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Goncalves S, Mandigout S, Le Bourvellec M, Duclos NC. Comparison of motion sensor and heart rate monitor for assessment of physical activity intensity in stroke outpatient rehabilitation sessions: an observational study. J Rehabil Med 2024; 56:jrm40559. [PMID: 38915294 PMCID: PMC11218675 DOI: 10.2340/jrm.v56.40559] [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: 04/13/2024] [Accepted: 06/10/2024] [Indexed: 06/26/2024] Open
Abstract
OBJECTIVE To compare the estimation of time spent on 4 categories of physical activity intensity (sedentary behaviour, light physical activity, moderate physical activity, and vigorous physical activity) between a motion sensor and a heart rate monitor during a stroke outpatient rehabilitation session. DESIGN A multicentre cross-sectional observational study. SUBJECTS/PATIENTS Participants with stroke (> 6 months) undergoing outpatient rehabilitation sessions. METHODS Participants wore the SenseWear Armband motion sensor and the Polar H10 heart rate monitor during 2 rehabilitation sessions. The times estimated by each device were compared using a generalized linear mixed model and post-hoc tests. RESULTS Ninety-nine participants from 29 clinics were recruited and data from 146 sessions were included in the analysis. The estimated times depended on the devices and the physical activity intensity category (F = 135, p < 0.05). The motion sensor estimated more time spent in sedentary behaviour and less time spent in moderate physical activity and vigorous physical activity than the heart rate monitor. CONCLUSION The motion sensor and heart rate monitor provide different estimates of physical activity intensity during stroke rehabilitation. Further research is needed to establish the most appropriate device for each physical activity category.
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Keogh A, Argent R, Doherty C, Duignan C, Fennelly O, Purcell C, Johnston W, Caulfield B. Breaking down the Digital Fortress: The Unseen Challenges in Healthcare Technology-Lessons Learned from 10 Years of Research. SENSORS (BASEL, SWITZERLAND) 2024; 24:3780. [PMID: 38931564 PMCID: PMC11207951 DOI: 10.3390/s24123780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 06/06/2024] [Accepted: 06/08/2024] [Indexed: 06/28/2024]
Abstract
Healthcare is undergoing a fundamental shift in which digital health tools are becoming ubiquitous, with the promise of improved outcomes, reduced costs, and greater efficiency. Healthcare professionals, patients, and the wider public are faced with a paradox of choice regarding technologies across multiple domains. Research is continuing to look for methods and tools to further revolutionise all aspects of health from prediction, diagnosis, treatment, and monitoring. However, despite its promise, the reality of implementing digital health tools in practice, and the scalability of innovations, remains stunted. Digital health is approaching a crossroads where we need to shift our focus away from simply looking at developing new innovations to seriously considering how we overcome the barriers that currently limit its impact. This paper summarises over 10 years of digital health experiences from a group of researchers with backgrounds in physical therapy-in order to highlight and discuss some of these key lessons-in the areas of validity, patient and public involvement, privacy, reimbursement, and interoperability. Practical learnings from this collective experience across patient cohorts are leveraged to propose a list of recommendations to enable researchers to bridge the gap between the development and implementation of digital health tools.
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Affiliation(s)
- Alison Keogh
- Clinical Medicine, School of Medicine, Trinity College Dublin, Tallaght University Hospital, D24 TP66 Dublin, Ireland;
- Insight Centre for Data Analytics, University College Dublin, D04 V1W8 Dublin, Ireland; (R.A.); (C.D.); (O.F.); (C.P.); (W.J.); (B.C.)
| | - Rob Argent
- Insight Centre for Data Analytics, University College Dublin, D04 V1W8 Dublin, Ireland; (R.A.); (C.D.); (O.F.); (C.P.); (W.J.); (B.C.)
- School of Pharmacy and Biomolecular Sciences, RCSI University of Medicine & Health Sciences, D02 YN77 Dublin, Ireland
| | - Cailbhe Doherty
- Insight Centre for Data Analytics, University College Dublin, D04 V1W8 Dublin, Ireland; (R.A.); (C.D.); (O.F.); (C.P.); (W.J.); (B.C.)
- School of Public Health, Physiotherapy and Sports Science, University College Dublin, D04 V1W8 Dublin, Ireland
| | - Ciara Duignan
- Insight Centre for Data Analytics, University College Dublin, D04 V1W8 Dublin, Ireland; (R.A.); (C.D.); (O.F.); (C.P.); (W.J.); (B.C.)
| | - Orna Fennelly
- Insight Centre for Data Analytics, University College Dublin, D04 V1W8 Dublin, Ireland; (R.A.); (C.D.); (O.F.); (C.P.); (W.J.); (B.C.)
| | - Ciaran Purcell
- Insight Centre for Data Analytics, University College Dublin, D04 V1W8 Dublin, Ireland; (R.A.); (C.D.); (O.F.); (C.P.); (W.J.); (B.C.)
- School of Allied Health, University of Limerick, V94 T9PX Limerick, Ireland
| | - William Johnston
- Insight Centre for Data Analytics, University College Dublin, D04 V1W8 Dublin, Ireland; (R.A.); (C.D.); (O.F.); (C.P.); (W.J.); (B.C.)
| | - Brian Caulfield
- Insight Centre for Data Analytics, University College Dublin, D04 V1W8 Dublin, Ireland; (R.A.); (C.D.); (O.F.); (C.P.); (W.J.); (B.C.)
- School of Public Health, Physiotherapy and Sports Science, University College Dublin, D04 V1W8 Dublin, Ireland
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Mather JD, Hayes LD, Mair JL, Sculthorpe NF. Validity of resting heart rate derived from contact-based smartphone photoplethysmography compared with electrocardiography: a scoping review and checklist for optimal acquisition and reporting. Front Digit Health 2024; 6:1326511. [PMID: 38486919 PMCID: PMC10937558 DOI: 10.3389/fdgth.2024.1326511] [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: 10/23/2023] [Accepted: 02/08/2024] [Indexed: 03/17/2024] Open
Abstract
Background With the rise of smartphone ownership and increasing evidence to support the suitability of smartphone usage in healthcare, the light source and smartphone camera could be utilized to perform photoplethysmography (PPG) for the assessment of vital signs, such as heart rate (HR). However, until rigorous validity assessment has been conducted, PPG will have limited use in clinical settings. Objective We aimed to conduct a scoping review assessing the validity of resting heart rate (RHR) acquisition from PPG utilizing contact-based smartphone devices. Our four specific objectives of this scoping review were to (1) conduct a systematic search of the published literature concerning contact-based smartphone device-derived PPG, (2) map study characteristics and methodologies, (3) identify if methodological and technological advancements have been made, and (4) provide recommendations for the advancement of the investigative area. Methods ScienceDirect, PubMed and SPORTDiscus were searched for relevant studies between January 1st, 2007, and November 6th, 2022. Filters were applied to ensure only literature written in English were included. Reference lists of included studies were manually searched for additional eligible studies. Results In total 10 articles were included. Articles varied in terms of methodology including study characteristics, index measurement characteristics, criterion measurement characteristics, and experimental procedure. Additionally, there were variations in reporting details including primary outcome measure and measure of validity. However, all studies reached the same conclusion, with agreement ranging between good to very strong and correlations ranging from r = .98 to 1. Conclusions Smartphone applications measuring RHR derived from contact-based smartphone PPG appear to agree with gold standard electrocardiography (ECG) in healthy subjects. However, agreement was established under highly controlled conditions. Future research could investigate their validity and consider effective approaches that transfer these methods from laboratory conditions into the "real-world", in both healthy and clinical populations.
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Affiliation(s)
- James D. Mather
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, United Kingdom
| | - Lawrence D. Hayes
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, United Kingdom
| | - Jacqueline L. Mair
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Nicholas F. Sculthorpe
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, United Kingdom
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Varma N, Han JK, Passman R, Rosman LA, Ghanbari H, Noseworthy P, Avari Silva JN, Deshmukh A, Sanders P, Hindricks G, Lip G, Sridhar AR. Promises and Perils of Consumer Mobile Technologies in Cardiovascular Care: JACC Scientific Statement. J Am Coll Cardiol 2024; 83:611-631. [PMID: 38296406 DOI: 10.1016/j.jacc.2023.11.024] [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: 11/01/2023] [Accepted: 11/16/2023] [Indexed: 02/08/2024]
Abstract
Direct-to-consumer (D2C) wearables are becoming increasingly popular in cardiovascular health management because of their affordability and capability to capture diverse health data. Wearables may enable continuous health care provider-patient partnerships and reduce the volume of episodic clinic-based care (thereby reducing health care costs). However, challenges arise from the unregulated use of these devices, including questionable data reliability, potential misinterpretation of information, unintended psychological impacts, and an influx of clinically nonactionable data that may overburden the health care system. Further, these technologies could exacerbate, rather than mitigate, health disparities. Experience with wearables in atrial fibrillation underscores these challenges. The prevalent use of D2C wearables necessitates a collaborative approach among stakeholders to ensure effective integration into cardiovascular care. Wearables are heralding innovative disease screening, diagnosis, and management paradigms, expanding therapeutic avenues, and anchoring personalized medicine.
