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Gong XY, Cheng J, Wu YT, He F, Wang SH, Liu CY, Zhu Y, Xu KH. Effectiveness of home-based cardiac telerehabilitation based on wearable ECG or heart rate monitoring devices in patients with heart disease: A meta-analysis of randomized controlled trials. Geriatr Nurs 2024; 58:238-246. [PMID: 38838406 DOI: 10.1016/j.gerinurse.2024.05.036] [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: 01/16/2024] [Revised: 05/19/2024] [Accepted: 05/24/2024] [Indexed: 06/07/2024]
Abstract
OBJECTIVE To evaluate the effectiveness of home-based cardiac telerehabilitation based on wearable electrocardiogram or heart rate monitoring devices in patients with heart disease. METHODS We searched eight electronic databases under the guidance of Cochrane Handbook and PRISMA recommendations. RESULTS The meta-analysis included data from 14 articles (15 RCTs) representing 1314 participants. A significant improvement in left ventricular ejection fraction [MD = 2.12, 95 % CI (1.21, 3.04), P < 0.001], 6-minute walk distance [MD = 40.00, 95 % CI (21.72, 58.29), P < 0.001] and peak oxygen intake [MD = 2.24, 95 % CI (1.38, 3.10), P < 0.001] were observed in the home-based cardiac telerehabilitation group. But it had no difference in anxiety [SMD = -0.83, 95 % CI (-1.65, -0.02), P = 0.05] and depression [SMD = -0.59, 95 % CI (-1.26, 0.09), P = 0.09]. Subgroup analyses revealed that interventions of no less than 3 months improved anxiety [SMD = -1.11, 95 % CI (-2.05, -0.18), P = 0.02] and depression [SMD = -1.01, 95 % CI (-1.93, -0.08), P = 0.03]. CONCLUSION Home-based cardiac telerehabilitation based on wearable electrocardiogram or heart rate monitoring devices has a positive effect on cardiac function. Long-term (≥ 3 months) cardiac rehabilitation might benefit individuals suffering from anxiety or depression.
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Affiliation(s)
- Xin-Yue Gong
- School of Nursing, Anhui University of Chinese Medicine, Hefei, China
| | - Jing Cheng
- School of Nursing, Anhui University of Chinese Medicine, Hefei, China.
| | - Ying-Ting Wu
- School of Nursing, Anhui University of Chinese Medicine, Hefei, China
| | - Fei He
- Department of Cardiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Si-Han Wang
- School of Nursing, Anhui University of Chinese Medicine, Hefei, China
| | - Chang-Yi Liu
- School of Nursing, Anhui University of Chinese Medicine, Hefei, China
| | - Ying Zhu
- School of Nursing, Anhui University of Chinese Medicine, Hefei, China
| | - Ke-Hui Xu
- The Second Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China
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2
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Rockette-Wagner B, Aggarwal R. A review of the evidence for the utility of physical activity monitor use in patients with idiopathic inflammatory myopathies. Rheumatology (Oxford) 2024; 63:1815-1824. [PMID: 38243707 DOI: 10.1093/rheumatology/keae004] [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: 09/19/2023] [Revised: 11/13/2023] [Accepted: 12/13/2023] [Indexed: 01/21/2024] Open
Abstract
Few proven therapies exist for patients with idiopathic inflammatory myopathies (IIMs), partly due to the lack of reliable and valid outcome measures for assessing treatment responses. The current core set measures developed by the International Myositis Assessment and Clinical Studies group were developed to standardize assessments of disease activity and treatment effect. None of the current measures address functional improvement in muscle weakness. Therefore, supplemental measures to more objectively assess physical activity levels and fatiguability in free-living settings are needed to assess disease activity more comprehensively. Validated physical activity monitors (PAMs) have the potential to serve as an objective functional outcome measure in clinical trials and observational studies. This review examines the current evidence for the use of body-worn PAMs in clinical settings with IIM patients. A practical overview of methods for PAM use in clinical patient populations (including measurement details and data processing) that focuses on IIM patients is also presented.
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Affiliation(s)
- Bonny Rockette-Wagner
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA
| | - Rohit Aggarwal
- Division of Rheumatology and Clinical Immunology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
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Ørbæk Andersen M, Carlsen J. Continuous heart monitoring in patients with pulmonary hypertension smartwatches and direct transmission to their electronic health records: A trial design. Contemp Clin Trials 2024; 142:107548. [PMID: 38679139 DOI: 10.1016/j.cct.2024.107548] [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: 01/16/2024] [Revised: 04/10/2024] [Accepted: 04/25/2024] [Indexed: 05/03/2024]
Abstract
BACKGROUND Pulmonary hypertension is a progressive disease for which early treatment interventions are essential. Traditionally, patients undergo periodic clinical assessments. However, recent advances in wearable technology could improve the quality and efficiency of follow-up monitoring in patients with pulmonary hypertension. TRIAL DESIGN To our knowledge, this is the first study describing direct data transmission from a smartwatch to patients' electronic health records. It implements a novel update and customised program to continuously and automatically transmit data from a smartwatch to the patient's electronic healthcare records. It will evaluate continuous monitoring in patients with pulmonary hypertension and monitor their physical activity time, heart rate variability, and heart rate at rest and during physical activity via a smartwatch. It will also evaluate the data transmission method, and its data will be assessed by the treating physicians supplemental to clinical practice. Smartwatch integration promises numerous advantages: comprehensive cardiovascular monitoring and improved patient experience. Our continuous smartwatch monitoring approach offers a solution for earlier detection of clinical worsening and could be included as a combined endpoint in future clinical trials. It could improve patient empowerment, enhance precision medicine, and reduce hospitalisations. The user-friendly smartwatch is designed to minimise disruption in daily life. CONCLUSION The ability to transfer real-time data from wearable devices to electronic health records could help to transform the treatment of patients with pulmonary hypertension and their follow-up monitoring outside a clinical setting, enhancing the efficiency of healthcare delivery.
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Affiliation(s)
- Mads Ørbæk Andersen
- Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark
| | - Jørn Carlsen
- Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Blegdamsvej 9, Copenhagen 2100, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, Copenhagen 2200, Denmark.
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Chimatapu SN, Mittelman SD, Habib M, Osuna-Garcia A, Vidmar AP. Wearable Devices Beyond Activity Trackers in Youth With Obesity: Summary of Options. Child Obes 2024; 20:208-218. [PMID: 37023409 PMCID: PMC10979694 DOI: 10.1089/chi.2023.0005] [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] [Indexed: 04/08/2023]
Abstract
Background: Current treatment protocols to prevent and treat pediatric obesity focus on prescriptive lifestyle interventions. However, treatment outcomes are modest due to poor adherence and heterogeneity in responses. Wearable technologies offer a unique solution as they provide real-time biofeedback that could improve adherence to and sustainability of lifestyle interventions. To date, all reviews on wearable devices in pediatric obesity cohorts have only explored biofeedback from physical activity trackers. Hence, we conducted a scoping review to (1) catalog other biofeedback wearable devices available in this cohort, (2) document various metrics collected from these devices, and (3) assess safety and adherence to these devices. Methods: This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Fifteen eligible studies examined the use of biofeedback wearable devices beyond activity trackers in pediatric cohorts, with an emphasis on feasibility of these devices. Results: Included studies varied in sample sizes (15-203) and in ages 6-21 years. Wearable devices are being used to capture various metrics of multicomponent weight loss interventions to provide more insights about glycemic variability, cardiometabolic function, sleep, nutrition, and body fat percentage. High safety and adherence rates were reported among these devices. Conclusions: Available evidence suggests that wearable devices have several applications aside from activity tracking, which could modify health behaviors through real-time biofeedback. Overall, these devices appear to be safe and feasible so as to be employed in various settings in the pediatric age group to prevent and treat obesity.
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Affiliation(s)
- Sri Nikhita Chimatapu
- Division of Endocrinology, Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Steven D. Mittelman
- Division of Endocrinology, Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Manal Habib
- Division of Endocrinology, Department of Pediatrics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Antonia Osuna-Garcia
- Department of Health and Life Sciences Librarian, Nursing, Biomedical Library, University of California Los Angeles, Los Angeles, CA, USA
| | - Alaina P. Vidmar
- Center for Endocrinology, Diabetes, and Metabolism, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
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Khushhal AA, Mohamed AA, Elsayed ME. Accuracy of Apple Watch to Measure Cardiovascular Indices in Patients with Chronic Diseases: A Cross Sectional Study. J Multidiscip Healthc 2024; 17:1053-1063. [PMID: 38496326 PMCID: PMC10941792 DOI: 10.2147/jmdh.s449071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 03/04/2024] [Indexed: 03/19/2024] Open
Abstract
Background The validity of the Apple Watch to measure the heart rate (HR) and oxygen saturation (Spo2) for patients with chronic diseases such as diabetes mellitus (DM), dyslipidemia, and hypertension is still unclear. Therefore, this study aims to investigate the accuracy of the Apple Watch in measuring the Spo2 and HR in patients with chronic diseases. Methods Forty-one patients with chronic diseases, including 20 with hypertension, 10 with diabetes, and 11 with dyslipidemia, completed a cross-sectional study. All participants used the Apple Watch against the Polar chest strap and the pulse oximeter at rest and during moderate intensity exercise sessions to measure HR and the SpO2 at rest for 5 minutes, during exercise for 16 minutes, and followed by 3 minutes of rest. The HR was measured during all previous periods, but evaluation of the Spo2 included 5 measures, done only before and after exercise, with a minute interval between each measure. Results Overall, a strong correlation exists between measuring the SpO2 using the Apple Watch against the pulse oximeter (Contec) at rest (r = 0.92, p < 0.001) and after exercise (r = 0.86, p < 0.001) in all patients. The HR had a very strong correlation between the Apple Watch and the Polar chest strap (r = 0.99, p < 0.001) in all patients. There was no significant difference (p = 0.76) between the twenty-seven white and fourteen brown-skinned patients. Conclusion The Apple Watch is valid to measure the HR and SpO2 in patients with chronic diseases. Clinical Trial Registration No NCT05271864.
