA, Bakker JP, Kilian R, Ellis R, Ohri N. A proposed multi-domain, digital model for capturing functional status and health-related quality of life in oncology. Clin Transl Sci 2024; 17:e13712. [PMID: 38266055 PMCID: PMC10774540 DOI: 10.1111/cts.13712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 11/22/2023] [Accepted: 12/07/2023] [Indexed: 01/26/2024] Open
Abstract
Whereas traditional oncology clinical trial endpoints remain key for assessing novel treatments, capturing patients' functional status is increasingly recognized as an important aspect for supporting clinical decisions and assessing outcomes in clinical trials. Existing functional status assessments suffer from various limitations, some of which may be addressed by adopting digital health technologies (DHTs) as a means of collecting both objective and self-reported outcomes. In this mini-review, we propose a device-agnostic multi-domain model for oncology capturing functional status, which includes physical activity data, vital signs, sleep variables, and measures related to health-related quality of life enabled by connected digital tools. By using DHTs for all aspects of data collection, our proposed model allows for high-resolution measurement of objective data as patients navigate their daily lives outside of the hospital setting. This is complemented by electronic questionnaires administered at intervals appropriate for each instrument. Preliminary testing and practical considerations to address before adoption are also discussed. Finally, we highlight multi-institutional pre-competitive collaborations as a means of successfully transitioning the proposed digitally enabled data collection model from feasibility studies to interventional trials and care management.
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Affiliation(s)
| | | | - Jessie P. Bakker
- Departments of Medicine and Neurology, Brigham and Women's HospitalBostonMassachusettsUSA
- Division of Sleep Medicine, Harvard Medical SchoolBostonMassachusettsUSA
| | - Rachel Kilian
- Koneksa HealthNew YorkNew YorkUSA
- SSI StrategyNew YorkNew YorkUSA
| | | | - Nitin Ohri
- Montefiore Medical Center, Albert Einstein College of MedicineBronxNew YorkUSA
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Mayer S, Kohn B, Fotteler M, Özkan S, Denkinger M. [Functionality and everyday suitability of commercially wristwear products for frail older people - a comparative product testing]. MMW Fortschr Med 2023; 165:3-10. [PMID: 38062322 DOI: 10.1007/s15006-023-3107-5] [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] [Indexed: 12/18/2023]
Abstract
BACKGROUND AND AIM There is a wide range of smartwatches and emergency watches on the market that are specifically designed for older people. The products are freely available, which is why there is an urgent need for information about the reliability and functionality of the products among potential users, but also health professionals and decision-makers. As part of a systematic product comparison test, the functionality and quality of seven smartwatches were investigated. METHOD Four watches for seniors, one watch for adults and two watches for children, but with comparable functionalities, were included in the test. For the test, real-life situations were simulated and, in addition to emergency calls, GPS tracking, fall detection and geofencing, the battery life, call quality, stability/robustness of the products and service/support were evaluated. From the total number of points, a grade was determined based on the German school grading system (1 = very good to 6 = insufficient). RESULTS All smartwatches evaluated were rated at least "3-satisfactory". The two best-rated watches received a score of 1.8. The differences were particularly evident in the emergency call functionality, battery life, precision of the tracking function, and service/support. The call quality, with one exception, and the stability/robustness were consistently rated as "1-very good". Three watches in the test were able to detect falls with variable results. CONCLUSION The functionality and usability of the tested products differed considerably. A focus on a few main functions can even provide added value for older, frail people. Continuous comparative testing of products for this target group with new and updated products is desirable.
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Affiliation(s)
- Sarah Mayer
- Institut für Geriatrische Forschung der Universität Ulm, AGAPLESION Bethesda Klinik Ulm gGmbH, Zollernring 26, 89073, Ulm, Deutschland
| | - Brigitte Kohn
- Geriatrisches Zentrum Ulm, AGAPLESION Bethesda Ulm, Zollernring 26, 89073, Ulm, Deutschland
| | - Marina Fotteler
- Geriatrisches Zentrum Ulm, AGAPLESION Bethesda Ulm, Zollernring 26, 89073, Ulm, Deutschland
| | - Seda Özkan
- Geriatrisches Zentrum Ulm, AGAPLESION Bethesda Ulm, Zollernring 26, 89073, Ulm, Deutschland
| | - Michael Denkinger
- Institut für Geriatrische Forschung der Universität Ulm, AGAPLESION Bethesda Klinik Ulm gGmbH, Zollernring 26, 89073, Ulm, Deutschland.