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Affiliation(s)
- Niraj Varma
- Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio, USA.
| | - Janet K Han
- Department of Cardiology, VA Greater Los Angeles Healthcare System, Los Angeles, California, USA; Department of Cardiology, David Geffen School of Medicine at the University of California-Los Angeles, Los Angeles, California, USA
| | - Rod Passman
- Department of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Lindsey Anne Rosman
- Division of Cardiology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Hamid Ghanbari
- Department of Cardiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Peter Noseworthy
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Abhishek Deshmukh
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Prashanthan Sanders
- Department of Cardiology, University of Adelaide, South Australia, Australia
| | | | - Gregory Lip
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University, and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom; Department of Clinical Medicine, Danish Center for Clinical Health Services Research, Aalborg University, Aalborg, Denmark
| | - Arun R Sridhar
- Department of Cardiology, Pulse Heart Institute, Seattle, Washington, USA; Department of Clinical Medicine, Danish Center for Clinical Health Services Research, Aalborg University, Aalborg, Denmark
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Marzano-Felisatti JM, De Lucca L, Guzmán Luján JF, Priego-Quesada JI, Pino-Ortega J. A Preliminary Investigation about the Influence of WIMU PRO TM Location on Heart Rate Accuracy: A Comparative Study in Cycle Ergometer. SENSORS (BASEL, SWITZERLAND) 2024; 24:988. [PMID: 38339705 PMCID: PMC10857324 DOI: 10.3390/s24030988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/25/2024] [Accepted: 02/01/2024] [Indexed: 02/12/2024]
Abstract
Technological development has boosted the use of multi-sensor devices to monitor athletes' performance, but the location and connectivity between devices have been shown to affect data reliability. This preliminary study aimed to determine whether the placement of a multi-sensor device (WIMU PROTM) could affect the heart rate signal reception (GARMINTM chest strap) and, therefore, data accuracy. Thirty-two physical education students (20 men and 12 women) performed 20 min of exercise in a cycle ergometer based on the warm-up of the Function Threshold Power 20 test in laboratory conditions, carrying two WIMU PROTM devices (Back: inter-scapula; Bicycle: bicycle's handlebar-20 cm from the chest) and two GARMINTM chest straps. A one-dimensional statistical parametric mapping test found full agreement between the two situations (inter-scapula vs. bicycle's handlebar). Excellent intra-class correlation values were obtained during the warm-up (ICC = 0.99, [1.00-1.00], p < 0.001), the time trial test (ICC = 0.99, [1.00-1.00], p < 0.001) and the cool-down (ICC = 0.99, [1.00-1.00], p < 0.001). The Bland-Altman plots confirmed the total agreement with a bias value of 0.00 ± 0.1 bpm. The interscapular back placement of the WIMU PROTM device does not affect heart rate measurement accuracy with a GARMINTM chest strap during cycling exercise in laboratory conditions.
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Affiliation(s)
- Joaquín Martín Marzano-Felisatti
- Research Group in Sports Biomechanics (GIBD), Department of Physical Education and Sports, Faculty of Physical Activity and Sport Sciences, Universitat de València, 46010 Valencia, Spain;
| | - Leonardo De Lucca
- Laboratory of Human Performance Research, Centre of Health and Sport Sciences, University of Santa Catarina State, Florianópolis 88040-900, Brazil;
| | - José Francisco Guzmán Luján
- Research Group in Sports Technique and Tactics (GITTE), Department of Physical Education and Sports, Faculty of Physical Activity and Sport Sciences, Universitat de València, 46010 Valencia, Spain
| | - Jose Ignacio Priego-Quesada
- Research Group in Sports Biomechanics (GIBD), Department of Physical Education and Sports, Faculty of Physical Activity and Sport Sciences, Universitat de València, 46010 Valencia, Spain;
| | - José Pino-Ortega
- Biovetmed & Sportsci Research Group, Department of Physical Activity and Sport, Faculty of Sport Sciences, University of Murcia, 30720 San Javier, Spain;
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Ibrahim NS, Rampal S, Lee WL, Pek EW, Suhaimi A. Evaluation of Wrist-Worn Photoplethysmography Trackers with an Electrocardiogram in Patients with Ischemic Heart Disease: A Validation Study. Cardiovasc Eng Technol 2024; 15:12-21. [PMID: 37973701 DOI: 10.1007/s13239-023-00693-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 10/18/2023] [Indexed: 11/19/2023]
Abstract
PURPOSE Photoplethysmography measurement of heart rate with wrist-worn trackers has been introduced in healthy individuals. However, additional consideration is necessary for patients with ischemic heart disease, and the available evidence is limited. The study aims to evaluate the validity and reliability of heart rate measures by a wrist-worn photoplethysmography (PPG) tracker compared to an electrocardiogram (ECG) during incremental treadmill exercise among patients with ischemic heart disease. METHODS Fifty-one participants performed the standard incremental treadmill exercise in a controlled laboratory setting with 12-lead ECG attached to the patient's body and wearing wrist-worn PPG trackers. RESULTS At each stage, the absolute percentage error of the PPG was within 10% of the standard acceptable range. Further analysis using a linear mixed model, which accounts for individual variations, revealed that PPG yielded the best performance at the baseline low-intensity exercise. As the stages progressed, heart rate validity decreased but was regained during recovery. The reliability was moderate to excellent. CONCLUSIONS Low-cost trackers AMAZFIT Cor and Bip validity and reliability were within acceptable ranges, especially during low-intensity exercise among patients with ischemic heart disease recovering from cardiac procedures. Though using the tracker as part of the diagnosis tool still requires more supporting studies, it can potentially be used as a self-monitoring tool with precautions.
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Affiliation(s)
- Nur Syazwani Ibrahim
- Department of Rehabilitation Medicine, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Sanjay Rampal
- Centre for Epidemiology and Evidence-based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
| | - Wan Ling Lee
- Department of Nursing Science, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Eu Way Pek
- Department of Rehabilitation Medicine, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Anwar Suhaimi
- Department of Rehabilitation Medicine, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
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Wang TL, Wu HY, Wang WY, Chen CW, Chien WC, Chu CM, Wu YS. Assessment of Heart Rate Monitoring During Exercise With Smart Wristbands and a Heart Rhythm Patch: Validation and Comparison Study. JMIR Form Res 2023; 7:e52519. [PMID: 38096010 PMCID: PMC10755651 DOI: 10.2196/52519] [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: 09/06/2023] [Revised: 11/10/2023] [Accepted: 11/24/2023] [Indexed: 12/31/2023] Open
Abstract
BACKGROUND The integration of wearable devices into fitness routines, particularly in military settings, necessitates a rigorous assessment of their accuracy. This study evaluates the precision of heart rate measurements by locally manufactured wristbands, increasingly used in military academies, to inform future device selection for military training activities. OBJECTIVE This research aims to assess the reliability of heart rate monitoring in chest straps versus wearable wristbands. METHODS Data on heart rate and acceleration were collected using the Q-Band Q-69 smart wristband (Mobile Action Technology Inc) and compared against the Zephyr Bioharness standard measuring device. The Lin concordance correlation coefficient, Pearson product moment correlation coefficient, and intraclass correlation coefficient were used for reliability analysis. RESULTS Participants from a Northern Taiwanese medical school were enrolled (January 1-June 31, 2021). The Q-Band Q-69 demonstrated that the mean absolute percentage error (MAPE) of women was observed to be 13.35 (SD 13.47). Comparatively, men exhibited a lower MAPE of 8.54 (SD 10.49). The walking state MAPE was 7.79 for women and 10.65 for men. The wristband's accuracy generally remained below 10% MAPE in other activities. Pearson product moment correlation coefficient analysis indicated gender-based performance differences, with overall coefficients of 0.625 for women and 0.808 for men, varying across walking, running, and cooldown phases. CONCLUSIONS This study highlights significant gender and activity-dependent variations in the accuracy of the MobileAction Q-Band Q-69 smart wristband. Reduced accuracy was notably observed during running. Occasional extreme errors point to the necessity of caution in relying on such devices for exercise monitoring. The findings emphasize the limitations and potential inaccuracies of wearable technology, especially in high-intensity physical activities.
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Affiliation(s)
- Tse-Lun Wang
- Division of Trauma and Surgical Critical Care, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung City, Taiwan
| | - Hao-Yi Wu
- Department of Nursing, Tri-Service General Hospital, Taipei City, Taiwan
| | - Wei-Yun Wang
- National Defense Medical Center and Department of Nursing, School of Nursing, Tri-Service General Hospital, Taipei City, Taiwan
| | - Chao-Wen Chen
- Division of Trauma and Surgical Critical Care, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan
- Department of Emergency Medicine, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung City, Taiwan
| | - Wu-Chien Chien
- Department of Medical Research, Tri-Service General Hospital National Defense Medical Center, Taipei City, Taiwan
- School of Public Health, National Defense Medical Center, Taipei, Taiwan
- Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
- Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
| | - Chi-Ming Chu
- School of Public Health, National Defense Medical Center, Taipei, Taiwan
- Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan
- Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
- Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
- Department of Public Health, Kaohsiung Medical University, Kaohsiung City, Taiwan
- Department of Public Health, China Medical University, Taichung City, Taiwan
| | - Yi-Syuan Wu
- Division of Trauma and Surgical Critical Care, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan
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Lindsey B, Hanley C, Reider L, Snyder S, Zhou Y, Bell E, Shim J, Hahn JO, Vignos M, Bar-Kochba E. Accuracy of heart rate measured by military-grade wearable ECG monitor compared with reference and commercial monitors. BMJ Mil Health 2023:e002541. [PMID: 38053265 DOI: 10.1136/military-2023-002541] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 10/27/2023] [Indexed: 12/07/2023]
Abstract
INTRODUCTION Physiological monitoring of soldiers can indicate combat readiness and performance. Despite demonstrated use of wearable devices for HR monitoring, commercial options lack desired military features. A newly developed OMNI monitor includes desired features such as long-range secure data transmission. This study investigated the accuracy of the OMNI to measure HR via accuracy of R-R interval duration relative to research-grade ECG and commercial products. METHODS 54 healthy individuals (male/female=37/17, age=22.2±3.6 years, height=173.0±9.1 cm, weight=70.1±11.2 kg) completed a submaximal exercise test while wearing a reference ECG (Biopac) and a randomly assigned chest-based monitor (OMNI, Polar H10, Equivital EQ-02, Zephyr Bioharness 3). All participants also wore two wrist-based photoplethysmography (PPG) devices, Garmin fēnix 6 and Empatica E4. Bland-Altman analyses of agreement, concordance correlation coefficient (CCC) and root-mean-squared error (RMSE) were used to determine accuracy of the OMNI and commercial devices relative to Biopac. Additionally, a linear mixed-effects model evaluated the effects of device and exercise intensity on agreement. RESULTS Chest-based devices showed superior agreement with Biopac for measuring R-R interval compared with wrist-based ones in terms of mean bias, CCC and RMSE, with OMNI demonstrating the best scores on all metrics. Linear mixed-effects model showed no significant main or interaction effects for the chest-based devices. However, significant effects were found for Garmin and Empatica devices (p<0.001) as well as the interaction effects between both Garmin and Empatica and exercise intensity (p<0.001). CONCLUSIONS Chest-based ECG devices are preferred to wrist-based PPG devices due to superior HR accuracy over a range of exercise intensities, with the OMNI device demonstrating equal, if not superior, performance to other commercial ECG monitors. Additionally, wrist-based PPG devices are significantly affected by exercise intensity as they underestimate HR at low intensities and overestimate HR at high intensities.