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Affiliation(s)
- Alaa Abdulhafiz Khushhal
- Department of Medical Rehabilitation Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Ashraf Abdelaal Mohamed
- Department of Medical Rehabilitation Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
- Department of Physical Therapy for Cardiovascular/ Respiratory Disorder and Geriatrics, Faculty of Physical Therapy, Cairo University, Cairo, Egypt
| | - Mahmoud Elshahat Elsayed
- Cardiology Department, Umm Al-Qura University Medical Center, Umm Al-Qura University, Makkah, Saudi Arabia
- Cardiology Department, Faculty of Medicine, Al Azhar University, Cairo, Egypt
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Pandit JA, Pawelek JB, Leff B, Topol EJ. The hospital at home in the USA: current status and future prospects. NPJ Digit Med 2024; 7:48. [PMID: 38413704 PMCID: PMC10899639 DOI: 10.1038/s41746-024-01040-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 02/14/2024] [Indexed: 02/29/2024] Open
Abstract
The annual cost of hospital care services in the US has risen to over $1 trillion despite relatively worse health outcomes compared to similar nations. These trends accentuate a growing need for innovative care delivery models that reduce costs and improve outcomes. HaH-a program that provides patients acute-level hospital care at home-has made significant progress over the past two decades. Technological advancements in remote patient monitoring, wearable sensors, health information technology infrastructure, and multimodal health data processing have contributed to its rise across hospitals. More recently, the COVID-19 pandemic brought HaH into the mainstream, especially in the US, with reimbursement waivers that made the model financially acceptable for hospitals and payors. However, HaH continues to face serious challenges to gain widespread adoption. In this review, we evaluate the peer-reviewed evidence and discuss the promises, challenges, and what it would take to tap into the future potential of HaH.
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Affiliation(s)
- Jay A Pandit
- Scripps Translational Research Institute, Scripps Research, La Jolla, CA, USA.
| | - Jeff B Pawelek
- Scripps Translational Research Institute, Scripps Research, La Jolla, CA, USA
| | - Bruce Leff
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Eric J Topol
- Scripps Translational Research Institute, Scripps Research, La Jolla, CA, USA
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Tran T, Steiner JM, Venkateswaran A, Buber J. Peak oxygen consumption by smartwatches compared with cardiopulmonary exercise test in complex congenital heart disease. Heart 2024; 110:353-358. [PMID: 37827554 DOI: 10.1136/heartjnl-2023-322989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 09/21/2023] [Indexed: 10/14/2023] Open
Abstract
OBJECTIVE To evaluate for correlation between exercise capacity as assessed by peak oxygen consumption (pVO2) measurement during a cardiopulmonary exercise test (CPET) and smartwatches reporting this parameter in patients with adult congenital heart disease (ACHD) complex lesions. METHODS A prospective study that included patients with ACHD either a Fontan circulation or a right ventricle supporting the systemic circulation who underwent two separate CPETs at least 1 year apart. Generalised estimating equations linear regression was performed to identify factors associated with correlation between smartwatch and CPET-derived pVO2. RESULTS 48 patients (71% with a Fontan circulation, 42% females, mean age 33±9 years) underwent two CPETs between May 2018 and May 2022 with echocardiograms performed within 6 months of each CPET. Apple Watch was the predominant smartwatch used (79%). Smartwatch and CPET measured peak heart rate (Pearson correlation=0.932, 95% CI (0.899, 0.954)) and pVO2 (0.8627, 95% CI (0.8007, 0.9064) and 0.8634, 95% CI (0.7676, 0.9215) in the first and second CPET, respectively) correlated well, with smartwatch-measured pVO2 values measuring higher by a mean of 3.146 mL/kg/min (95% CI (2.559, 3.732)). Changes in pVO2 between the first and the second CPET also correlated well (Pearson correlation=0.9165, 95% CI (0.8549, 0.9525)), indicating that for every 1 mL/(min kg) change in CPET-measured pVO2, there was a corresponding 0.896 mL/(min kg) change in the smartwatch-measured pVO2. CONCLUSION Both absolute values and changes over time in pVO2 as measured by smartwatches and CPETs correlate well in patients with complex ACHD.
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Affiliation(s)
- Tomio Tran
- Medicine, Division of Cardiology, University of Washington, Seattle, Washington, USA
| | - Jill Marie Steiner
- Medicine, Division of Cardiology, University of Washington, Seattle, Washington, USA
| | | | - Jonathan Buber
- Medicine, Division of Cardiology, University of Washington, Seattle, Washington, USA
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Adil M, Atiq I, Younus S. Effectiveness of the Apple Watch as a mental health tracker. J Glob Health 2024; 14:03010. [PMID: 38332682 PMCID: PMC10853680 DOI: 10.7189/jogh.14.03010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024] Open
Affiliation(s)
- Mariam Adil
- Department of Internal Medicine, Dow University of Health Sciences, Karachi, Pakistan
| | - Isha Atiq
- Department of Internal Medicine, Dow University of Health Sciences, Karachi, Pakistan
| | - Sumaiya Younus
- Institute of Professional Psychology, Bahria University, Karachi, Pakistan
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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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Shrestha AB, Khanal B, Mainali N, Shrestha S, Chapagain S, Umar TP, Jaiswal V. Navigating the Role of Smartwatches in Cardiac Fitness Monitoring: Insights From Physicians and the Evolving Landscape. Curr Probl Cardiol 2024; 49:102073. [PMID: 37689377 DOI: 10.1016/j.cpcardiol.2023.102073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 08/31/2023] [Accepted: 09/04/2023] [Indexed: 09/11/2023]
Abstract
Alongside the advancement of technology, wearable devices like smartwatches have widely been used for monitoring heartbeat, SpO2, EKG, and pacemaker activity. However, the global question is- can they be as effective as our standard diagnostic tests- electrocardiogram and echocardiography? Reported in the studies, smartwatches to the gold standard Holter monitoring for recognizing irregular pulse showed good sensitivity (98.2%), specificity (98.1%), and accuracy (98.1%). Smartwatches can be good enough for helping people get long-term monitoring of cardiac fitness and early diagnosis of atrial fibrillation but physicians shouldn't completely rely on them and perform standard investigations once the patient with symptoms visits them. We are also concerned that there must be certain rules and regulations for FDA approval of smartwatches to maintain standard criteria before they are released in the market.
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Affiliation(s)
| | | | - Nischal Mainali
- Kathmandu Medical College and Teaching Hospital, Sinamangal, Kathmandu, Nepal
| | | | - Sanskriti Chapagain
- Devdaha Medical College and Research Institiute Pvt. Ltd, Devdaha, Rupandehi, Nepal
| | - Tungki Pratama Umar
- UCL Centre for Nanotechnology and Regenerative Medicine, Division of Surgery and Interventional Science, University College London, London, UK
| | - Vikash Jaiswal
- Department of Research and Academic Affairs, Larkin Community Hospital, South Miami, FL
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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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Thomas M, Boursalie O, Samavi R, Doyle TE. Data-driven approach to quantify trust in medical devices using Bayesian networks. Exp Biol Med (Maywood) 2023; 248:2578-2592. [PMID: 38281083 PMCID: PMC10854471 DOI: 10.1177/15353702231215893] [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] [Subscribe] [Scholar Register] [Indexed: 01/29/2024] Open
Abstract
Bayesian networks are increasingly used to quantify the uncertainty of subjective and stochastic concepts such as trust. In this article, we propose a data-driven approach to estimate Bayesian parameters in the domain of wearable medical devices. Our approach extracts the probability of a trust factor being in a specific state directly from the devices (e.g. sensor quality). The strength of the relationship between related factors is defined by expert knowledge and incorporated into the model. We use propagation rules from requirements engineering to estimate how much each trust factor contributes to the related intermediate nodes in the network and ultimately compute the trust score. The trust score is a relative measure of trustworthiness when different devices are evaluated in the same test conditions and using the same Bayesian structure. To evaluate our approach, we developed Bayesian networks for the trust quantification of similar wearable devices from two manufacturers under identical test conditions and noise levels. The results demonstrated the learnability and generalizability of our approach.
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Affiliation(s)
- Mini Thomas
- Department of Computing and Software, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Omar Boursalie
- Department of Electrical and Computer Engineering, Toronto Metropolitan University, ON M5B 2K3, Canada
| | - Reza Samavi
- Department of Electrical and Computer Engineering, Toronto Metropolitan University, ON M5B 2K3, Canada
- Vector Institute, Toronto, ON M5G 1M1, Canada
| | - Thomas E Doyle
- Vector Institute, Toronto, ON M5G 1M1, Canada
- Department of Electrical & Computer Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
- School of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
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13
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Montanari A, Ferlini A, Balaji AN, Mascolo C, Kawsar F. EarSet: A Multi-Modal Dataset for Studying the Impact of Head and Facial Movements on In-Ear PPG Signals. Sci Data 2023; 10:850. [PMID: 38040725 PMCID: PMC10692189 DOI: 10.1038/s41597-023-02762-3] [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: 03/09/2023] [Accepted: 11/17/2023] [Indexed: 12/03/2023] Open
Abstract
Photoplethysmography (PPG) is a simple, yet powerful technique to study blood volume changes by measuring light intensity variations. However, PPG is severely affected by motion artifacts, which hinder its trustworthiness. This problem is pressing in earables since head movements and facial expressions cause skin and tissue displacements around and inside the ear. Understanding such artifacts is fundamental to the success of earables for accurate cardiovascular health monitoring. However, the lack of in-ear PPG datasets prevents the research community from tackling this challenge. In this work, we report on the design of an ear tip featuring a 3-channels PPG and a co-located 6-axis motion sensor. This, enables sensing PPG data at multiple wavelengths and the corresponding motion signature from both ears. Leveraging our device, we collected a multi-modal dataset from 30 participants while performing 16 natural motions, including both head/face and full body movements. This unique dataset will greatly support research towards making in-ear vital signs sensing more accurate and robust, thus unlocking the full potential of the next-generation PPG-equipped earables.