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Chase CJ, Aguiar EJ, Moore CC, Chipkin SR, Staudenmayer J, Tudor-Locke C, Ducharme SW. Cadence (steps/min) as an indicator of the walk-to-run transition. Hum Mov Sci 2023; 90:103117. [PMID: 37336086 PMCID: PMC10526715 DOI: 10.1016/j.humov.2023.103117] [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: 07/29/2022] [Revised: 02/12/2023] [Accepted: 06/12/2023] [Indexed: 06/21/2023]
Abstract
BACKGROUND Humans naturally transition from walking to running at a point known as the walk-to-run transition (WRT). The WRT commonly occurs at a speed of ∼2.1 m/s (m/s) or a Froude number (dimensionless value considering leg length) of 0.5. Emerging evidence suggests the WRT can also be classified using a cadence of 140 steps/min. An accurate cadence-based WRT metric would aid in classifying wearable technology minute-level step metrics as walking vs. running. PURPOSE To evaluate performance of 1) WRT predictors directly identified from a treadmill-based dataset of sequentially faster bouts, and 2) accepted WRT predictors compiled from previous literature. METHODS Twenty-eight adults (71.4% men; age = 36.6 ± 12.8 years, BMI = 26.2 ± 4.7 kg/m2) completed a series of five-minute treadmill walking bouts increasing in 0.2 m/s increments until they freely chose to run. Optimal WRT values for speed, Froude number, and cadence were identified using receiver operating characteristic (ROC) curve analyses. WRT value performance was evaluated via classification accuracy metrics. RESULTS Overall accuracies (metric, percent) according to WRT predictors from previous literature were: speed (2.1 m/s, 55.0%), Froude number (0.5, 76.8%), and cadence (140 steps/min, 91.1%), and those from the dataset herein were: speed (1.9 and 2.0 m/s, 78.6%), Froude number (0.68, 77.3%), and cadence (134, 139, and 141 steps/min, 92.9%). The three equally accurate cadence values support a heuristic range of cadence-based WRT values in young and middle-aged adults: 135-140 steps/min. SIGNIFICANCE A tight range of cadence values performed better as WRT predictors compared to either previously reported or directly identified speed or Froude number values. These findings have important implications for gait classification, especially considering cadence is a simple metric which can be readily assessed across settings using direct observation or wearable technologies.
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Affiliation(s)
- Colleen J Chase
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA.
| | - Elroy J Aguiar
- Department of Kinesiology, The University of Alabama, Tuscaloosa, AL, USA
| | - Christopher C Moore
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Stuart R Chipkin
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - John Staudenmayer
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA, USA
| | - Catrine Tudor-Locke
- College of Health and Human Services, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Scott W Ducharme
- Department of Kinesiology, California State University, Long Beach, Long Beach, CA, USA
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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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Bate GL, Kirk C, Rehman RZU, Guan Y, Yarnall AJ, Del Din S, Lawson RA. The Role of Wearable Sensors to Monitor Physical Activity and Sleep Patterns in Older Adult Inpatients: A Structured Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:4881. [PMID: 37430796 PMCID: PMC10222486 DOI: 10.3390/s23104881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/05/2023] [Accepted: 05/07/2023] [Indexed: 07/12/2023]
Abstract
Low levels of physical activity (PA) and sleep disruption are commonly seen in older adult inpatients and are associated with poor health outcomes. Wearable sensors allow for objective continuous monitoring; however, there is no consensus as to how wearable sensors should be implemented. This review aimed to provide an overview of the use of wearable sensors in older adult inpatient populations, including models used, body placement and outcome measures. Five databases were searched; 89 articles met inclusion criteria. We found that studies used heterogenous methods, including a variety of sensor models, placement and outcome measures. Most studies reported the use of only one sensor, with either the wrist or thigh being the preferred location in PA studies and the wrist for sleep outcomes. The reported PA measures can be mostly characterised as the frequency and duration of PA (Volume) with fewer measures relating to intensity (rate of magnitude) and pattern of activity (distribution per day/week). Sleep and circadian rhythm measures were reported less frequently with a limited number of studies providing both physical activity and sleep/circadian rhythm outcomes concurrently. This review provides recommendations for future research in older adult inpatient populations. With protocols of best practice, wearable sensors could facilitate the monitoring of inpatient recovery and provide measures to inform participant stratification and establish common objective endpoints across clinical trials.