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Affiliation(s)
- Bryndan Lindsey
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - C Hanley
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - L Reider
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - S Snyder
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
- University of Maryland, College Park, Maryland, USA
| | - Y Zhou
- University of Maryland, College Park, Maryland, USA
| | - E Bell
- University of Maryland, College Park, Maryland, USA
- Towson University, Towson, Maryland, USA
| | - J Shim
- University of Maryland, College Park, Maryland, USA
- Kyung Hee University, Seoul, The Republic of Korea
| | - J-O Hahn
- University of Maryland, College Park, Maryland, USA
| | - M Vignos
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - E Bar-Kochba
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
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Klier K, Koch L, Graf L, Schinköthe T, Schmidt A. Diagnostic Accuracy of Single-Lead Electrocardiograms Using the Kardia Mobile App and the Apple Watch 4: Validation Study. JMIR Cardio 2023; 7:e50701. [PMID: 37995111 DOI: 10.2196/50701] [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: 07/10/2023] [Revised: 09/06/2023] [Accepted: 09/08/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND To date, the 12-lead electrocardiogram (ECG) is the gold standard for cardiological diagnosis in clinical settings. With the advancements in technology, a growing number of smartphone apps and gadgets for recording, visualizing, and evaluating physical performance as well as health data is available. Although this new smart technology is innovative and time- and cost-efficient, less is known about its diagnostic accuracy and reliability. OBJECTIVE This study aimed to examine the agreement between the mobile single-lead ECG measurements of the Kardia Mobile App and the Apple Watch 4 compared to the 12-lead gold standard ECG in healthy adults under laboratory conditions. Furthermore, it assessed whether the measurement error of the devices increases with an increasing heart rate. METHODS This study was designed as a prospective quasi-experimental 1-sample measurement, in which no randomization of the sampling was carried out. In total, ECGs at rest from 81 participants (average age 24.89, SD 8.58 years; n=58, 72% male) were recorded and statistically analyzed. Bland-Altman plots were created to graphically illustrate measurement differences. To analyze the agreement between the single-lead ECGs and the 12-lead ECG, Pearson correlation coefficient (r) and Lin concordance correlation coefficient (CCCLin) were calculated. RESULTS The results showed a higher agreement for the Apple Watch (mean deviation QT: 6.85%; QT interval corrected for heart rate using Fridericia formula [QTcF]: 7.43%) than Kardia Mobile (mean deviation QT: 9.53%; QTcF: 9.78%) even if both tend to underestimate QT and QTcF intervals. For Kardia Mobile, the QT and QTcF intervals correlated significantly with the gold standard (rQT=0.857 and rQTcF=0.727; P<.001). CCCLin corresponded to an almost complete heuristic agreement for the QT interval (0.835), whereas the QTcF interval was in the range of strong agreement (0.682). Further, for the Apple Watch, Pearson correlations were highly significant and in the range of a large effect (rQT=0.793 and rQTcF=0.649; P<.001). CCCLin corresponded to a strong heuristic agreement for both the QT (0.779) and QTcF (0.615) intervals. A small negative correlation between the measurement error and increasing heart rate could be found of each the devices and the reference. CONCLUSIONS Smart technology seems to be a promising and reliable approach for nonclinical health monitoring. Further research is needed to broaden the evidence regarding its validity and usability in different target groups.
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Affiliation(s)
- Kristina Klier
- Institute of Sport Science, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Lucas Koch
- Institute of Sport Science, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Lisa Graf
- Institute of Sport Science, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Timo Schinköthe
- CANKADO GmbH, Ottobrunn, Germany
- Research Center for Smart Digital Health, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Annette Schmidt
- Institute of Sport Science, University of the Bundeswehr Munich, Neubiberg, Germany
- Research Center for Smart Digital Health, University of the Bundeswehr Munich, Neubiberg, Germany
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10
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Romanchuk O. Cardiorespiratory dynamics during respiratory maneuver in athletes. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3. [DOI: https:/doi.org/10.3389/fnetp.2023.1276899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
Introduction: The modern practice of sports medicine and medical rehabilitation requires the search for subtle criteria for the development of conditions and recovery of the body after diseases, which would have a prognostic value for the prevention of negative effects of training and rehabilitation tools, and also testify to the development and course of mechanisms for counteracting pathogenetic processes in the body. The purpose of this study was to determine the informative directions of the cardiorespiratory system parameters dynamics during the performing a maneuver with a change in breathing rate, which may indicate the body functional state violation.Methods: The results of the study of 183 healthy men aged 21.2 ± 2.3 years who regularly engaged in various sports were analyzed. The procedure for studying the cardiorespiratory system included conducting combined measurements of indicators of activity of the respiratory and cardiovascular systems in a sitting position using a spiroarteriocardiograph device. The duration of the study was 6 min and involved the sequential registration of three measurements with a change in breathing rate (spontaneous breathing, breathing at 0.1 Hz and 0.25 Hz).Results: Performing a breathing maneuver at breathing 0.1 Hz and breathing 0.25 Hz in comparison with spontaneous breathing leads to multidirectional significant changes in heart rate variability indicators–TP (ms2), LF (ms2), LFHF (ms2/ms2); of blood pressure variability indicators–TPDBP (mmHg2), LFSBP (mmHg2), LFDBP (mmHg2), HFSBP (mmHg2); of volume respiration variability indicators - LFR, (L×min-1)2; HFR, (L×min-1)2; LFHFR, (L×min-1)2/(L×min-1)2; of arterial baroreflex sensitivity indicators - BRLF (ms×mmHg-1), BRHF (ms×mmHg-1). Differences in indicators of systemic hemodynamics and indicators of cardiovascular and respiratory systems synchronization were also informative.Conclusion: According to the results of the study, it is shown that during performing a breathing maneuver with a change in the rate of breathing, there are significant changes in cardiorespiratory parameters, the analysis of which the increments made it possible to determine of the changes directions dynamics, their absolute values and informative limits regarding the possible occurrence of the cardiorespiratory interactions dysregulation.
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Romanchuk O. Cardiorespiratory dynamics during respiratory maneuver in athletes. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1276899. [PMID: 38020241 PMCID: PMC10643240 DOI: 10.3389/fnetp.2023.1276899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 10/19/2023] [Indexed: 12/01/2023]
Abstract
Introduction: The modern practice of sports medicine and medical rehabilitation requires the search for subtle criteria for the development of conditions and recovery of the body after diseases, which would have a prognostic value for the prevention of negative effects of training and rehabilitation tools, and also testify to the development and course of mechanisms for counteracting pathogenetic processes in the body. The purpose of this study was to determine the informative directions of the cardiorespiratory system parameters dynamics during the performing a maneuver with a change in breathing rate, which may indicate the body functional state violation. Methods: The results of the study of 183 healthy men aged 21.2 ± 2.3 years who regularly engaged in various sports were analyzed. The procedure for studying the cardiorespiratory system included conducting combined measurements of indicators of activity of the respiratory and cardiovascular systems in a sitting position using a spiroarteriocardiograph device. The duration of the study was 6 min and involved the sequential registration of three measurements with a change in breathing rate (spontaneous breathing, breathing at 0.1 Hz and 0.25 Hz). Results: Performing a breathing maneuver at breathing 0.1 Hz and breathing 0.25 Hz in comparison with spontaneous breathing leads to multidirectional significant changes in heart rate variability indicators-TP (ms2), LF (ms2), LFHF (ms2/ms2); of blood pressure variability indicators-TPDBP (mmHg2), LFSBP (mmHg2), LFDBP (mmHg2), HFSBP (mmHg2); of volume respiration variability indicators - LFR, (L×min-1)2; HFR, (L×min-1)2; LFHFR, (L×min-1)2/(L×min-1)2; of arterial baroreflex sensitivity indicators - BRLF (ms×mmHg-1), BRHF (ms×mmHg-1). Differences in indicators of systemic hemodynamics and indicators of cardiovascular and respiratory systems synchronization were also informative. Conclusion: According to the results of the study, it is shown that during performing a breathing maneuver with a change in the rate of breathing, there are significant changes in cardiorespiratory parameters, the analysis of which the increments made it possible to determine of the changes directions dynamics, their absolute values and informative limits regarding the possible occurrence of the cardiorespiratory interactions dysregulation.