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Affiliation(s)
| | - Andrea Ferlini
- Nokia Bell Labs, Cambridge, UK.
- University of Cambridge, Cambridge, UK.
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14
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Dang T, Spathis D, Ghosh A, Mascolo C. Human-centred artificial intelligence for mobile health sensing: challenges and opportunities. ROYAL SOCIETY OPEN SCIENCE 2023; 10:230806. [PMID: 38026044 PMCID: PMC10646451 DOI: 10.1098/rsos.230806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 10/23/2023] [Indexed: 12/01/2023]
Abstract
Advances in wearable sensing and mobile computing have enabled the collection of health and well-being data outside of traditional laboratory and hospital settings, paving the way for a new era of mobile health. Meanwhile, artificial intelligence (AI) has made significant strides in various domains, demonstrating its potential to revolutionize healthcare. Devices can now diagnose diseases, predict heart irregularities and unlock the full potential of human cognition. However, the application of machine learning (ML) to mobile health sensing poses unique challenges due to noisy sensor measurements, high-dimensional data, sparse and irregular time series, heterogeneity in data, privacy concerns and resource constraints. Despite the recognition of the value of mobile sensing, leveraging these datasets has lagged behind other areas of ML. Furthermore, obtaining quality annotations and ground truth for such data is often expensive or impractical. While recent large-scale longitudinal studies have shown promise in leveraging wearable sensor data for health monitoring and prediction, they also introduce new challenges for data modelling. This paper explores the challenges and opportunities of human-centred AI for mobile health, focusing on key sensing modalities such as audio, location and activity tracking. We discuss the limitations of current approaches and propose potential solutions.
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Affiliation(s)
- Ting Dang
- University of Cambridge, Cambridge, UK
- Nokia Bell Labs, Cambridge, UK
| | - Dimitris Spathis
- University of Cambridge, Cambridge, UK
- Nokia Bell Labs, Cambridge, UK
| | - Abhirup Ghosh
- University of Cambridge, Cambridge, UK
- University of Birmingham, Birmingham, UK
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15
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Yamada K, Enokida Y, Kato R, Imaizumi J, Takada T, Ojima H. The Feasibility and Reliability of Upper Arm-Worn Apple Watch Heart Rate Monitoring for Surgeons During Surgery: Observational Study. JMIR Hum Factors 2023; 10:e50891. [PMID: 37910162 PMCID: PMC10652190 DOI: 10.2196/50891] [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: 07/16/2023] [Revised: 09/05/2023] [Accepted: 09/23/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND Health care professionals, particularly those in surgical settings, face high stress levels, impacting their well-being. Traditional monitoring methods, like using Holter electrocardiogram monitors, are impractical in the operating room, limiting the assessment of physicians' health. Wrist-worn heart rate monitors, like the Apple Watch, offer promise but are restricted in surgeries due to sterility issues. OBJECTIVE This study aims to assess the feasibility and accuracy of using an upper arm-worn Apple Watch for heart rate monitoring during robotic-assisted surgeries, comparing its performance with that of a wrist-worn device to establish a reliable alternative monitoring site. METHODS This study used 2 identical Apple Watch Series 8 devices to monitor the heart rate of surgeons during robotic-assisted surgery. Heart rate data were collected from the wrist-worn and the upper arm-worn devices. Statistical analyses included calculating the mean difference and SD of difference between the 2 devices, constructing Bland-Altman plots, assessing accuracy based on mean absolute error and mean absolute percentage error, and calculating the intraclass correlation coefficient. RESULTS The mean absolute errors for the whole group and for participants A, B, C, and D were 3.63, 3.58, 2.70, 3.93, and 4.28, respectively, and the mean absolute percentage errors were 3.58%, 3.34%, 2.42%, 4.58%, and 4.00%, respectively. Bland-Altman plots and scatter plots showed no systematic error when comparing the heart rate measurements obtained from the upper arm-worn and the wrist-worn Apple Watches. The intraclass correlation coefficients for participants A, B, C, and D were 0.559, 0.651, 0.508, and 0.563, respectively, with a significance level of P<.001, indicating moderate reliability. CONCLUSIONS The findings of this study suggest that the upper arm is a viable alternative site for monitoring heart rate during surgery using an Apple Watch. The agreement and reliability between the measurements obtained from the upper arm-worn and the wrist-worn devices were good, with no systematic error and a high level of accuracy. These findings have important implications for improving data collection and management of the physical and mental demands of operating room staff during surgery, where wearing a watch on the wrist may not be feasible.
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Affiliation(s)
- Kazunosuke Yamada
- Department of Gastroenterological Surgery, Gunma Prefectural Cancer Center, Oota City, Gunma, Japan
| | - Yasuaki Enokida
- Department of Gastroenterological Surgery, Gunma Prefectural Cancer Center, Oota City, Gunma, Japan
| | - Ryuji Kato
- Department of Gastroenterological Surgery, Gunma Prefectural Cancer Center, Oota City, Gunma, Japan
| | - Jun Imaizumi
- Department of Gastroenterological Surgery, Gunma Prefectural Cancer Center, Oota City, Gunma, Japan
| | - Takahiro Takada
- Department of Gastroenterological Surgery, Gunma Prefectural Cancer Center, Oota City, Gunma, Japan
| | - Hitoshi Ojima
- Department of Gastroenterological Surgery, Gunma Prefectural Cancer Center, Oota City, Gunma, Japan
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16
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Sanal-Hayes NEM, Mclaughlin M, Hayes LD, Mair JL, Ormerod J, Carless D, Hilliard N, Meach R, Ingram J, Sculthorpe NF. A scoping review of 'Pacing' for management of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): lessons learned for the long COVID pandemic. J Transl Med 2023; 21:720. [PMID: 37838675 PMCID: PMC10576275 DOI: 10.1186/s12967-023-04587-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 10/03/2023] [Indexed: 10/16/2023] Open
Abstract
BACKGROUND Controversy over treatment for people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a barrier to appropriate treatment. Energy management or pacing is a prominent coping strategy for people with ME/CFS. Whilst a definitive definition of pacing is not unanimous within the literature or healthcare providers, it typically comprises regulating activity to avoid post exertional malaise (PEM), the worsening of symptoms after an activity. Until now, characteristics of pacing, and the effects on patients' symptoms had not been systematically reviewed. This is problematic as the most common approach to pacing, pacing prescription, and the pooled efficacy of pacing was unknown. Collating evidence may help advise those suffering with similar symptoms, including long COVID, as practitioners would be better informed on methodological approaches to adopt, pacing implementation, and expected outcomes. OBJECTIVES In this scoping review of the literature, we aggregated type of, and outcomes of, pacing in people with ME/CFS. ELIGIBILITY CRITERIA Original investigations concerning pacing were considered in participants with ME/CFS. SOURCES OF EVIDENCE Six electronic databases (PubMed, Scholar, ScienceDirect, Scopus, Web of Science and the Cochrane Central Register of Controlled Trials [CENTRAL]) were searched; and websites MEPedia, Action for ME, and ME Action were also searched for grey literature, to fully capture patient surveys not published in academic journals. METHODS A scoping review was conducted. Review selection and characterisation was performed by two independent reviewers using pretested forms. RESULTS Authors reviewed 177 titles and abstracts, resulting in 17 included studies: three randomised control trials (RCTs); one uncontrolled trial; one interventional case series; one retrospective observational study; two prospective observational studies; four cross-sectional observational studies; and five cross-sectional analytical studies. Studies included variable designs, durations, and outcome measures. In terms of pacing administration, studies used educational sessions and diaries for activity monitoring. Eleven studies reported benefits of pacing, four studies reported no effect, and two studies reported a detrimental effect in comparison to the control group. CONCLUSIONS Highly variable study designs and outcome measures, allied to poor to fair methodological quality resulted in heterogenous findings and highlights the requirement for more research examining pacing. Looking to the long COVID pandemic, our results suggest future studies should be RCTs utilising objectively quantified digitised pacing, over a longer duration of examination (i.e. longitudinal studies), using the core outcome set for patient reported outcome measures. Until these are completed, the literature base is insufficient to inform treatment practises for people with ME/CFS and long COVID.