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Affiliation(s)
- Gemma L. Bate
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (G.L.B.); (C.K.); (R.Z.U.R.); (A.J.Y.); (S.D.D.)
| | - Cameron Kirk
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (G.L.B.); (C.K.); (R.Z.U.R.); (A.J.Y.); (S.D.D.)
| | - Rana Z. U. Rehman
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (G.L.B.); (C.K.); (R.Z.U.R.); (A.J.Y.); (S.D.D.)
| | - Yu Guan
- Department of Computer Science, University of Warwick, Coventry CV4 7EZ, UK;
| | - Alison J. Yarnall
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (G.L.B.); (C.K.); (R.Z.U.R.); (A.J.Y.); (S.D.D.)
- The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK
- National Institute for Health and Care Research (NIHR), Newcastle Biomedical Research Centre (BRC), Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Silvia Del Din
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (G.L.B.); (C.K.); (R.Z.U.R.); (A.J.Y.); (S.D.D.)
- National Institute for Health and Care Research (NIHR), Newcastle Biomedical Research Centre (BRC), Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Rachael A. Lawson
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE4 5PL, UK; (G.L.B.); (C.K.); (R.Z.U.R.); (A.J.Y.); (S.D.D.)
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Popham S, Burq M, Rainaldi EE, Shin S, Dunn J, Kapur R. An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study. JMIR BIOMEDICAL ENGINEERING 2023; 8:e43726. [PMID: 38875664 PMCID: PMC11041455 DOI: 10.2196/43726] [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: 10/21/2022] [Revised: 12/05/2022] [Accepted: 01/19/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Measuring the amount of physical activity and its patterns using wearable sensor technology in real-world settings can provide critical insights into health status. OBJECTIVE This study's aim was to develop and evaluate the analytical validity and transdemographic generalizability of an algorithm that classifies binary ambulatory status (yes or no) on the accelerometer signal from wrist-worn biometric monitoring technology. METHODS Biometric monitoring technology algorithm validation traditionally relies on large numbers of self-reported labels or on periods of high-resolution monitoring with reference devices. We used both methods on data collected from 2 distinct studies for algorithm training and testing, one with precise ground-truth labels from a reference device (n=75) and the second with participant-reported ground-truth labels from a more diverse, larger sample (n=1691); in total, we collected data from 16.7 million 10-second epochs. We trained a neural network on a combined data set and measured performance in multiple held-out testing data sets, overall and in demographically stratified subgroups. RESULTS The algorithm was accurate at classifying ambulatory status in 10-second epochs (area under the curve 0.938; 95% CI 0.921-0.958) and on daily aggregate metrics (daily mean absolute percentage error 18%; 95% CI 15%-20%) without significant performance differences across subgroups. CONCLUSIONS Our algorithm can accurately classify ambulatory status with a wrist-worn device in real-world settings with generalizability across demographic subgroups. The validated algorithm can effectively quantify users' walking activity and help researchers gain insights on users' health status.
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Affiliation(s)
- Sara Popham
- Verily Life Sciences, South San Francisco, CA, United States
| | - Maximilien Burq
- Verily Life Sciences, South San Francisco, CA, United States
| | - Erin E Rainaldi
- Verily Life Sciences, South San Francisco, CA, United States
| | - Sooyoon Shin
- Verily Life Sciences, South San Francisco, CA, United States
| | - Jessilyn Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
- Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, United States
- Duke Clinical Research Institute, Durham, NC, United States
| | - Ritu Kapur
- Verily Life Sciences, South San Francisco, CA, United States
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Mora-Gonzalez J, Gould ZR, Moore CC, Aguiar EJ, Ducharme SW, Schuna JM, Barreira TV, Staudenmayer J, McAvoy CR, Boikova M, Miller TA, Tudor-Locke C. A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study. Int J Behav Nutr Phys Act 2022; 19:117. [PMID: 36076265 PMCID: PMC9461139 DOI: 10.1186/s12966-022-01350-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 08/17/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies. PURPOSE To expand a previously published child/youth catalog of validity indices to include adults (21-40, 41-60 and 61-85 years of age) assessed across a range of treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist). METHODS Two hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015-2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV). RESULTS Over the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045). CONCLUSIONS Standardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy. TRIAL REGISTRATION Clinicaltrials.gov NCT02650258. Registered 24 December 2015.