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Affiliation(s)
- Oleksandr Romanchuk
- Department of Medical Rehabilitation, Ukrainian Research Institute of Medical Rehabilitation and Resort Therapy of the Ministry of Health of Ukraine, Odesa, Ukraine
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12
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Støve MP, Graversen AH, Sørensen J. Assessment of Noninvasive Oxygen Saturation in Patients With COPD During Pulmonary Rehabilitation: Smartwatch versus Pulse Oximeter. Respir Care 2023; 68:1041-1048. [PMID: 37193599 PMCID: PMC10353168 DOI: 10.4187/respcare.10760] [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: 05/18/2023]
Abstract
BACKGROUND Patients with COPD can have hypoxemia; hence, monitoring peripheral SpO2 during pulmonary rehabilitation is recommended. This study aimed to examine the accuracy of SpO2 readings in patients with COPD as measured by wearable devices at rest and after physical exercise. METHODS Thirty-six participants with COPD (20 women), ages 52-89 years, participated in this cross-sectional study. Oxygen saturation was concurrently measured by using the Contec Pulse Oximeter CMS50D as a comparator, and the Apple Watch Series 7 and the Garmin Vivosmart 4 at rest and immediately after the 30-s sit-to-stand test and the 6-min walk test (6MWT). RESULTS For the Apple Watch, the root mean squared error showed a deviation of 3.5% at rest, 4.1% after the 30-s sit-to-stand test, and 3.9% after the 6MWT. The level of agreement was 2.8 ± 2.4 (7.6, -1.9) at rest, 3.1 ± 2.8 (8.6, -2.3) after the 30-s sit-to-stand test, and 2.8 ± 2.9 (8.6, -2.9) after the 6MWT. For the Garmin Vivosmart, the root mean squared error showed a deviation of 3.3% at rest, 6.1% after the 30-s sit-to-stand test, and 5.4% after the 6MWT. Level of agreement was 1.9 ± 2.7 (7.2, -3.3) at rest, 2.9 ± 5.4 (13.5, -7.7) after the 30-s sit-to-stand test, and 2.3 ± 5.0 (12.1, -7.4) after the 6MWT. The limits of agreement showed considerable measurement variance and a tendency for the devices to be less accurate at lower saturation levels. CONCLUSIONS The Apple Watch Series 7 and Garmin Vivosmart 4 overestimated SpO2 in participants with COPD when SpO2 was < 95% and underestimated oxygen saturation when saturation was > 95%. These findings suggest that wearable devices should not be used to monitor oxygen saturation during pulmonary rehabilitation.
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Affiliation(s)
- Morten Pallisgaard Støve
- Department of Physiotherapy, University College of Northern Denmark, Aalborg, Denmark.
- Centre for General Practice, Aalborg University, Aalborg East, Denmark
| | | | - Johanne Sørensen
- Department of Physiotherapy, University College of Northern Denmark, Aalborg, Denmark
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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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Romagnoli S, Ripanti F, Morettini M, Burattini L, Sbrollini A. Wearable and Portable Devices for Acquisition of Cardiac Signals while Practicing Sport: A Scoping Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23063350. [PMID: 36992060 PMCID: PMC10055735 DOI: 10.3390/s23063350] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/16/2023] [Accepted: 03/20/2023] [Indexed: 05/31/2023]
Abstract
Wearable and portable devices capable of acquiring cardiac signals are at the frontier of the sport industry. They are becoming increasingly popular for monitoring physiological parameters while practicing sport, given the advances in miniaturized technologies, powerful data, and signal processing applications. Data and signals acquired by these devices are increasingly used to monitor athletes' performances and thus to define risk indices for sport-related cardiac diseases, such as sudden cardiac death. This scoping review investigated commercial wearable and portable devices employed for cardiac signal monitoring during sport activity. A systematic search of the literature was conducted on PubMed, Scopus, and Web of Science. After study selection, a total of 35 studies were included in the review. The studies were categorized based on the application of wearable or portable devices in (1) validation studies, (2) clinical studies, and (3) development studies. The analysis revealed that standardized protocols for validating these technologies are necessary. Indeed, results obtained from the validation studies turned out to be heterogeneous and scarcely comparable, since the metrological characteristics reported were different. Moreover, the validation of several devices was carried out during different sport activities. Finally, results from clinical studies highlighted that wearable devices are crucial to improve athletes' performance and to prevent adverse cardiovascular events.
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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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Budig M, Stoohs R, Keiner M. Validity of Two Consumer Multisport Activity Tracker and One Accelerometer against Polysomnography for Measuring Sleep Parameters and Vital Data in a Laboratory Setting in Sleep Patients. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22239540. [PMID: 36502241 PMCID: PMC9741062 DOI: 10.3390/s22239540] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 11/25/2022] [Accepted: 12/01/2022] [Indexed: 05/16/2023]
Abstract
Two commercial multisport activity trackers (Garmin Forerunner 945 and Polar Ignite) and the accelerometer ActiGraph GT9X were evaluated in measuring vital data, sleep stages and sleep/wake patterns against polysomnography (PSG). Forty-nine adult patients with suspected sleep disorders (30 males/19 females) completed a one-night PSG sleep examination followed by a multiple sleep latency test (MSLT). Sleep parameters, time in bed (TIB), total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL), awake time (WASO + SOL), sleep stages (light, deep, REM sleep) and the number of sleep cycles were compared. Both commercial trackers showed high accuracy in measuring vital data (HR, HRV, SpO2, respiratory rate), r > 0.92. For TIB and TST, all three trackers showed medium to high correlation, r > 0.42. Garmin had significant overestimation of TST, with MAE of 84.63 min and MAPE of 25.32%. Polar also had an overestimation of TST, with MAE of 45.08 min and MAPE of 13.80%. ActiGraph GT9X results were inconspicuous. The trackers significantly underestimated awake times (WASO + SOL) with weak correlation, r = 0.11−0.57. The highest MAE was 50.35 min and the highest MAPE was 83.02% for WASO for Garmin and ActiGraph GT9X; Polar had the highest MAE of 21.17 min and the highest MAPE of 141.61% for SOL. Garmin showed significant deviations for sleep stages (p < 0.045), while Polar only showed significant deviations for sleep cycle (p = 0.000), r < 0.50. Garmin and Polar overestimated light sleep and underestimated deep sleep, Garmin significantly, with MAE up to 64.94 min and MAPE up to 116.50%. Both commercial trackers Garmin and Polar did not detect any daytime sleep at all during the MSLT test. The use of the multisport activity trackers for sleep analysis can only be recommended for general daily use and for research purposes. If precise data on sleep stages and parameters are required, their use is limited. The accuracy of the vital data measurement was adequate. Further studies are needed to evaluate their use for medical purposes, inside and outside of the sleep laboratory. The accelerometer ActiGraph GT9X showed overall suitable accuracy in detecting sleep/wake patterns.
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Affiliation(s)
- Mario Budig
- Department of Sports Science, German University of Health & Sport, 85737 Ismaning, Germany
| | | | - Michael Keiner
- Department of Sports Science, German University of Health & Sport, 85737 Ismaning, Germany
- Correspondence:
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Agreement between two photoplethysmography-based wearable devices for monitoring heart rate during different physical activity situations: a new analysis methodology. Sci Rep 2022; 12:15448. [PMID: 36104356 PMCID: PMC9474518 DOI: 10.1038/s41598-022-18356-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 08/10/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractWearables are being increasingly used to monitor heart rate (HR). However, their usefulness for analyzing continuous HR in research or at clinical level is questionable. The aim of this study is to analyze the level of agreement between different wearables in the measurement of HR based on photoplethysmography, according to different body positions and physical activity levels, and compared to a gold-standard ECG. The proposed method measures agreement among several time scales since different wearables obtain HR at different sampling rates. Eighteen university students (10 men, 8 women; 22 ± 2.45 years old) participated in a laboratory study. Participants simultaneously wore an Apple Watch and a Polar Vantage watch. ECG was measured using a BIOPAC system. HR was recorded continuously and simultaneously by the three devices, for consecutive 5-min periods in 4 different situations: lying supine, sitting, standing and walking at 4 km/h on a treadmill. HR estimations were obtained with the maximum precision offered by the software of each device and compared by averaging in several time scales, since the wearables obtained HR at different sampling rates, although results are more detailed for 5 s and 30 s epochs. Bland–Altman (B-A) plots show that there is no noticeable difference between data from the ECG and any of the smartwatches while participants were lying down. In this position, the bias is low when averaging in both 5 s and 30 s. Differently, B-A plots show that there are differences when the situation involves some level of physical activity, especially for shorter epochs. That is, the discrepancy between devices and the ECG was greater when walking on the treadmill and during short time scales. The device showing the biggest discrepancy was the Polar Watch, and the one with the best results was the Apple Watch. We conclude that photoplethysmography-based wearable devices are suitable for monitoring HR averages at regular intervals, especially at rest, but their feasibility is debatable for a continuous analysis of HR for research or clinical purposes, especially when involving some level of physical activity. An important contribution of this work is a new methodology to synchronize and measure the agreement against a gold standard of two or more devices measuring HR at different and not necessarily even paces.