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Affiliation(s)
- Nilihan E M Sanal-Hayes
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, UK
- School of Health and Society, University of Salford, Salford, UK
| | - Marie Mclaughlin
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, UK
- School of Sport, Exercise & Rehabilitation Sciences, University of Hull, Hull, UK
| | - Lawrence D Hayes
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, UK
| | - 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.
| | - Jane Ormerod
- Long COVID Scotland, 12 Kemnay Place, Aberdeen, UK
| | - David Carless
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, UK
| | | | - Rachel Meach
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, UK
| | - Joanne Ingram
- School of Education and Social Sciences, University of the West of Scotland, Glasgow, UK
| | - Nicholas F Sculthorpe
- Sport and Physical Activity Research Institute, School of Health and Life Sciences, University of the West of Scotland, Glasgow, UK
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Qureshi FM, Golan R, Ghomeshi A, Ramasamy R. An Update on the Use of Wearable Devices in Men's Health. World J Mens Health 2023; 41:785-795. [PMID: 36792091 PMCID: PMC10523121 DOI: 10.5534/wjmh.220205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 12/02/2022] [Accepted: 12/12/2022] [Indexed: 02/01/2023] Open
Abstract
Men's health represents an often-overlooked aspect of public health. Men have higher mortality rates worldwide and are more negatively affected by chronic conditions such as obesity and heart disease, as well as addiction to alcohol and tobacco. Men also have health issues such as prostate cancer and male sexual dysfunction which only affect them. Because of the skewed burden of morbidity and mortality on men, it is imperative from a public health perspective to make a concerted effort to specifically improve men's health. The use of wearable devices in medical practice presents a novel avenue to invest in men's health in a safe, easily scalable, and economic fashion. Wearable devices are now ubiquitous in society, and their use in the healthcare setting is only increasing with time. There are commercially available devices such as smart watches which are available to lay people and healthcare professionals alike to improve overall health and wellness, and there are also purpose-built wearable devices which are used to track or treat a specific disease. In our review of the literature, we found that while research in the field of wearable devices is still in its early stages, there is ample evidence that wearable devices can greatly improve men's health in the long-term.
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Affiliation(s)
- Farhan M Qureshi
- Desai Sethi Urology Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
- Medical Scientist Training Program, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Roei Golan
- Department of Clinical Sciences, Florida State University College of Medicine, Tallahassee, FL, USA
| | - Armin Ghomeshi
- Department of Urology, Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
| | - Ranjith Ramasamy
- Desai Sethi Urology Institute, Miller School of Medicine, University of Miami, Miami, FL, USA.
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18
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Brandenbarg P, Hoekstra F, Barakou I, Seves BL, Hettinga FJ, Hoekstra T, van der Woude LHV, Dekker R, Krops LA. Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review. BMC Sports Sci Med Rehabil 2023; 15:115. [PMID: 37735403 PMCID: PMC10512652 DOI: 10.1186/s13102-023-00717-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 08/22/2023] [Indexed: 09/23/2023]
Abstract
BACKGROUND People with physical disabilities and/or chronic diseases tend to have an inactive lifestyle. Monitoring physical activity levels is important to provide insight on how much and what types of activities people with physical disabilities and/or chronic diseases engage in. This information can be used as input for interventions to promote a physically active lifestyle. Therefore, valid and reliable physical activity measurement instruments are needed. This scoping review aims 1) to provide a critical mapping of the existing literature and 2) directions for future research on measurement properties of device-based instruments assessing physical activity behavior in ambulant adults with physical disabilities and/or chronic diseases. METHODS Four databases (MEDLINE, CINAHL, Web of Science, Embase) were systematically searched from 2015 to April 16th 2023 for articles investigating measurement properties of device-based instruments assessing physical activity in ambulatory adults with physical disabilities and/or chronic diseases. For the majority, screening and selection of eligible studies were done in duplicate. Extracted data were publication data, study data, study population, device, studied measurement properties and study outcome. Data were synthesized per device. RESULTS One hundred three of 21566 Studies were included. 55 Consumer-grade and 23 research-grade devices were studied on measurement properties, using 14 different physical activity outcomes, in 23 different physical disabilities and/or chronic diseases. ActiGraph (n = 28) and Fitbit (n = 39) devices were most frequently studied. Steps (n = 68) was the most common used physical activity outcome. 97 studies determined validity, 11 studies reliability and 6 studies responsiveness. CONCLUSION This scoping review shows a large variability in research on measurement properties of device-based instruments in ambulatory adults with physical disabilities and/or chronic diseases. The variability highlights a need for standardization of and consensus on research in this field. The review provides directions for future research.
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Affiliation(s)
- Pim Brandenbarg
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands.
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands.
| | - Femke Hoekstra
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
- School of Health and Exercise Sciences, University of British Columbia Okanagan, Kelowna, BC, V1V 1V7, Canada
| | - Ioulia Barakou
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Bregje L Seves
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Florentina J Hettinga
- Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle, NE1 8ST, UK
| | - Trynke Hoekstra
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
- Department of Health Sciences and Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, 1081 BT, The Netherlands
| | - Lucas H V van der Woude
- Department of Human Movement Sciences, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Rienk Dekker
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
| | - Leonie A Krops
- Department of Rehabilitation Medicine, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB, The Netherlands
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Ye X, Sun M, Yu S, Yang J, Liu Z, Lv H, Wu B, He J, Wang X, Huang L. Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study. JMIR Mhealth Uhealth 2023; 11:e43340. [PMID: 37410528 PMCID: PMC10360014 DOI: 10.2196/43340] [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: 10/09/2022] [Revised: 12/11/2022] [Accepted: 06/09/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Cardiorespiratory fitness plays an important role in coping with hypoxic stress at high altitudes. However, the association of cardiorespiratory fitness with the development of acute mountain sickness (AMS) has not yet been evaluated. Wearable technology devices provide a feasible assessment of cardiorespiratory fitness, which is quantifiable as maximum oxygen consumption (VO2max) and may contribute to AMS prediction. OBJECTIVE We aimed to determine the validity of VO2max estimated by the smartwatch test (SWT), which can be self-administered, in order to overcome the limitations of clinical VO2max measurements. We also aimed to evaluate the performance of a VO2max-SWT-based model in predicting susceptibility to AMS. METHODS Both SWT and cardiopulmonary exercise test (CPET) were performed for VO2max measurements in 46 healthy participants at low altitude (300 m) and in 41 of them at high altitude (3900 m). The characteristics of the red blood cells and hemoglobin levels in all the participants were analyzed by routine blood examination before the exercise tests. The Bland-Altman method was used for bias and precision assessment. Multivariate logistic regression was performed to analyze the correlation between AMS and the candidate variables. A receiver operating characteristic curve was used to evaluate the efficacy of VO2max in predicting AMS. RESULTS VO2max decreased after acute high altitude exposure, as measured by CPET (25.20 [SD 6.46] vs 30.17 [SD 5.01] at low altitude; P<.001) and SWT (26.17 [SD 6.71] vs 31.28 [SD 5.17] at low altitude; P<.001). Both at low and high altitudes, VO2max was slightly overestimated by SWT but had considerable accuracy as the mean absolute percentage error (<7%) and mean absolute error (<2 mL·kg-1·min-1), with a relatively small bias compared with VO2max-CPET. Twenty of the 46 participants developed AMS at 3900 m, and their VO2max was significantly lower than that of those without AMS (CPET: 27.80 [SD 4.55] vs 32.00 [SD 4.64], respectively; P=.004; SWT: 28.00 [IQR 25.25-32.00] vs 32.00 [IQR 30.00-37.00], respectively; P=.001). VO2max-CPET, VO2max-SWT, and red blood cell distribution width-coefficient of variation (RDW-CV) were found to be independent predictors of AMS. To increase the prediction accuracy, we used combination models. The combination of VO2max-SWT and RDW-CV showed the largest area under the curve for all parameters and models, which increased the area under the curve from 0.785 for VO2max-SWT alone to 0.839. CONCLUSIONS Our study demonstrates that the smartwatch device can be a feasible approach for estimating VO2max. In both low and high altitudes, VO2max-SWT showed a systematic bias toward a calibration point, slightly overestimating the proper VO2max when investigated in healthy participants. The SWT-based VO2max at low altitude is an effective indicator of AMS and helps to better identify susceptible individuals following acute high-altitude exposure, particularly by combining the RDW-CV at low altitude. TRIAL REGISTRATION Chinese Clinical Trial Registry ChiCTR2200059900; https://www.chictr.org.cn/showproj.html?proj=170253.
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Affiliation(s)
- Xiaowei Ye
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Mengjia Sun
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Shiyong Yu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jie Yang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Zhen Liu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Hailin Lv
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Boji Wu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jingyu He
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xuhong Wang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Lan Huang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
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Shiwani MA, Chico TJA, Ciravegna F, Mihaylova L. Continuous Monitoring of Health and Mobility Indicators in Patients with Cardiovascular Disease: A Review of Recent Technologies. SENSORS (BASEL, SWITZERLAND) 2023; 23:5752. [PMID: 37420916 PMCID: PMC10300851 DOI: 10.3390/s23125752] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 06/01/2023] [Accepted: 06/12/2023] [Indexed: 07/09/2023]
Abstract
Cardiovascular diseases kill 18 million people each year. Currently, a patient's health is assessed only during clinical visits, which are often infrequent and provide little information on the person's health during daily life. Advances in mobile health technologies have allowed for the continuous monitoring of indicators of health and mobility during daily life by wearable and other devices. The ability to obtain such longitudinal, clinically relevant measurements could enhance the prevention, detection and treatment of cardiovascular diseases. This review discusses the advantages and disadvantages of various methods for monitoring patients with cardiovascular disease during daily life using wearable devices. We specifically discuss three distinct monitoring domains: physical activity monitoring, indoor home monitoring and physiological parameter monitoring.