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Affiliation(s)
- Jose Mora-Gonzalez
- PROFITH "PROmoting FITness and Health Through Physical Activity" Research Group, Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain
- College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA
| | - Zachary R Gould
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Christopher C Moore
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Elroy J Aguiar
- Department of Kinesiology, The University of Alabama, Tuscaloosa, AL, USA
| | - Scott W Ducharme
- Department of Kinesiology, California State University, Long Beach, Long Beach, CA, USA
| | - John M Schuna
- School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR, USA
| | - Tiago V Barreira
- Exercise Science Department, Syracuse University, Syracuse, NY, USA
| | - John Staudenmayer
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA, USA
| | - Cayla R McAvoy
- College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA
| | - Mariya Boikova
- College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA
| | - Taavy A Miller
- College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA
- Hanger Institute for Clinical Research and Education, Austin, TX, USA
| | - Catrine Tudor-Locke
- College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA.
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8
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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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9
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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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10
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Garduno AC, LaCroix AZ, LaMonte MJ, Dunstan DW, Evenson KR, Wang G, Di C, Schumacher BT, Bellettiere J. Associations of Daily Steps and Step Intensity With Incident Diabetes in a Prospective Cohort Study of Older Women: The OPACH Study. Diabetes Care 2022; 45:339-347. [PMID: 35050362 PMCID: PMC8914434 DOI: 10.2337/dc21-1202] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 11/12/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The primary aim was to assess associations between total steps per day and incident diabetes, whereas the secondary aim was to assess whether the intensity and/or cadence of steps is associated with incident diabetes. RESEARCH DESIGN AND METHODS Women without physician-diagnosed diabetes (n = 4,838; mean [SD] age 78.9 [6.7] years) were followed up to 6.9 years; 395 developed diabetes. Hip-worn ActiGraph GT3X+ accelerometers worn for 1 week enabled measures of total, light-intensity, and moderate- to vigorous-intensity (MV-intensity) steps per day. Using Cox proportional hazards analysis we modeled adjusted change in the hazard rate for incident diabetes associated with total, light-intensity, and MV-intensity steps per day. We further estimated the proportion of the steps-diabetes association mediated by BMI. RESULTS On average, participants took 3,729 (SD 2,114) steps/day, of which 1,875 (791) were light-intensity steps and 1,854 ± 1,762 were MV-intensity. More steps per day were associated with a lower hazard rate for incident diabetes. Confounder-adjusted models for a 2,000 steps/day increment yielded hazard ratio (HR) 0.88 (95% CI 0.78-1.00; P = 0.046). After further adjustment for BMI, HR was 0.90 (95% CI 0.80-1.02; P = 0.11). BMI did not significantly mediate the steps-diabetes association (proportion mediated = 17.7% [95% CI -55.0 to 142.0]; P = 0.09]). The relationship between MV-intensity steps per day (HR 0.86 [95% CI 0.74-1.00]; P = 0.04) and incident diabetes was stronger than for light-intensity steps per day (HR 0.97 [95% CI 0.73-1.29]; P = 0.84). CONCLUSIONS These findings suggest that for older adults, more steps per day are associated with lower incident diabetes and MV-intensity steps are most strongly associated with a lower hazard of diabetes. This evidence supports that regular stepping is an important risk factor for type 2 diabetes prevention in older adults.
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Affiliation(s)
- Alexis C. Garduno
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, CA
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA
| | - Andrea Z. LaCroix
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, CA
| | - Michael J. LaMonte
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo-SUNY, Buffalo, NY
| | - David W. Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Kelly R. Evenson
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Guangxing Wang
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Chongzhi Di
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Benjamin T. Schumacher
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, CA
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA
| | - John Bellettiere
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, CA
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11
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Chen X, Li J, Liu Y, Jiang J, Zhao C, Zhao C, Lim EG, Sun X, Wen Z. An Integrated Self-Powered Real-Time Pedometer System with Ultrafast Response and High Accuracy. ACS APPLIED MATERIALS & INTERFACES 2021; 13:61789-61798. [PMID: 34904819 DOI: 10.1021/acsami.1c19734] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
As accurate step counting is a critical indicator for exercise evaluation in daily life, pedometers give a quantitative prediction of steps and analyze the amount of exercise to regulate the exercise plan. However, the merchandized pedometers still suffer from limited battery life and low accuracy. In this work, an integrated self-powered real-time pedometer system has been demonstrated. The highly integrated system contains a porous triboelectric nanogenerator (P-TENG), a data acquisition and processing (DAQP) module, and a mobile phone APP. The P-TENG works as a pressure sensor that generates electrical signals synchronized with users' footsteps, and combining it with the analogue front-end (AFE) circuit yields an ultrafast response time of 8 ms. Moreover, the combination of a mini press-to-spin-type electromagnetic generator (EMG) and a supercapacitor enables a self-powered and self-sustained operation of the entire pedometer system. This work implements the regulation of TENG signals by electronic circuit design and proposes a highly integrated system. The improved reliability and practicality provide more possibilities for wearable self-powered electronic devices.