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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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Schaffarczyk M, Rogers B, Reer R, Gronwald T. Validity of the Polar H10 Sensor for Heart Rate Variability Analysis during Resting State and Incremental Exercise in Recreational Men and Women. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22176536. [PMID: 36081005 PMCID: PMC9459793 DOI: 10.3390/s22176536] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 08/23/2022] [Accepted: 08/25/2022] [Indexed: 05/09/2023]
Abstract
Heart rate variability (HRV) is frequently applied in sport-specific settings. The rising use of freely accessible applications for its recording requires validation processes to ensure accurate data. It is the aim of this study to compare the HRV data obtained by the Polar H10 sensor chest strap device and an electrocardiogram (ECG) with the focus on RR intervals and short-term scaling exponent alpha 1 of Detrended Fluctuation Analysis (DFA a1) as non-linear metric of HRV analysis. A group of 25 participants performed an exhaustive cycling ramp with measurements of HRV with both recording systems. Average time between heartbeats (RR), heart rate (HR) and DFA a1 were recorded before (PRE), during, and after (POST) the exercise test. High correlations were found for the resting conditions (PRE: r = 0.95, rc = 0.95, ICC3,1 = 0.95, POST: r = 0.86, rc = 0.84, ICC3,1 = 0.85) and for the incremental exercise (r > 0.93, rc > 0.93, ICC3,1 > 0.93). While PRE and POST comparisons revealed no differences, significant bias could be found during the exercise test for all variables (p < 0.001). For RR and HR, bias and limits of agreement (LoA) in the Bland−Altman analysis were minimal (RR: bias of 0.7 to 0.4 ms with LoA of 4.3 to −2.8 ms during low intensity and 1.3 to −0.5 ms during high intensity, HR: bias of −0.1 to −0.2 ms with LoA of 0.3 to −0.5 ms during low intensity and 0.4 to −0.7 ms during high intensity). DFA a1 showed wider bias and LoAs (bias of 0.9 to 8.6% with LoA of 11.6 to −9.9% during low intensity and 58.1 to −40.9% during high intensity). Linear HRV measurements derived from the Polar H10 chest strap device show strong agreement and small bias compared with ECG recordings and can be recommended for practitioners. However, with respect to DFA a1, values in the uncorrelated range and during higher exercise intensities tend to elicit higher bias and wider LoA.
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Affiliation(s)
- Marcelle Schaffarczyk
- Department Sports and Exercise Medicine, Institute of Human Movement Science, University of Hamburg, 20148 Hamburg, Germany
- Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, 20457 Hamburg, Germany
- Correspondence:
| | - Bruce Rogers
- Department of Internal Medicine, College of Medicine, University of Central Florida, Orlando, FL 32827, USA
| | - Rüdiger Reer
- Department Sports and Exercise Medicine, Institute of Human Movement Science, University of Hamburg, 20148 Hamburg, Germany
| | - Thomas Gronwald
- Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, 20457 Hamburg, Germany
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Charlton PH, Kotzen K, Mejía-Mejía E, Aston PJ, Budidha K, Mant J, Pettit C, Behar JA, Kyriacou PA. Detecting beats in the photoplethysmogram: benchmarking open-source algorithms. Physiol Meas 2022; 43. [PMID: 35853440 PMCID: PMC9393905 DOI: 10.1088/1361-6579/ac826d] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 07/19/2022] [Indexed: 11/12/2022]
Abstract
The photoplethysmogram (PPG) signal is widely used in pulse oximeters and smartwatches. A fundamental step in analysing the PPG is the detection of heartbeats. Several PPG beat detection algorithms have been proposed, although it is not clear which performs best. OBJECTIVE This study aimed to: (i) develop a framework with which to design and test PPG beat detectors; (ii) assess the performance of PPG beat detectors in different use cases; and (iii) investigate how their performance is affected by patient demographics and physiology. APPROACH Fifteen beat detectors were assessed against electrocardiogram-derived heartbeats using data from eight datasets. Performance was assessed using the F1 score, which combines sensitivity and positive predictive value. MAIN RESULTS Eight beat detectors performed well in the absence of movement, with F1 scores of ≥90\% on hospital data and wearable data collected at rest. Their performance was poorer during exercise, with F1 scores of 55-91\%; poorer in neonates than adults with F1 scores of 84-96\% in neonates compared to 98-99\% in adults; and poorer in atrial fibrillation (AF), with F1 scores of 92-97\% in AF, compared to 99-100\% in normal sinus rhythm. SIGNIFICANCE Two PPG beat detectors denoted 'MSPTD' and 'qppg' performed best, with complementary performance characteristics. This evidence can be used to inform the choice of PPG beat detector algorithm. The algorithms, datasets, and assessment framework are freely available.
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Affiliation(s)
- Peter H Charlton
- Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, Cambridgeshire, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Kevin Kotzen
- Faculty of Biomedical Engineering, Technion Israel Institute of Technology, Julius Silver Building, Haifa, 32000, ISRAEL
| | - Elisa Mejía-Mejía
- Research Centre for Biomedical Engineering, City University of London, Northampton Square, London, EC1V 0HB, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Philip J Aston
- Department of Mathematics, University of Surrey, Thomas Telford building (AA), floor 4, Guildford, Surrey, GU2 7XH, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Karthik Budidha
- Research Centre for Biomedical Engineering, City University of London, Northampton Square, London, EC1V 0HB, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Jonathan Mant
- Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, Cambridgeshire, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Callum Pettit
- Department of Mathematics, University of Surrey, Thomas Telford building (AA), floor 4, Guildford, Surrey, GU2 7XH, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Joachim A Behar
- Biomedical Engineering Faculty, Technion Israel Institute of Technology, Julius Silver Building, Haifa, 32000, ISRAEL
| | - Panayiotis A Kyriacou
- Research Centre for Biomedical Engineering, City University of London, Northampton Square, London, EC1V 0HB, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
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Estimation of Heart Rate and Energy Expenditure Using a Smart Bracelet during Different Exercise Intensities: A Reliability and Validity Study. SENSORS 2022; 22:s22134661. [PMID: 35808157 PMCID: PMC9268904 DOI: 10.3390/s22134661] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 06/15/2022] [Accepted: 06/16/2022] [Indexed: 11/16/2022]
Abstract
Background. With wrist-worn wearables becoming increasingly available, it is important to understand their reliability and validity in different conditions. The primary objective of this study was to examine the reliability and validity of the Lexin Mio smart bracelet in measuring heart rate (HR) and energy expenditure (EE) in people with different physical activity levels exercising at different intensities. Methods. A total of 65 participants completed one maximal oxygen uptake test and two running exercise tests wearing the Mio smart bracelet, the Polar H10 HR band, and a gas-analysis system. Results. In terms of HR measurement reliability, the Mio smart bracelet showed good reliability in a left versus right test and good test−retest reliability (p > 0.05; mean absolute percentage error (MAPE) < 10%; intraclass correlation coefficient (ICC) > 0.4). For EE measurement, the Mio smart bracelet showed good reliability in a left versus right test, good test−retest reliability on the right (p > 0.05; MAPE > 10%; ICC > 0.4), and low test−retest reliability on the left (p > 0.05; MAPE > 10%; ICC < 0.4). Regarding validity, the Mio smart bracelet showed good validity for HR measurement (p > 0.05; MAPE < 10%; ICC > 0.4) and low validity for EE measurement (p < 0.05; MAPE > 10%; ICC < 0.4). Conclusion. The Lexin Mio smart bracelet showed good reliability and validity for HR measurement among people with different physical activity levels exercising at various exercise intensities in a laboratory setting. However, the smart bracelet showed good reliability and low validity for the estimation of EE.
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22
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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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23
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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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24
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Charlton PH, Pilt K, Kyriacou PA. Establishing best practices in photoplethysmography signal acquisition and processing. Physiol Meas 2022; 43. [PMID: 35508148 PMCID: PMC9136485 DOI: 10.1088/1361-6579/ac6cc4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 05/04/2022] [Indexed: 11/19/2022]
Abstract
Photoplethysmography is now widely utilised by clinical devices such as pulse oximeters, and wearable devices such as smartwatches. It holds great promise for health monitoring in daily life. This editorial considers whether it would be possible and beneficial to establish best practices for photoplethysmography signal acquisition and processing. It reports progress made towards this, balanced with the challenges of working with a diverse range of photoplethysmography device designs and intended applications, each of which could benefit from different approaches to signal acquisition and processing. It concludes that there are several potential benefits to establishing best practices. However, it is not yet clear whether it is possible to establish best practices which hold across the range of photoplethysmography device designs and applications.
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Affiliation(s)
- Peter H Charlton
- Department of Public Health and Primary Care, Cambridge University, Strangeways Research Laboratory, 2 Worts' Causeway, Cambridge, CB1 8RN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Kristjan Pilt
- Department of Health Technologies, Tallinn University of Technology, Ehitajate tee 5, Tallinn, Harjumaa, 19086, ESTONIA
| | - Panayiotis A Kyriacou
- School of Mathematics Computer Science and Engineering, City University of London, Northampton Square, London, EC1V 0HB, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
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25
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Held NJ, Perrotta AS, Mueller T, Pfoh-MacDonald SJ. Agreement of the Apple Watch® and Fitbit Charge® for recording step count and heart rate when exercising in water. Med Biol Eng Comput 2022; 60:1323-1331. [DOI: 10.1007/s11517-022-02536-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 01/17/2022] [Indexed: 11/30/2022]
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26
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Shei RJ, Holder IG, Oumsang AS, Paris BA, Paris HL. Wearable activity trackers-advanced technology or advanced marketing? Eur J Appl Physiol 2022; 122:1975-1990. [PMID: 35445837 PMCID: PMC9022022 DOI: 10.1007/s00421-022-04951-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 04/04/2022] [Indexed: 11/26/2022]
Abstract
Wearable devices represent one of the most popular trends in health and fitness. Rapid advances in wearable technology present a dizzying display of possible functions: from thermometers and barometers, magnetometers and accelerometers, to oximeters and calorimeters. Consumers and practitioners utilize wearable devices to track outcomes, such as energy expenditure, training load, step count, and heart rate. While some rely on these devices in tandem with more established tools, others lean on wearable technology for health-related outcomes, such as heart rhythm analysis, peripheral oxygen saturation, sleep quality, and caloric expenditure. Given the increasing popularity of wearable devices for both recreation and health initiatives, understanding the strengths and limitations of these technologies is increasingly relevant. Need exists for continued evaluation of the efficacy of wearable devices to accurately and reliably measure purported outcomes. The purposes of this review are (1) to assess the current state of wearable devices using recent research on validity and reliability, (2) to describe existing gaps between physiology and technology, and (3) to offer expert interpretation for the lay and professional audience on how best to approach wearable technology and employ it in the pursuit of health and fitness. Current literature demonstrates inconsistent validity and reliability for various metrics, with algorithms not publicly available or lacking high-quality validation studies. Advancements in wearable technology should consider standardizing validation metrics, providing transparency in used algorithms, and improving how technology can be tailored to individuals. Until then, it is prudent to exercise caution when interpreting metrics reported from consumer-wearable devices.