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Affiliation(s)
- Muhammad Ali Shiwani
- Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield S1 3JD, UK
| | - Timothy J. A. Chico
- Department of Infection, Immunity and Cardiovascular Disease, The Medical School, The University of Sheffield, Sheffield S10 2RX, UK
| | - Fabio Ciravegna
- Dipartimento di Informatica, Università di Torino, 10124 Turin, Italy
| | - Lyudmila Mihaylova
- Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield S1 3JD, UK
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21
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Agbohessou KG, Sahuguede S, Lacroix J, Hamdan F, Conchon E, Dumas Y, Julien-Vergonjanne A, Mandigout S. Validity of Estimated Results from a Wearable Device for the Tests Time Up and Go and Sit to Stand in Young Adults and in People with Chronic Diseases. SENSORS (BASEL, SWITZERLAND) 2023; 23:5742. [PMID: 37420906 DOI: 10.3390/s23125742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/15/2023] [Accepted: 06/16/2023] [Indexed: 07/09/2023]
Abstract
BACKGROUND Health care professionals need a valid tool to assess the physical ability of patients with chronic diseases. We aimed to assess the validity of the results of physical fitness tests estimated by a wrist wearable device in young adults and chronic disease people. METHODS Participants wore a sensor placed on their wrist and performed two physical fitness tests (sit to stand (STS) and time up and go (TUG)). We checked the concordance of sensor-estimated results using Bland-Altman analysis, root-mean-square error, and intraclass coefficient of correlation (ICC). RESULTS In total, 31 young adults (groups A; median age = 25 ± 5 years) and 14 people with chronic diseases (groups B; median age = 70 ± 15 years) were included. Concordance was high for both STS (ICCA = 0.95, and ICCB = 0.90), and TUG (ICCA = 0.75, ICCB = 0.98). The best estimations were given by the sensor during STS tests in young adults (mean bias = 0.19 ± 2.69; p = 0.12) and chronic disease people (mean bias = -0.14 ± 3.09 s; p = 0.24). The sensor provided the largest estimation errors over 2 s during the TUG test in young adults. CONCLUSION This study showed that the results provided by the sensor are consistent with those of the gold standard during STS and TUG in both healthy youth and people with chronic diseases.
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Affiliation(s)
| | - Stephanie Sahuguede
- XLIM Laboratory, UMR CNRS 7252, University of Limoges, 87000 Limoges, France
| | - Justine Lacroix
- HAVAE EA6310 (Handicap, Aging, Autonomy, Environment), University of Limoges, 87042 Limoges, France
| | - Fadel Hamdan
- XLIM Laboratory, UMR CNRS 7252, University of Limoges, 87000 Limoges, France
| | - Emmanuel Conchon
- XLIM Laboratory, UMR CNRS 7252, University of Limoges, 87000 Limoges, France
| | - Yannick Dumas
- Développement de Logiciels, UNOVA, 87000 Limoges, France
| | | | - Stephane Mandigout
- HAVAE EA6310 (Handicap, Aging, Autonomy, Environment), University of Limoges, 87042 Limoges, France
- ILFOMER (Institut Limousin de Formation aux Métiers de la Réadaptation), Université de Limoges, 87000 Limoges, France
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22
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Durán Vega HC, Lopez Echaury A, Flores E. The Energy a Plastic Surgeon Expends during Liposuction. PLASTIC AND RECONSTRUCTIVE SURGERY-GLOBAL OPEN 2023; 11:e5001. [PMID: 37250835 PMCID: PMC10212613 DOI: 10.1097/gox.0000000000005001] [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: 02/13/2023] [Accepted: 03/29/2023] [Indexed: 05/31/2023]
Abstract
It is generally accepted that liposuction requires a significant amount of energy from surgeons. This procedure involves the use of specialized equipment and techniques to remove fat cells from the body, which can be physically demanding for surgeons. The amount of effort required for liposuction must be evaluated in terms of energy consumption. Our goal was to conduct a study to record the energy that the surgeon uses during liposuction and correlate these results with the volume of fat obtained as well as other variables. Methods A series of cases was carried out from April 2022 to November 1, 2022, in three different plastic surgery centers. Three plastic surgeons recorded the procedures using an Apple Watch, choosing from among Apple Watch training options and free indoor walking. The surgeon then concluded the registration at the time of finishing the surgery and removed the surgical gloves and gowns. Results Complete data were obtained for 63 patients. The average fat obtained per 1 kcal of energy was 6.14 cm3 of fat, and 160 cal to obtain 1 cm3 of fat by liposuction. Other data that demonstrated statistically significant correlations were fat volume versus average pace (km), total fat volume versus average heart rate, fat volume versus surgical time, and fat volume versus distance. Conclusions Liposuction is a surgical procedure that requires considerable effort. This study demonstrates the amount of energy required for regular liposuction. Compared with other single procedures, three times more energy is required to complete liposuction.
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23
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Edgerton JR, Damiano RJ. Commentary: What is the measure of success for atrial fibrillation ablation? Is a reduction in arrhythmia burden sufficient? J Thorac Cardiovasc Surg 2023; 165:1396-1397. [PMID: 33965223 PMCID: PMC9680864 DOI: 10.1016/j.jtcvs.2021.04.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 04/01/2021] [Accepted: 04/05/2021] [Indexed: 11/18/2022]
Affiliation(s)
- James R Edgerton
- Division of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, Barnes-Jewish Hospital, St Louis, Mo; Baylor Research Institute, Dallas, Tex.
| | - Ralph J Damiano
- Division of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, Barnes-Jewish Hospital, St Louis, Mo
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Martín-Escudero P, Cabanas AM, Dotor-Castilla ML, Galindo-Canales M, Miguel-Tobal F, Fernández-Pérez C, Fuentes-Ferrer M, Giannetti R. Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise? Bioengineering (Basel) 2023; 10:254. [PMID: 36829748 PMCID: PMC9952291 DOI: 10.3390/bioengineering10020254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/28/2023] [Accepted: 01/30/2023] [Indexed: 02/17/2023] Open
Abstract
The market for wrist-worn devices is growing at previously unheard-of speeds. A consequence of their fast commercialization is a lack of adequate studies testing their accuracy on varied populations and pursuits. To provide an understanding of wearable sensors for sports medicine, the present study examined heart rate (HR) measurements of four popular wrist-worn devices, the (Fitbit Charge (FB), Apple Watch (AW), Tomtom runner Cardio (TT), and Samsung G2 (G2)), and compared them with gold standard measurements derived by continuous electrocardiogram examination (ECG). Eight athletes participated in a comparative study undergoing maximal stress testing on a cycle ergometer or a treadmill. We analyzed 1,286 simultaneous HR data pairs between the tested devices and the ECG. The four devices were reasonably accurate at the lowest activity level. However, at higher levels of exercise intensity the FB and G2 tended to underestimate HR values during intense physical effort, while the TT and AW devices were fairly reliable. Our results suggest that HR estimations should be considered cautiously at specific intensities. Indeed, an effective intervention is required to register accurate HR readings at high-intensity levels (above 150 bpm). It is important to consider that even though none of these devices are certified or sold as medical or safety devices, researchers must nonetheless evaluate wrist-worn wearable technology in order to fully understand how HR affects psychological and physical health, especially under conditions of more intense exercise.
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Affiliation(s)
- Pilar Martín-Escudero
- Professional Medical School of Physical Education and Sport, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Ana María Cabanas
- Departamento de Física, FACI, Universidad de Tarapacá, Arica 1010069, Chile
| | | | - Mercedes Galindo-Canales
- Professional Medical School of Physical Education and Sport, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Francisco Miguel-Tobal
- Professional Medical School of Physical Education and Sport, Faculty of Medicine, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Cristina Fernández-Pérez
- Servicio de Medicina Preventiva Complejo Hospitalario de Santiago de Compostela, Instituto de Investigación Sanitaria de Santiago, 15706 Santiago de Compostela, Spain
| | - Manuel Fuentes-Ferrer
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, 38010 Santa Cruz de Tenerife, Spain
| | - Romano Giannetti
- IIT, Institute of Technology Research, Universidad Pontificia Comillas, 28015 Madrid, Spain
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Zhang Y, Zhao Y, Liu K, Chai Y, Lin F, Zhan H, Zheng Y, Yuan W. Test reliability and comparability of paper and Chinese electronic version of the western Ontario and McMaster University osteoarthritis index: protocol for a randomised controlled clinical trial. BMJ Open 2022; 12:e063576. [PMID: 36351726 PMCID: PMC9644355 DOI: 10.1136/bmjopen-2022-063576] [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] [Indexed: 11/11/2022] Open
Abstract
INTRODUCTION The Western Ontario and McMaster University osteoarthritis index (WOMAC) is the most commonly used indicator of disease-specific outcome in knee osteoarthritis for its convenience and reliability. It has two formats the paper-based WOMAC (p-WOMAC) and the electronic WOMAC (e-WOMAC). In China, the p-WOMAC has been widely used though e-WOMAC is yet untested. This study aims to test whether e-WOMAC is consistent with the p-WOMAC before and after the intervention. METHODS AND ANALYSIS A total of 70 patients from Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine will be randomly assigned in two groups, named, group A and group B. This study is divided into three stages. In the first stage, patients in group A will be evaluated first by p-WOMAC and then by e-WOMAC. Patients in group B will be evaluated by e-WOMAC and then by p-WOMAC. In the second stage of the study, drug interventions will be implemented. 200 mg celecoxib will be administered orally once a day starting from the second day of enrolment for a period of 21 days. In the third stage, postintervention evaluation will be conducted after administration. Patients in group A will be evaluated first by e-WOMAC and then by p-WOMAC. Patients in group B will be evaluated first by p-WOMAC and then by e-WOMAC. In order to avoid the possible bias because of patients' potential memory, e-WOMAC and p-WOMAC will be taken for each patient at 15 min apart. The primary outcome of the study is the mean score difference in WOMAC, and the secondary outcomes are the score differences in WOMAC subscales: pain, stiffness and physical function. ETHICS AND DISSEMINATION The protocol has been approved by the Independent Review Board of SGH (approval number: 2020-814-21-01). The results of the trial will be submitted for publication in a peer-reviewed journal. TRIAL REGISTRATION NUMBER ChiCTR2100050914.