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Affiliation(s)
- Xiaoping Chen
- Institute of Functional Nano and Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123, China
- Department of Applied Mathematics, School of Science, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Junyan Li
- Department of Applied Mathematics, School of Science, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Yina Liu
- Department of Applied Mathematics, School of Science, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Jinxing Jiang
- Institute of Functional Nano and Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123, China
| | - Chun Zhao
- Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Cezhou Zhao
- Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Eng Gee Lim
- Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China
| | - Xuhui Sun
- Institute of Functional Nano and Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123, China
| | - Zhen Wen
- Institute of Functional Nano and Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123, China
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12
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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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13
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Shimizu K, Sugawara K. Validation of Potential Reference Measure for Indoor Walking Distance to Evaluate Wearable Sensing Devices . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:7178-7181. [PMID: 34892756 DOI: 10.1109/embc46164.2021.9629854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The walking distance estimated from the coordinate position information of the center of mass obtained via Xsens MTw Awinda were validated from 5 adult volunteers and the accuracy was shown significantly high. (Average absolute error of -1.22% with a standard deviation of 2.26%).
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14
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Criterion Validity of iOS and Android Applications to Measure Steps and Distance in Adults. TECHNOLOGIES 2021. [DOI: 10.3390/technologies9030055] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The growing popularity of physical activity (PA) applications (apps) in recent years and the vast amounts of data that they generate present attractive possibilities for surveillance. However, measurement accuracy is indispensable when tracking PA variables to provide meaningful measures of PA. The purpose of this study was to examine the steps and distance criterion validity of freeware accelerometer-based PA smartphone apps, during incremental-intensity treadmill walking and jogging. Thirty healthy adults (25.9 ± 5.7 years) participated in this cross-sectional study. They were fitted with two smartphones (one with Android and one with iOS operating systems), each one simultaneously running four different apps (i.e., Runtastic Pedometer, Accupedo, Pacer, and Argus). They walked and jogged for 5 min at each of the predefined speeds of 4.8, 6.0, and 8.4 km/h on a treadmill, and two researchers counted every step taken during trials with a digital tally counter. Validity was evaluated by comparing each app with the criterion measure using repeated-measures analysis of variance (ANOVA), mean absolute percentage errors (MAPEs), and Bland–Altman plots. For step count, Android apps performed slightly more accurately that iOS apps; nevertheless, MAPEs were generally low for all apps (<5%) and accuracy increased at higher speeds. On the other hand, errors were significantly higher for distance estimation (>10%). The findings suggest that accelerometer-based apps are accurate tools for counting steps during treadmill walking and jogging and could be considered suitable for use as an outcome measure within a clinical trial. However, none of the examined apps was suitable for measuring distance.
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15
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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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16
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McAvoy CR, Moore CC, Aguiar EJ, Ducharme SW, Schuna JM, Barreira TV, Chase CJ, Gould ZR, Amalbert-Birriel MA, Chipkin SR, Staudenmayer J, Tudor-Locke C, Mora-Gonzalez J. Cadence (steps/min) and relative intensity in 21 to 60-year-olds: the CADENCE-adults study. Int J Behav Nutr Phys Act 2021; 18:27. [PMID: 33568188 PMCID: PMC7877025 DOI: 10.1186/s12966-021-01096-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 01/29/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Heuristic cadence (steps/min) thresholds of ≥100 and ≥ 130 steps/min correspond with absolutely-defined moderate (3 metabolic equivalents [METs]; 1 MET = 3.5 mL O2·kg- 1·min- 1) and vigorous (6 METs) intensity, respectively. Scarce evidence informs cadence thresholds for relatively-defined moderate (≥ 64% heart rate maximum [HRmax = 220-age], ≥ 40%HR reserve [HRR = HRmax -HRresting, and ≥ 12 Rating of Perceived Exertion [RPE]); or vigorous intensity (≥ 77%HRmax, ≥ 60%HRR, and ≥ 14 RPE). PURPOSE To identify heuristic cadence thresholds corresponding with