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Affiliation(s)
- Ren-Jay Shei
- Indiana University Alumni Association, Indiana University, 1000 E 17th Street, Bloomington, IN, 47408, USA.
| | - Ian G Holder
- Department of Sports Medicine, Pepperdine University, Malibu, CA, USA
| | - Alicia S Oumsang
- Department of Sports Medicine, Pepperdine University, Malibu, CA, USA
| | - Brittni A Paris
- Department of Sports Medicine, Pepperdine University, Malibu, CA, USA
| | - Hunter L Paris
- Department of Sports Medicine, Pepperdine University, Malibu, CA, USA
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27
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Charlton PH, Kyriacou PA, Mant J, Marozas V, Chowienczyk P, Alastruey J. Wearable Photoplethysmography for Cardiovascular Monitoring. PROCEEDINGS OF THE IEEE. INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS 2022; 110:355-381. [PMID: 35356509 PMCID: PMC7612541 DOI: 10.1109/jproc.2022.3149785] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 01/06/2022] [Accepted: 01/27/2022] [Indexed: 05/29/2023]
Abstract
Smart wearables provide an opportunity to monitor health in daily life and are emerging as potential tools for detecting cardiovascular disease (CVD). Wearables such as fitness bands and smartwatches routinely monitor the photoplethysmogram signal, an optical measure of the arterial pulse wave that is strongly influenced by the heart and blood vessels. In this survey, we summarize the fundamentals of wearable photoplethysmography and its analysis, identify its potential clinical applications, and outline pressing directions for future research in order to realize its full potential for tackling CVD.
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Affiliation(s)
- Peter H. Charlton
- Department of Biomedical EngineeringSchool of Biomedical Engineering and Imaging SciencesKing’s College London, King’s Health PartnersLondonSE1 7EUU.K.
- Research Centre for Biomedical Engineering, CityUniversity of LondonLondonEC1V 0HBU.K.
- Department of Public Health and Primary CareUniversity of CambridgeCambridgeCB1 8RNU.K.
| | - Panicos A. Kyriacou
- Research Centre for Biomedical Engineering, CityUniversity of LondonLondonEC1V 0HBU.K.
| | - Jonathan Mant
- Department of Public Health and Primary CareUniversity of CambridgeCambridgeCB1 8RNU.K.
| | - Vaidotas Marozas
- Department of Electronics Engineering and the Biomedical Engineering Institute, Kaunas University of Technology44249KaunasLithuania
| | - Phil Chowienczyk
- Department of Clinical PharmacologyKing’s College LondonLondonSE1 7EHU.K.
| | - Jordi Alastruey
- Department of Biomedical EngineeringSchool of Biomedical Engineering and Imaging SciencesKing’s College London, King’s Health PartnersLondonSE1 7EUU.K.
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28
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Rogers B, Schaffarczyk M, Clauß M, Mourot L, Gronwald T. The Movesense Medical Sensor Chest Belt Device as Single Channel ECG for RR Interval Detection and HRV Analysis during Resting State and Incremental Exercise: A Cross-Sectional Validation Study. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22052032. [PMID: 35271179 PMCID: PMC8914935 DOI: 10.3390/s22052032] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 02/26/2022] [Accepted: 03/03/2022] [Indexed: 05/05/2023]
Abstract
The value of heart rate variability (HRV) in the fields of health, disease, and exercise science has been established through numerous investigations. The typical mobile-based HRV device simply records interbeat intervals, without differentiation between noise or arrythmia as can be done with an electrocardiogram (ECG). The intent of this report is to validate a new single channel ECG device, the Movesense Medical sensor, against a conventional 12 channel ECG. A heterogeneous group of 21 participants performed an incremental cycling ramp to failure with measurements of HRV, before (PRE), during (EX), and after (POST). Results showed excellent correlations between devices for linear indexes with Pearson's r between 0.98 to 1.0 for meanRR, SDNN, RMSSD, and 0.95 to 0.97 for the non-linear index DFA a1 during PRE, EX, and POST. There was no significant difference in device specific meanRR during PRE and POST. Bland-Altman analysis showed high agreement between devices (PRE and POST: meanRR bias of 0.0 and 0.4 ms, LOA of 1.9 to -1.8 ms and 2.3 to -1.5; EX: meanRR bias of 11.2 to 6.0 ms; LOA of 29.8 to -7.4 ms during low intensity exercise and 8.5 to 3.5 ms during high intensity exercise). The Movesense Medical device can be used in lieu of a reference ECG for the calculation of HRV with the potential to differentiate noise from atrial fibrillation and represents a significant advance in both a HR and HRV recording device in a chest belt form factor for lab-based or remote field-application.
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Affiliation(s)
- Bruce Rogers
- Department of Internal Medicine, College of Medicine, University of Central Florida, Orlando, FL 32827, USA
- Correspondence:
| | - Marcelle Schaffarczyk
- Department Sports and Exercise Medicine, Institute of Human Movement Science, University of Hamburg, 20148 Hamburg, Germany;
| | - Martina Clauß
- Institute of Movement and Trainings Science in Sport, Faculty of Sport Science, Leipzig University, 04109 Leipzig, Germany;
| | - Laurent Mourot
- EA3920 Pronostic Factors and Regulatory Factors of Cardiac and Vascular Pathologies, Exercise Performance Health Innovation (EPHI) Plaptform, University of Bourgogne Franche-Comté, 25000 Besançon, France;
- Division for Physical Education, National Research Tomsk Polytechnic University, 634040 Tomsk, Russia
| | - Thomas Gronwald
- Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, 20457 Hamburg, Germany;
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29
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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: 9] [Impact Index Per Article: 4.5] [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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30
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Bouillod A, Soto-Romero G, Grappe F, Bertucci W, Brunet E, Cassirame J. Caveats and Recommendations to Assess the Validity and Reliability of Cycling Power Meters: A Systematic Scoping Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22010386. [PMID: 35009945 PMCID: PMC8749704 DOI: 10.3390/s22010386] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 12/24/2021] [Accepted: 12/31/2021] [Indexed: 05/05/2023]
Abstract
A large number of power meters have become commercially available during the last decades to provide power output (PO) measurement. Some of these power meters were evaluated for validity in the literature. This study aimed to perform a review of the available literature on the validity of cycling power meters. PubMed, SPORTDiscus, and Google Scholar have been explored with PRISMA methodology. A total of 74 studies have been extracted for the reviewing process. Validity is a general quality of the measurement determined by the assessment of different metrological properties: Accuracy, sensitivity, repeatability, reproducibility, and robustness. Accuracy was most often studied from the metrological property (74 studies). Reproducibility was the second most studied (40 studies) property. Finally, repeatability, sensitivity, and robustness were considerably less studied with only 7, 5, and 5 studies, respectively. The SRM power meter is the most used as a gold standard in the studies. Moreover, the number of participants was very different among them, from 0 (when using a calibration rig) to 56 participants. The PO tested was up to 1700 W, whereas the pedalling cadence ranged between 40 and 180 rpm, including submaximal and maximal exercises. Other exercise conditions were tested, such as torque, position, temperature, and vibrations. This review provides some caveats and recommendations when testing the validity of a cycling power meter, including all of the metrological properties (accuracy, sensitivity, repeatability, reproducibility, and robustness) and some exercise conditions (PO range, sprint, pedalling cadence, torque, position, participant, temperature, vibration, and field test).
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Affiliation(s)
- Anthony Bouillod
- EA4660, C3S Health-Sport Department, Sports University, 25000 Besancon, France; (A.B.); (F.G.)
- French Cycling Federation, 78180 Saint Quentin, France;
- LAAS-CNRS, Université de Toulouse, CNRS, 31000 Toulouse, France;
- Professional Cycling Team FDJ, 77230 Moussy-le-Vieux, France
| | | | - Frederic Grappe
- EA4660, C3S Health-Sport Department, Sports University, 25000 Besancon, France; (A.B.); (F.G.)
- Professional Cycling Team FDJ, 77230 Moussy-le-Vieux, France
| | - William Bertucci
- EA7507, Laboratoire Performance, Santé, Métrologie, Société, 51100 Reims, France;
| | | | - Johan Cassirame
- EA4660, C3S Health-Sport Department, Sports University, 25000 Besancon, France; (A.B.); (F.G.)