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Affiliation(s)
- Yujie Zhang
- Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, ShangHai, 201203, China
| | - Ye Zhao
- Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, ShangHai, 201203, China
| | - Kaoqiang Liu
- Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, ShangHai, 201203, China
| | - Yongli Chai
- Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, ShangHai, 201203, China
| | - Fen Lin
- Shanghai Jsure Health Co., Ltd, Shanghai, China
| | - Hongsheng Zhan
- Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, ShangHai, 201203, China
| | - Yuxin Zheng
- Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, ShangHai, 201203, China
| | - Weian Yuan
- Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, ShangHai, 201203, China
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26
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Wang J, Wu X, Sun J, Xu T, Zhu T, Yu F, Duan S, Deng Q, Liu Z, Guo F, Li X, Wang Y, Song L, Feng H, Zhou X, Jiang H. Prediction of major adverse cardiovascular events in patients with acute coronary syndrome: Development and validation of a non-invasive nomogram model based on autonomic nervous system assessment. Front Cardiovasc Med 2022; 9:1053470. [PMID: 36407419 PMCID: PMC9670131 DOI: 10.3389/fcvm.2022.1053470] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 10/13/2022] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Disruption of the autonomic nervous system (ANS) can lead to acute coronary syndrome (ACS). We developed a nomogram model using heart rate variability (HRV) and other data to predict major adverse cardiovascular events (MACEs) following emergency coronary angiography in patients with ACS. METHODS ACS patients admitted from January 2018 to June 2020 were examined. Holter monitors were used to collect HRV data for 24 h. Coronary angiograms, clinical data, and MACEs were recorded. A nomogram was developed using the results of Cox regression analysis. RESULTS There were 439 patients in a development cohort and 241 in a validation cohort, and the mean follow-up time was 22.80 months. The nomogram considered low-frequency/high-frequency ratio, age, diabetes, previous myocardial infarction, and current smoking. The area-under-the-curve (AUC) values for 1-year MACE-free survival were 0.790 (95% CI: 0.702-0.877) in the development cohort and 0.894 (95% CI: 0.820-0.967) in the external validation cohort. The AUCs for 2-year MACE-free survival were 0.802 (95% CI: 0.739-0.866) in the development cohort and 0.798 (95% CI: 0.693-0.902) in the external validation cohort. Development and validation were adequately calibrated and their predictions correlated with the observed outcome. Decision curve analysis (DCA) showed the model had good discriminative ability in predicting MACEs. CONCLUSION Our validated nomogram was based on non-invasive ANS assessment and traditional risk factors, and indicated reliable prediction of MACEs in patients with ACS. This approach has potential for use as a method for non-invasive monitoring of health that enables provision of individualized treatment strategies.
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Affiliation(s)
- Jun Wang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Xiaolin Wu
- Department of Cardiology, Institute of Cardiovascular Diseases, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, China
| | - Ji Sun
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Tianyou Xu
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Tongjian Zhu
- Department of Cardiology, Institute of Cardiovascular Diseases, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, China
| | - Fu Yu
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Shoupeng Duan
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Qiang Deng
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Zhihao Liu
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Fuding Guo
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Xujun Li
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Yijun Wang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Lingpeng Song
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Hui Feng
- Information Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xiaoya Zhou
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Hong Jiang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiac Autonomic Nervous System Research Center of Wuhan University, Wuhan, China
- Hubei Key Laboratory of Autonomic Nervous System Modulation, Wuhan, China
- TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
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Wattanapisit A, Ng CJ, Angkurawaranon C, Wattanapisit S, Chaovalit S, Stoutenberg M. Summary and application of the WHO 2020 physical activity guidelines for patients with essential hypertension in primary care. Heliyon 2022; 8:e11259. [PMID: 36325139 PMCID: PMC9618974 DOI: 10.1016/j.heliyon.2022.e11259] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/15/2022] [Accepted: 10/20/2022] [Indexed: 11/06/2022] Open
Abstract
The new World Health Organization (WHO) 2020 guidelines on physical activity (PA) and sedentary behavior include recommendations for adults with chronic conditions. The guidelines provide adaptable and general recommendations for people living with chronic medical conditions. This article summarizes the content and provides suggestions for the application of the guidelines for patients with essential hypertension in primary care. The WHO 2020 PA guidelines recommend broad advice for adults and older adults with chronic conditions. The key recommendations are consistent with other hypertension guidelines. A systemic approach to promote PA in primary care (i.e., PA assessment, safety considerations, PA prescription, behavioral counseling, and referral) along with applying the WHO guidelines is required. Health risk assessment and safety issues related to hypertension (e.g., current PA levels, level of blood pressure, treatment plans, comorbidities) should be concerned. The FITT Pro (frequency, intensity, time, type, and progression) can be adopted as a framework to break down the guidelines into specific PA prescription. The WHO 2020 PA guidelines address the importance of PA in clinical populations. The guidelines can be adapted for patients with hypertension in primary care settings.
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Affiliation(s)
- Apichai Wattanapisit
- Department of Clinical Medicine, School of Medicine, Walailak University, Nakhon Si Thammarat, Thailand,Family Medicine Clinic, Walailak University Hospital, Nakhon Si Thammarat, Thailand
| | - Chirk Jenn Ng
- Department of Primary Care Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia,SingHealth Polyclinics, Singapore, Singapore,Duke-NUS Medical School, Singapore, Singapore
| | - Chaisiri Angkurawaranon
- Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand,Global Health and Chronic Conditions Research Group, Chiang Mai University, Chiang Mai, Thailand,Corresponding author.
| | | | - Sirawee Chaovalit
- Department of Physical Therapy, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand
| | - Mark Stoutenberg
- Department of Kinesiology, College of Public Health, Temple University, Philadelphia, USA
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28
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Howell P, Aryal A, Wu C. Online Patient Recommender Systems for Preventive Care: Propositions to Advance Research (Preprint). JMIR Res Protoc 2022; 12:e43316. [PMID: 36995747 PMCID: PMC10132006 DOI: 10.2196/43316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 01/21/2023] [Accepted: 02/07/2023] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND Preventive care helps patients identify and address medical issues early when they are easy to treat. The internet offers vast information about preventive measures, but the sheer volume of data can be overwhelming for individuals to process. To help individuals navigate this information, recommender systems filter and recommend relevant information to specific users. Despite their popularity in other fields, such as e-commerce, recommender systems have yet to be extensively studied as tools to support the implementation of prevention strategies in health care. This underexplored area presents an opportunity for recommender systems to serve as a complementary tool for medical professionals to enhance patient-centered decision-making and for patients to access health information. Thus, these systems can potentially improve the delivery of preventive care. OBJECTIVE This study proposes practical, evidence-based propositions. It aims to identify the key factors influencing patients' use of recommender systems and outlines a study design, methods for creating a survey, and techniques for conducting an analysis. METHODS This study proposes a 6-stage approach to examine user perceptions of the factors that may influence the use of recommender systems for preventive care. First, we formulate 6 research propositions that can be developed later into hypotheses for empirical testing. Second, we will create a survey instrument by collecting items from extant literature and then verify their relevance using expert analysis. This stage will continue with content and face validity testing to ensure the robustness of the selected items. Using Qualtrics (Qualtrics), the survey can be customized and prepared for deployment on Amazon Mechanical Turk. Third, we will obtain institutional review board approval because this is a human subject study. In the fourth stage, we propose using the survey to collect data from approximately 600 participants on Amazon Mechanical Turk and then using R to analyze the research model. This platform will serve as a recruitment tool and the method of obtaining informed consent. In our fifth stage, we will perform principal component analysis, Harman Single Factor test, exploratory factor analysis, and correlational analysis; examine the reliability and convergent validity of individual items; test if multicollinearity exists; and complete a confirmatory factor analysis. RESULTS Data collection and analysis will begin after institutional review board approval is obtained. CONCLUSIONS In pursuit of better health outcomes, low costs, and improved patient and provider experiences, the integration of recommender systems with health care services can extend the reach and scale of preventive care. Examining recommender systems for preventive care can be vital in achieving the quadruple aims by advancing the steps toward precision medicine and applying best practices. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/43316.
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Affiliation(s)
- Pamella Howell
- Department of Information Systems, College of Business and Economics, California State University, Los Angeles, Los Angeles, CA, United States
| | - Arun Aryal
- Department of Information Systems, College of Business and Economics, California State University, Los Angeles, Los Angeles, CA, United States
| | - Crystal Wu
- Department of Information Systems, College of Business and Economics, California State University, Los Angeles, Los Angeles, CA, United States
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29
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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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Garikapati K, Turnbull S, Bennett RG, Campbell TG, Kanawati J, Wong MS, Thomas SP, Chow CK, Kumar S. The Role of Contemporary Wearable and Handheld Devices in the Diagnosis and Management of Cardiac Arrhythmias. Heart Lung Circ 2022; 31:1432-1449. [PMID: 36109292 DOI: 10.1016/j.hlc.2022.08.001] [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: 04/13/2022] [Revised: 07/18/2022] [Accepted: 08/01/2022] [Indexed: 10/14/2022]
Abstract
Cardiac arrhythmias are associated with significant morbidity, mortality and economic burden on the health care system. Detection and surveillance of cardiac arrhythmias using medical grade non-invasive methods (electrocardiogram, Holter monitoring) is the accepted standard of care. Whilst their accuracy is excellent, significant limitations remain in terms of accessibility, ease of use, cost, and a suboptimal diagnostic yield (up to ∼50%) which is critically dependent on the duration of monitoring. Contemporary wearable and handheld devices that utilise photoplethysmography and the electrocardiogram present a novel opportunity for remote screening and diagnosis of arrhythmias. They have significant advantages in terms of accessibility and availability with the potential of enhancing the diagnostic yield of episodic arrhythmias. However, there is limited data on the accuracy and diagnostic utility of these devices and their role in therapeutic decision making in clinical practice remains unclear. Evidence is mounting that they may be useful in screening for atrial fibrillation, and anecdotally, for the diagnosis of other brady and tachyarrhythmias. Recently, there has been an explosion of patient uptake of such devices for self-monitoring of arrhythmias. Frequently, the clinician is presented such information for review and comment, which may influence clinical decisions about treatment. Further studies are needed before incorporation of such technologies in routine clinical practice, given the lack of systematic data on their accuracy and utility. Moreover, challenges with regulation of quality standards and privacy remain. This state-of-the-art review summarises the role of novel ambulatory, commercially available, heart rhythm monitors in the diagnosis and management of cardiac arrhythmias and their expanding role in the diagnostic and therapeutic paradigm in cardiology.