relatively-defined moderate and vigorous intensity in 21-60-year-olds. METHODS In this cross-sectional study, 157 adults (40.4 ± 11.5 years; 50.6% men) completed up to twelve 5-min treadmill bouts, beginning at 0.5 mph and increasing by 0.5 mph. Steps were directly observed, HR was measured with chest-worn monitors, and RPE was queried in the final minute of each bout. Segmented mixed model regression and Receiver Operating Characteristic (ROC) curve analyses identified optimal cadence thresholds, stratified by age (21-30, 31-40, 41-50, and 51-60 years). Reconciliation of the two analytical models, including trade-offs between sensitivity, specificity, positive and negative predictive values, and overall accuracy, yielded final heuristic cadences. RESULTS Across all moderate intensity indicators, the segmented regression models estimated optimal cadence thresholds ranging from 123.8-127.5 (ages 21-30), 121.3-126.0 (ages 31-40), 117.7-122.7 (ages 41-50), and 113.3-116.1 steps/min (ages 51-60). Corresponding values for vigorous intensity were 140.3-144.1, 140.2-142.6, 139.3-143.6, and 131.6-132.8 steps/min, respectively. ROC analysis estimated chronologically-arranged age groups' cadence thresholds ranging from 114.5-118, 113.5-114.5, 104.6-112.9, and 103.6-106.0 across all moderate intensity indicators, and 127.5, 121.5, 117.2-123.2, and 113.0 steps/min, respectively, for vigorous intensity. CONCLUSIONS Heuristic cadence thresholds corresponding to relatively-defined moderate intensity for the chronologically-arranged age groups were ≥ 120, 120, 115, and 105 steps/min, regardless of the intensity indicator (i.e., % HRmax, %HRR, or RPE). Corresponding heuristic values for vigorous intensity indicators were ≥ 135, 130, 125, and 120 steps/min. These cadences are useful for predicting/programming intensity aligned with age-associated differences in physiological response to, and perceived experiences of, moderate and/or vigorous intensity. TRIAL REGISTRATION Clinicaltrials.gov NCT02650258 . Registered 24 December 2015.
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Affiliation(s)
- Cayla R McAvoy
- College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA
| | - Christopher C Moore
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Elroy J Aguiar
- Department of Kinesiology, The University of Alabama, Tuscaloosa, AL, USA
| | - Scott W Ducharme
- Department of Kinesiology, California State University, Long Beach, Long Beach, CA, USA
| | - John M Schuna
- School of Biological and Population Health Sciences, Oregon State University, Corvallis, OR, USA
| | - Tiago V Barreira
- Exercise Science Department, Syracuse University, Syracuse, NY, USA
| | - Colleen J Chase
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Zachary R Gould
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA
| | | | - Stuart R Chipkin
- Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA, USA
| | - John Staudenmayer
- Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA, USA
| | - Catrine Tudor-Locke
- College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA.
| | - Jose Mora-Gonzalez
- College of Health and Human Services, University of North Carolina at Charlotte, 9201 University City Blvd, Charlotte, NC, 28223, USA
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17
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Validity of Consumer Activity Monitors and an Algorithm Using Smartphone Data for Measuring Steps during Different Activity Types. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17249314. [PMID: 33322833 PMCID: PMC7764011 DOI: 10.3390/ijerph17249314] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 11/26/2020] [Accepted: 12/09/2020] [Indexed: 12/29/2022]
Abstract
Background: Consumer activity monitors and smartphones have gained relevance for the assessment and promotion of physical activity. The aim of this study was to determine the concurrent validity of various consumer activity monitor models and smartphone models for measuring steps. Methods: Participants completed three activity protocols: (1) overground walking with three different speeds (comfortable, slow, fast), (2) activities of daily living (ADLs) focusing on arm movements, and (3) intermittent walking. Participants wore 11 activity monitors (wrist: 8; hip: 2; ankle: 1) and four smartphones (hip: 3; calf: 1). Observed steps served as the criterion measure. The mean average percentage error (MAPE) was calculated for each device and protocol. Results: Eighteen healthy adults participated in the study (age: 28.8 ± 4.9 years). MAPEs ranged from 0.3–38.2% during overground walking, 48.2–861.2% during ADLs, and 11.2–47.3% during intermittent walking. Wrist-worn activity monitors tended to misclassify arm movements as steps. Smartphone data collected at the hip, analyzed with a separate algorithm, performed either equally or even superiorly to the research-grade ActiGraph. Conclusion: This study highlights the potential of smartphones for physical activity measurement. Measurement inaccuracies during intermittent walking and arm movements should be considered when interpreting study results and choosing activity monitors for evaluation purposes.
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