- EA7507, Laboratoire Performance, Santé, Métrologie, Société, 51100 Reims, France;
- Mtraining, R&D Division, 25480 Ecole Valentin, France
- Correspondence: ; Tel.: +33-6-8781-8295
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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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32
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Budig M, Keiner M, Stoohs R, Hoffmeister M, Höltke V. Heart Rate and Distance Measurement of Two Multisport Activity Trackers and a Cellphone App in Different Sports: A Cross-Sectional Validation and Comparison Field Study. SENSORS (BASEL, SWITZERLAND) 2021; 22:180. [PMID: 35009723 PMCID: PMC8749603 DOI: 10.3390/s22010180] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 12/24/2021] [Accepted: 12/26/2021] [Indexed: 11/16/2022]
Abstract
Options for monitoring sports have been continuously developed by using activity trackers to determine almost all vital and movement parameters. The aim of this study was to validate heart rate and distance measurements of two activity trackers (Polar Ignite; Garmin Forerunner 945) and a cellphone app (Polar Beat app using iPhone 7 as a hardware platform) in a cross-sectional field study. Thirty-six moderate endurance-trained adults (20 males/16 females) completed a test battery consisting of walking and running 3 km, a 1.6 km interval run (standard 400 m outdoor stadium), 3 km forest run (outdoor), 500/1000 m swim and 4.3/31.5 km cycling tests. Heart rate was recorded via a Polar H10 chest strap and distance was controlled via a map, 400 m stadium or 50 m pool. For all tests except swimming, strong correlation values of r > 0.90 were calculated with moderate exercise intensity and a mean absolute percentage error of 2.85%. During the interval run, several significant deviations (p < 0.049) were observed. The swim disciplines showed significant differences (p < 0.001), with the 500 m test having a mean absolute percentage error of 8.61%, and the 1000 m test of 55.32%. In most tests, significant deviations (p < 0.001) were calculated for distance measurement. However, a maximum mean absolute percentage error of 4.74% and small mean absolute error based on the total route lengths were calculated. This study showed that the accuracy of heart rate measurements could be rated as good, except for rapid changing heart rate during interval training and swimming. Distance measurement differences were rated as non-relevant in practice for use in sports.
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Affiliation(s)
- Mario Budig
- Department of Sports Science, German University of Health & Sport, 85737 Ismaning, Germany; (M.B.); (M.H.); (V.H.)
| | - Michael Keiner
- Department of Sports Science, German University of Health & Sport, 85737 Ismaning, Germany; (M.B.); (M.H.); (V.H.)
| | | | - Meike Hoffmeister
- Department of Sports Science, German University of Health & Sport, 85737 Ismaning, Germany; (M.B.); (M.H.); (V.H.)
| | - Volker Höltke
- Department of Sports Science, German University of Health & Sport, 85737 Ismaning, Germany; (M.B.); (M.H.); (V.H.)
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33
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Abstract
For apparently healthy pregnant women, regular physical activity is recommended. The American College of Obstetricians and Gynecologists (ACOG) created recommendations for physical activity and exercise during pregnancy in 1985. At that time, pregnant women were advised to not exceed a heart rate of 140 beats per minute with physical activity. The heart rate recommendation was subsequently removed with the recommendations published in 1994, 2002, and 2015. In 2020, the ACOG updated its recommendations on physical activity for pregnant and postpartum women. The recommendation included exercising at a "fairly light to somewhat hard" perceived intensity and at less than 60-80% of age-predicted maximum heart rate, usually not exceeding a heart rate of 140 beats per minute. Women often seek advice from healthcare providers on physical activity during pregnancy, yet providers report concern about giving appropriate physical activity guidance. This paper summarizes the key scientific literature on monitoring absolute and relative exercise intensity in relation to the current ACOG recommendations, providing background on intensity-related concepts used in the recommendation. This paper also provides practical guidance to assist healthcare providers in relaying this information to pregnant women.
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Affiliation(s)
- Kelly R. Evenson
- Kelly R. Evenson, Department of
Epidemiology, University of NC, Gillings School of Global Public Health, 123 W
Franklin Street, Building C, Suite 410, Chapel Hill, NC, USA; e-mail:
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34
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Ash GI, Stults-Kolehmainen M, Busa MA, Gaffey AE, Angeloudis K, Muniz-Pardos B, Gregory R, Huggins RA, Redeker NS, Weinzimer SA, Grieco LA, Lyden K, Megally E, Vogiatzis I, Scher L, Zhu X, Baker JS, Brandt C, Businelle MS, Fucito LM, Griggs S, Jarrin R, Mortazavi BJ, Prioleau T, Roberts W, Spanakis EK, Nally LM, Debruyne A, Bachl N, Pigozzi F, Halabchi F, Ramagole DA, Janse van Rensburg DC, Wolfarth B, Fossati C, Rozenstoka S, Tanisawa K, Börjesson M, Casajus JA, Gonzalez-Aguero A, Zelenkova I, Swart J, Gursoy G, Meyerson W, Liu J, Greenbaum D, Pitsiladis YP, Gerstein MB. Establishing a Global Standard for Wearable Devices in Sport and Exercise Medicine: Perspectives from Academic and Industry Stakeholders. Sports Med 2021; 51:2237-2250. [PMID: 34468950 PMCID: PMC8666971 DOI: 10.1007/s40279-021-01543-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/08/2021] [Indexed: 10/20/2022]
Abstract
Millions of consumer sport and fitness wearables (CSFWs) are used worldwide, and millions of datapoints are generated by each device. Moreover, these numbers are rapidly growing, and they contain a heterogeneity of devices, data types, and contexts for data collection. Companies and consumers would benefit from guiding standards on device quality and data formats. To address this growing need, we convened a virtual panel of industry and academic stakeholders, and this manuscript summarizes the outcomes of the discussion. Our objectives were to identify (1) key facilitators of and barriers to participation by CSFW manufacturers in guiding standards and (2) stakeholder priorities. The venues were the Yale Center for Biomedical Data Science Digital Health Monthly Seminar Series (62 participants) and the New England Chapter of the American College of Sports Medicine Annual Meeting (59 participants). In the discussion, stakeholders outlined both facilitators of (e.g., commercial return on investment in device quality, lucrative research partnerships, and transparent and multilevel evaluation of device quality) and barriers (e.g., competitive advantage conflict, lack of flexibility in previously developed devices) to participation in guiding standards. There was general agreement to adopt Keadle et al.'s standard pathway for testing devices (i.e., benchtop, laboratory, field-based, implementation) without consensus on the prioritization of these steps. Overall, there was enthusiasm not to add prescriptive or regulatory steps, but instead create a networking hub that connects companies to consumers and researchers for flexible guidance navigating the heterogeneity, multi-tiered development, dynamicity, and nebulousness of the CSFW field.
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Affiliation(s)
- Garrett I Ash
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Center for Medical Informatics, Yale University, New Haven, CT, USA
| | - Matthew Stults-Kolehmainen
- Digestive Health Multispecialty Clinic, Yale-New Haven Hospital, New Haven, CT, USA
- Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, NY, USA
| | - Michael A Busa
- Center for Human Health and Performance, Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA, USA
- Department of Kinesiology, University of Massachusetts, Amherst, MA, USA
| | - Allison E Gaffey
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Department of Internal Medicine (Cardiovascular Medicine), Yale School of Medicine, New Haven, CT, USA
| | | | - Borja Muniz-Pardos
- GENUD Research Group, Faculty of Health and Sport Sciences, University of Zaragoza, Zaragoza, Spain
| | - Robert Gregory
- Department of Health and Movement Sciences, Southern Connecticut State University, New Haven, CT, USA
| | - Robert A Huggins
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
| | | | | | | | | | | | - Ioannis Vogiatzis
- Department of Sport, Exercise and Rehabilitation, School Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
- European Respiratory Society (ERS), Digital Health Working Group, Lausanne, Switzerland
| | - LaurieAnn Scher
- Consumer Technology Association Working Groups for Health Technology Standards, Washington, DC, USA
- Fitscript LLC, New Haven, CT, USA
| | - Xinxin Zhu
- Center for Biomedical Data Science, Yale School of Medicine, New Haven, CT, USA
| | - Julien S Baker
- Faculty of Sports Science, Ningbo University, Ningbo, China
- School of Health and Life Sciences, Institute for Clinical Exercise and Health Science, University of the West of Scotland, South Lanarkshire, Scotland, UK
- Department of Sport, Physical Education and Health, Centre for Health and Exercise Science Research, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Cynthia Brandt
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
- Center for Medical Informatics, Yale University, New Haven, CT, USA
- Emergency Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Michael S Businelle
- Department of Family and Preventive Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Tobacco Settlement Endowment Trust Health Promotion Research Center, Stephenson Cancer Center, Oklahoma City, OK, USA
| | - Lisa M Fucito
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Yale Cancer Center, New Haven, CT, USA
- Smilow Cancer Hospital, Yale-New Haven Hospital, New Haven, CT, USA
| | - Stephanie Griggs
- Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, USA
| | - Robert Jarrin
- Department of Emergency Medicine, George Washington University, Washington, DC, USA
- Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC, USA
| | - Bobak J Mortazavi
- Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
| | | | - Walter Roberts
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Elias K Spanakis
- University of Maryland School of Medicine, Baltimore, MD, USA
- Division of Endocrinology, Baltimore Veterans Affairs Medical Center, Maryland, USA
| | - Laura M Nally
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, USA
| | - Andre Debruyne
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- European Federation of Sports Medicine Associations (EFSMA), Lausanne, Switzerland
| | - Norbert Bachl
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- European Federation of Sports Medicine Associations (EFSMA), Lausanne, Switzerland
- Institute of Sports Science, University of Vienna, Vienna, Austria
- Austrian Institute of Sports Medicine, Vienna, Austria
| | - Fabio Pigozzi
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- European Federation of Sports Medicine Associations (EFSMA), Lausanne, Switzerland
- Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Rome, Italy
- Villa Stuart Sport Clinic, FIFA Medical Center of Excellence, Rome, Italy
| | - Farzin Halabchi
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Sports and Exercise Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Dimakatso A Ramagole
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- Section Sports Medicine, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
| | - Dina C Janse van Rensburg
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- Section Sports Medicine, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
| | - Bernd Wolfarth
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- Department of Sports Medicine, Humboldt University and Charité University School of Medicine, Berlin, Germany
| | - Chiara Fossati
- Department of Movement, Human and Health Sciences, University of Rome "Foro Italico", Rome, Italy
| | - Sandra Rozenstoka
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- European Federation of Sports Medicine Associations (EFSMA), Lausanne, Switzerland
- FIMS Collaboration Centre of Sports Medicine, Sports Laboratory, Riga, Latvia
| | - Kumpei Tanisawa
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Japan
| | - Mats Börjesson
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- Department of Molecular and Clinical Medicine, Center for Health and Performance, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden
- Department of MGA, Region of Western Sweden, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - José Antonio Casajus
- GENUD Research Group, Faculty of Health and Sport Sciences, University of Zaragoza, Zaragoza, Spain
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
| | - Alex Gonzalez-Aguero
- GENUD Research Group, Faculty of Health and Sport Sciences, University of Zaragoza, Zaragoza, Spain
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
| | - Irina Zelenkova
- GENUD Research Group, Faculty of Health and Sport Sciences, University of Zaragoza, Zaragoza, Spain
- I.M. Sechenov First Moscow State Medical University (Sechenov University, Ministry of Health of Russia, Moscow, Russia
| | - Jeroen Swart
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland
- Division of Physiological Sciences and HPALS Research Centre, FIMS Collaboration Centre of Sports Medicine, University of Cape Town, Cape Town, South Africa
| | - Gamze Gursoy
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - William Meyerson
- Duke Psychiatry and Behavioral Sciences, Duke Medicine, Durham, NC, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jason Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Dov Greenbaum
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Zvi Meitar Institute for Legal Implications of Emerging Technologies, Interdisciplinary Center Herzliya, Herzliya, Israel
- Harry Radyzner Law School, Interdisciplinary Center Herzliya, Herzliya, Israel
| | - Yannis P Pitsiladis
- Centre for Stress and Age-related Disease, University of Brighton, Brighton, UK.