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Affiliation(s)
- Kartheek Garikapati
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Samual Turnbull
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Richard G Bennett
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Timothy G Campbell
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Juliana Kanawati
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Mary S Wong
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Stuart P Thomas
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Clara K Chow
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia
| | - Saurabh Kumar
- Department of Cardiology, Westmead Hospital, Westmead Applied Research Centre, University of Sydney, Sydney, NSW Australia.
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31
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Dunne DM, Lefevre-Lewis C, Cunniffe B, Impey SG, Tod D, Close GL, Morton JP, Murphy R. Athlete experiences of communication strategies in applied sports nutrition and future considerations for mobile app supportive solutions. Front Sports Act Living 2022; 4:911412. [PMID: 36172339 PMCID: PMC9512279 DOI: 10.3389/fspor.2022.911412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
Aim This study aimed to explore athletes' experiences and opinions of communication strategies in applied sports nutrition, as well as capture suggestions for future mobile app supportive solutions. Methods A qualitative approach was used for this research. Data was generated from semi-structured focus groups (n = 9) with a purposive sample of 41 (male = 24, female = 17) full time professional athletes (mean age 24 ± 4.59) from five sports (football, rugby union, athletics, cycling, and boxing). Data was analyzed using reflexive thematic analysis. Results The analysis identified four higher order themes and five sub themes. Athletes appear dissatisfied with the levels of personalization in the nutrition support they receive. Limited practitioner contact time was suggested as a contributing factor to this problem. Athletes acknowledged the usefulness of online remote nutrition support and reported a desire for more personalized technology that can tailor support to their individual needs. Conclusion Athletes experienced a hybrid human-computer approach that combines in-person and remote digital methods to communicate with and receive information from practitioners. Mobile technology may now afford sports nutritionists with new opportunities to develop scalable solutions to support practice.
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Affiliation(s)
- David Mark Dunne
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom
| | | | - Brian Cunniffe
- Department of Surgery, University College London, London, United Kingdom
- English Institute of Sport, Manchester, United Kingdom
| | - Samuel George Impey
- Centre for Exercise and Sports Science Research, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - David Tod
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom
| | - Graeme Leonard Close
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom
| | - James P. Morton
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom
| | - Rebecca Murphy
- Research Institute for Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, United Kingdom
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Lui GY, Loughnane D, Polley C, Jayarathna T, Breen PP. The Apple Watch for Monitoring Mental Health-Related Physiological Symptoms: Literature Review. JMIR Ment Health 2022; 9:e37354. [PMID: 36069848 PMCID: PMC9494213 DOI: 10.2196/37354] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 07/29/2022] [Accepted: 08/03/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND An anticipated surge in mental health service demand related to COVID-19 has motivated the use of novel methods of care to meet demand, given workforce limitations. Digital health technologies in the form of self-tracking technology have been identified as a potential avenue, provided sufficient evidence exists to support their effectiveness in mental health contexts. OBJECTIVE This literature review aims to identify current and potential physiological or physiologically related monitoring capabilities of the Apple Watch relevant to mental health monitoring and examine the accuracy and validation status of these measures and their implications for mental health treatment. METHODS A literature review was conducted from June 2021 to July 2021 of both published and gray literature pertaining to the Apple Watch, mental health, and physiology. The literature review identified studies validating the sensor capabilities of the Apple Watch. RESULTS A total of 5583 paper titles were identified, with 115 (2.06%) reviewed in full. Of these 115 papers, 19 (16.5%) were related to Apple Watch validation or comparison studies. Most studies showed that the Apple Watch could measure heart rate acceptably with increased errors in case of movement. Accurate energy expenditure measurements are difficult for most wearables, with the Apple Watch generally providing the best results compared with peers, despite overestimation. Heart rate variability measurements were found to have gaps in data but were able to detect mild mental stress. Activity monitoring with step counting showed good agreement, although wheelchair use was found to be prone to overestimation and poor performance on overground tasks. Atrial fibrillation detection showed mixed results, in part because of a high inconclusive result rate, but may be useful for ongoing monitoring. No studies recorded validation of the Sleep app feature; however, accelerometer-based sleep monitoring showed high accuracy and sensitivity in detecting sleep. CONCLUSIONS The results are encouraging regarding the application of the Apple Watch in mental health, particularly as heart rate variability is a key indicator of changes in both physical and emotional states. Particular benefits may be derived through avoidance of recall bias and collection of supporting ecological context data. However, a lack of methodologically robust and replicated evidence of user benefit, a supportive health economic analysis, and concerns about personal health information remain key factors that must be addressed to enable broader uptake.
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Affiliation(s)
- Gough Yumu Lui
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia
| | | | - Caitlin Polley
- Electrical and Electronic Engineering, School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW, Australia
| | - Titus Jayarathna
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia
| | - Paul P Breen
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia.,Translational Health Research Institute, Western Sydney University, Penrith, NSW, Australia
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Dobbie LJ, Tahrani A, Alam U, James J, Wilding J, Cuthbertson DJ. Exercise in Obesity-the Role of Technology in Health Services: Can This Approach Work? Curr Obes Rep 2022; 11:93-106. [PMID: 34791611 PMCID: PMC8597870 DOI: 10.1007/s13679-021-00461-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/02/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE OF REVIEW Physical activity (PA) is an important strategy to prevent and treat obesity. Electronic health (eHealth) interventions, such as wearable activity monitors and smartphone apps, may promote adherence to regular PA and successful weight loss. This review highlights the evidence for eHealth interventions in promoting PA and reducing weight. RECENT FINDINGS Wearables can increase PA and are associated with moderate weight loss in middle/older-aged individuals, with less convincing effects long-term (> 1 year) and in younger people. Data for interventions such as mobile phone applications, SMS, and exergaming are less robust. Investigations of all eHealth interventions are often limited by complex, multi-modality study designs, involving concomitant dietary modification, making the independent contribution of each eHealth intervention on body weight challenging to assess. eHealth interventions may promote PA, thereby contributing to weight loss/weight maintenance; however, further evaluation is required for this approach to be adopted into routine clinical practice.
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Affiliation(s)
- Laurence J. Dobbie
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
- University Hospital Aintree, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Abd Tahrani
- Institute of Metabolism and Systems, School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK
- Department of Diabetes and Endocrinology, Birmingham Heartlands Hospital, Birmingham, UK
| | - Uazman Alam
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
- University Hospital Aintree, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Jennifer James
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
- University Hospital Aintree, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - John Wilding
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
- University Hospital Aintree, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Daniel J. Cuthbertson
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
- University Hospital Aintree, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
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Wang Z, Zhang Q, Lan K, Yang Z, Gao X, Wu A, Xin Y, Zhang Z. Enhancing instantaneous oxygen uptake estimation by non-linear model using cardio-pulmonary physiological and motion signals. Front Physiol 2022; 13:897412. [PMID: 36105296 PMCID: PMC9465676 DOI: 10.3389/fphys.2022.897412] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 07/29/2022] [Indexed: 11/30/2022] Open
Abstract
Oxygen uptake (VO2) is an important parameter in sports medicine, health assessment and clinical treatment. At present, more and more wearable devices are used in daily life, clinical treatment and health care. The parameters obtained by wearables have great research potential and application prospect. In this paper, an instantaneous VO2 estimation model based on XGBoost was proposed and verified by using data obtained from a medical-grade wearable device (Beijing SensEcho) at different posture and activity levels. Furthermore, physiological characteristics extracted from single-lead electrocardiogram, thoracic and abdominal respiration signal and tri-axial acceleration signal were studied to optimize the model. There were 29 healthy volunteers recruited for the study to collect data while stationary (lying, sitting, standing), walking, Bruce treadmill test and recuperating with SensEcho and the gas analyzer (Metalyzer 3B). The results show that the VO2 values estimated by the proposed model are in good agreement with the true values measured by the gas analyzer (R2 = 0.94 ± 0.03, n = 72,235), and the mean absolute error (MAE) is 1.83 ± 0.59 ml/kg/min. Compared with the estimation method using a separate heart rate as input, our method reduced MAE by 54.70%. At the same time, other factors affecting the performance of the model were studied, including the influence of different input signals, gender and movement intensity, which provided more enlightenment for the estimation of VO2. The results show that the proposed model based on cardio-pulmonary physiological signals as inputs can effectively improve the accuracy of instantaneous VO2 estimation in various scenarios of activities and was robust between different motion modes and state. The VO2 estimation method proposed in this paper has the potential to be used in daily life covering the scenario of stationary, walking and maximal exercise.