- International Federation of Sports Medicine (FIMS), Lausanne, Switzerland.
- European Federation of Sports Medicine Associations (EFSMA), Lausanne, Switzerland.
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
- Department of Computer Science, Yale University, New Haven, CT, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA
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35
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Abstract
Eye-tracking and recording of physiological signals are increasingly used in research within cognitive science and human–computer interaction. For example, gaze position and measures of autonomic arousal, including pupil dilation, skin conductance (SC), and heart rate (HR), provide an indicator of cognitive and physiological processes. The growing popularity of these techniques is partially driven by the emergence of low-cost recording equipment and the proliferation of open-source software for data collection and analysis of such signals. However, the use of new technology requires investigation of its reliability and validation with respect to real-world usage and against established technologies. Accordingly, in two experiments (total N = 69), we assessed the Gazepoint GP3-HD eye-tracker and Gazepoint Biometrics (GPB) system from Gazepoint. We show that the accuracy, precision, and robustness of the eye-tracker are comparable to competing systems. While fixation and saccade events can be reliably extracted, the study of saccade kinematics is affected by the low sampling rate. The GP3-HD is also able to capture psychological effects on pupil dilation in addition to the well-defined pupillary light reflex. Finally, moderate-to-strong correlations between physiological recordings and derived metrics of SC and HR between the GPB and the well-established BIOPAC MP160 support its validity. However, low amplitude of the SC signal obtained from the GPB may reduce sensitivity when separating phasic and tonic components. Similarly, data loss in pulse monitoring may pose difficulties for certain HR variability analyses.
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36
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Wan EY, Ghanbari H, Akoum N, Itzhak Attia Z, Asirvatham SJ, Chung EH, Dagher L, Al-Khatib SM, Stuart Mendenhall G, McManus DD, Pathak RK, Passman RS, Peters NS, Schwartzman DS, Svennberg E, Tarakji KG, Turakhia MP, Trela A, Yarmohammadi H, Marrouche NF. HRS White Paper on Clinical Utilization of Digital Health Technology. CARDIOVASCULAR DIGITAL HEALTH JOURNAL 2021; 2:196-211. [PMID: 35265910 PMCID: PMC8890053 DOI: 10.1016/j.cvdhj.2021.07.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
This collaborative statement from the Digital Health Committee of the Heart Rhythm Society provides everyday clinical scenarios in which wearables may be utilized by patients for cardiovascular health and arrhythmia management. We describe herein the spectrum of wearables that are commercially available for patients, and their benefits, shortcomings and areas for technological improvement. Although wearables for rhythm diagnosis and management have not been examined in large randomized clinical trials, undoubtedly the usage of wearables has quickly escalated in clinical practice. This document is the first of a planned series in which we will update information on wearables as they are revised and released to consumers.
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Affiliation(s)
- Elaine Y. Wan
- Division of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, New York-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA
| | | | | | | | | | | | - Lilas Dagher
- Tulane Research Innovation for Arrhythmia Discoveries (TRIAD), Heart and Vascular Institute, Tulane University School of Medicine, New Orleans, LA, USA
| | | | | | | | - Rajeev K. Pathak
- Cardiac Electrophysiology Unit, Department of Cardiology, Canberra Hospital and Health Services, Australian National University, Canberra, Australia
| | - Rod S. Passman
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | | | - Emma Svennberg
- Karolinska Institutet, Department of Medicine Huddinge, Karolinska University Hospital, Stockholm, Sweden
| | - Khaldoun G. Tarakji
- Department of Cardiovascular Medicine, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Mintu P. Turakhia
- Department of Medicine, Stanford University, Stanford, California; Veterans Affairs Palo Alto Health Care System, Palo Alto, California, and Center for Digital Health, Stanford, CA, USA
| | - Anthony Trela
- Lucile Packard Children’s Hospital, Pediatric Cardiology, Palo Alto, CA, USA
| | - Hirad Yarmohammadi
- Division of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, New York-Presbyterian/Columbia University Irving Medical Center, New York, NY, USA
| | - Nassir F. Marrouche
- Tulane Research Innovation for Arrhythmia Discoveries (TRIAD), Heart and Vascular Institute, Tulane University School of Medicine, New Orleans, LA, USA
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37
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Muggeridge DJ, Hickson K, Davies AV, Giggins OM, Megson IL, Gorely T, Crabtree DR. Measurement of Heart Rate Using the Polar OH1 and Fitbit Charge 3 Wearable Devices in Healthy Adults During Light, Moderate, Vigorous, and Sprint-Based Exercise: Validation Study. JMIR Mhealth Uhealth 2021; 9:e25313. [PMID: 33764310 PMCID: PMC8088863 DOI: 10.2196/25313] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 01/08/2021] [Accepted: 02/18/2021] [Indexed: 01/19/2023] Open
Abstract
Background Accurate, continuous heart rate measurements are important for health assessment, physical activity, and sporting performance, and the integration of heart rate measurements into wearable devices has extended its accessibility. Although the use of photoplethysmography technology is not new, the available data relating to the validity of measurement are limited, and the range of activities being performed is often restricted to one exercise domain and/or limited intensities. Objective The primary objective of this study was to assess the validity of the Polar OH1 and Fitbit Charge 3 devices for measuring heart rate during rest, light, moderate, vigorous, and sprint-type exercise. Methods A total of 20 healthy adults (9 female; height: mean 1.73 [SD 0.1] m; body mass: mean 71.6 [SD 11.0] kg; and age: mean 40 [SD 10] years) volunteered and provided written informed consent to participate in the study consisting of 2 trials. Trial 1 was split into 3 components: 15-minute sedentary activities, 10-minute cycling on a bicycle ergometer, and incremental exercise test to exhaustion on a motorized treadmill (18-42 minutes). Trial 2 was split into 2 components: 4 × 15-second maximal sprints on a cycle ergometer and 4 × 30- to 50-m sprints on a nonmotorized resistance treadmill. Data from the 3 devices were time-aligned, and the validity of Polar OH1 and Fitbit Charge 3 was assessed against Polar H10 (criterion device). Validity was evaluated using the Bland and Altman analysis, Pearson moment correlation coefficient, and mean absolute percentage error. Results Overall, there was a very good correlation between the Polar OH1 and Polar H10 devices (r=0.95), with a mean bias of −1 beats·min-1 and limits of agreement of −20 to 19 beats·min-1. The Fitbit Charge 3 device underestimated heart rate by 7 beats·min-1 compared with Polar H10, with a limit of agreement of −46 to 33 beats·min-1 and poor correlation (r=0.8). The mean absolute percentage error for both devices was deemed acceptable (<5%). Polar OH1 performed well across each phase of trial 1; however, validity was worse for trial 2 activities. Fitbit Charge 3 performed well only during rest and nonsprint-based treadmill activities. Conclusions Compared with our criterion device, Polar OH1 was accurate at assessing heart rate, but the accuracy of Fitbit Charge 3 was generally poor. Polar OH1 performed worse during trial 2 compared with the activities in trial 1, and the validity of the Fitbit Charge 3 device was particularly poor during our cycling exercises.
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Affiliation(s)
| | - Kirsty Hickson
- Division of Biomedical Sciences, University of the Highlands and Islands, Inverness, United Kingdom
| | - Aimie Victoria Davies
- Department of Nursing and Midwifery, University of the Highlands and Islands, Inverness, United Kingdom
| | - Oonagh M Giggins
- NetwellCASALA, Dundalk Institute of Technology, Dundalk, Ireland
| | - Ian L Megson
- Division of Biomedical Sciences, University of the Highlands and Islands, Inverness, United Kingdom
| | - Trish Gorely
- Department of Nursing and Midwifery, University of the Highlands and Islands, Inverness, United Kingdom
| | - Daniel R Crabtree
- Division of Biomedical Sciences, University of the Highlands and Islands, Inverness, United Kingdom
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