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Affiliation(s)
- Zhao Wang
- Medical School of Chinese PLA, Beijing, China
| | - Qiang Zhang
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Ke Lan
- Beijing SensEcho Science and Technology Co Ltd, Beijing, China
| | - Zhicheng Yang
- PAII Inc., Palo Alto, Santa Clara, CA, United States
| | - Xiaolin Gao
- Institute of Sports Science, General Administration of Sport of China, Beijing, China
| | - Anshuo Wu
- The Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States
| | - Yi Xin
- School of Life Science, Beijing Institute of Technology, Beijing, China
- *Correspondence: Yi Xin, ; Zhengbo Zhang,
| | - Zhengbo Zhang
- Center for Artificial Intelligence in Medicine, Chinese PLA General Hospital, Beijing, China
- *Correspondence: Yi Xin, ; Zhengbo Zhang,
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Comparison of Apple Watch Series 4 vs. KardiaMobile: A Tale of Two Devices. CJC Open 2022; 4:939-945. [PMID: 36444370 PMCID: PMC9700214 DOI: 10.1016/j.cjco.2022.07.011] [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: 06/08/2022] [Accepted: 07/18/2022] [Indexed: 12/02/2022] Open
Abstract
Background The Apple Watch Series 4 (AW4) and the KardiaMobile single bipolar lead model (KM) are 2 of the most popular US Food & Drug Administration (FDA)-approved commercial heart trackers. However, a lack of knowledge remains regarding their rhythm-detection accuracy in real-life clinical situations. This paper aims to determine the practicality of using an AW4 or a KM in modern medical practice, by assessing the accuracy of each in identifying heart rhythms and heart rate. Methods Participants from the Toronto Heart Centre clinic were enrolled from January 2019 to December 2019. They had a 12-lead electrocardiogram (ECG), followed by wearing the AW4 watch (OS 5.3), and pressing on the KM electrode plates, within the span of 5 minutes of one another. Each session involved a 12-lead ECG, an ECG from each device, and AW4’s photoplethysmography function (APPG). Results Of 200 participants, 162 (81%) were in sinus rhythm, and 38 (19%) had atrial fibrillation. The rhythm-detection accuracy for sinus rhythm was 100% for the AW4, and 99.03% for the KM. For atrial fibrillation, accuracy was 90.48% for the AW4, and 100% for the KM. The heart rate accuracy for sinus rhythm was 94.39% for the KM, 90.65% for the APPG, and 96.26% for the Apple ECG function. The heart rate accuracy for atrial fibrillation was 91.30% for the KM, 82.61% for the APPG, and 86.96% for the Apple ECG function. Conclusions Both the AW4 and the KM could reliably detect rhythm and heart rate in real-life clinical situations. However, a nonsignificant trend occurred toward better rhythm detection and accuracy with KM, compared with AW4. The difference is mainly due to artifacts (eg, tremors) and the fit of the strap for AW4. The findings have important implications for how these consumer devices can be used in real-life clinical settings.
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Kim C, Kim SH, Suh MR. Accuracy and Validity of Commercial Smart Bands for Heart Rate Measurements During Cardiopulmonary Exercise Test. Ann Rehabil Med 2022; 46:209-218. [PMID: 36071003 PMCID: PMC9452288 DOI: 10.5535/arm.22050] [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] [Received: 05/04/2022] [Accepted: 07/01/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To assess the accuracies and validities of popular smart bands for heart rate (HR) measurement in cardiovascular disease (CVD) patients during a graded exercise test (GXT). METHODS Seventy-eight patients were randomly assigned to wear two different smart bands out of three possible choices: Samsung Galaxy Fit 2, Xiaomi Mi Band 5, or Partron PWB-250 on each wrist. A 12-lead exercise electrocardiogram (ECG) and patch-type single-lead ECG were used to assess the comparative HR accuracy of the smart bands. The HR was recorded during the GXT using the modified Bruce protocol. RESULTS The concordance correlation coefficients (rc) were calculated to provide a measure of agreement between each device and the ECG. In all conditions, the Mi Band 5 and Galaxy Fit 2' correlations were rc>0.90, while the PWB-250 correlation was rc=0.58 at rest. When evaluating the accuracy according to the magnitude of HR, all smart bands performed well (rc>0.90) when the HR was below 100 but accuracy tended to decrease with higher HR values. CONCLUSION This study showed that the three smart bands had a high level of accuracy for HR measurements during low-intensity exercise. However, during moderate-intensity and high-intensity exercise, all the three smart bands performed less accurately. Further studies are needed to find a more optimal smart band for HR measurement that can be used for precise HR monitoring during formal cardiac rehabilitation exercise training, including at high and maximal intensity (Clinical Trial Registration No. cris.nih.go.kr/KCT0007036).
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Affiliation(s)
- Chul Kim
- Department of Rehabilitation Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea
| | - Seung Hyoun Kim
- Department of Rehabilitation Medicine, Sanggye Paik Hospital, Seoul, Korea
| | - Mi Rim Suh
- Department of Rehabilitation Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea
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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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Dandapani HG, Davoodi NM, Joerg LC, Li MM, Strauss DH, Fan K, Massachi T, Goldberg EM. Leveraging Mobile-Based Sensors for Clinical Research to Obtain Activity and Health Measures for Disease Monitoring, Prevention, and Treatment. Front Digit Health 2022; 4:893070. [PMID: 35774115 PMCID: PMC9237242 DOI: 10.3389/fdgth.2022.893070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 05/23/2022] [Indexed: 11/29/2022] Open
Abstract
Clinical researchers are using mobile-based sensors to obtain detailed and objective measures of the activity and health of research participants, but many investigators lack expertise in integrating wearables and sensor technologies effectively into their studies. Here, we describe the steps taken to design a study using sensors for disease monitoring in older adults and explore the benefits and drawbacks of our approach. In this study, the Geriatric Acute and Post-acute Fall Prevention Intervention (GAPcare), we created an iOS app to collect data from the Apple Watch's gyroscope, accelerometer, and other sensors; results of cognitive and fitness tests; and participant-entered survey data. We created the study app using ResearchKit, an open-source framework developed by Apple for medical research that includes neuropsychological tests (e.g., of executive function and memory), gait speed, balance, and other health assessments. Data is transmitted via an Application Programming Interface (API) from the app to REDCap for researchers to monitor and analyze in real-time. Employing the lessons learned from GAPcare could help researchers create study-tailored research apps and access timely information about their research participants from wearables and smartphone devices for disease prevention, monitoring, and treatment.
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Affiliation(s)
| | - Natalie M. Davoodi
- Brown University, Providence, RI, United States
- Department of Emergency Medicine, The Warren Alpert Medical School of Brown University, Providence, RI, United States
| | | | | | - Daniel H. Strauss
- Brown University, Providence, RI, United States
- Department of Emergency Medicine, The Warren Alpert Medical School of Brown University, Providence, RI, United States
| | - Kelly Fan
- Brown University, Providence, RI, United States
| | | | - Elizabeth M. Goldberg
- Brown University, Providence, RI, United States
- Department of Emergency Medicine, The Warren Alpert Medical School of Brown University, Providence, RI, United States
- *Correspondence: Elizabeth M. Goldberg
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Elshafei M, Costa DE, Shihab E. Toward the Personalization of Biceps Fatigue Detection Model for Gym Activity: An Approach to Utilize Wearables' Data from the Crowd. SENSORS (BASEL, SWITZERLAND) 2022; 22:1454. [PMID: 35214356 PMCID: PMC8877759 DOI: 10.3390/s22041454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 02/05/2022] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
Nowadays, wearables-based Human Activity Recognition (HAR) systems represent a modern, robust, and lightweight solution to monitor athlete performance. However, user data variability is a problem that may hinder the performance of HAR systems, especially the cross-subject HAR models. Such a problem may have a lesser effect on the subject-specific model because it is a tailored model that serves a specific user; hence, data variability is usually low, and performance is often high. However, such a performance comes with a high cost in data collection and processing per user. Therefore, in this work, we present a personalized model that achieves higher performance than the cross-subject model while maintaining a lower data cost than the subject-specific model. Our personalization approach sources data from the crowd based on similarity scores computed between the test subject and the individuals in the crowd. Our dataset consists of 3750 concentration curl repetitions from 25 volunteers with ages and BMI ranging between 20-46 and 24-46, respectively. We compute 11 hand-crafted features and train 2 personalized AdaBoost models, Decision Tree (AdaBoost-DT) and Artificial Neural Networks (AdaBoost-ANN), using data from whom the test subject shares similar physical and single traits. Our findings show that the AdaBoost-DT model outperforms the cross-subject-DT model by 5.89%, while the AdaBoost-ANN model outperforms the cross-subject-ANN model by 3.38%. On the other hand, at 50.0% less of the test subject's data consumption, our AdaBoost-DT model outperforms the subject-specific-DT model by 16%, while the AdaBoost-ANN model outperforms the subject-specific-ANN model by 10.33%. Yet, the subject-specific models achieve the best performances at 100% of the test subjects' data consumption.
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Huang PH, Kim KH, Schermer M. Ethical Issues of Digital Twins for Personalized Health Care Service: Preliminary Mapping Study. J Med Internet Res 2022; 24:e33081. [PMID: 35099399 PMCID: PMC8844982 DOI: 10.2196/33081] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 10/27/2021] [Accepted: 11/16/2021] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND The concept of digital twins has great potential for transforming the existing health care system by making it more personalized. As a convergence of health care, artificial intelligence, and information and communication technologies, personalized health care services that are developed under the concept of digital twins raise a myriad of ethical issues. Although some of the ethical issues are known to researchers working on digital health and personalized medicine, currently, there is no comprehensive review that maps the major ethical risks of digital twins for personalized health care services. OBJECTIVE This study aims to fill the research gap by identifying the major ethical risks of digital twins for personalized health care services. We first propose a working definition for digital twins for personalized health care services to facilitate future discussions on the ethical issues related to these emerging digital health services. We then develop a process-oriented ethical map to identify the major ethical risks in each of the different data processing phases. METHODS We resorted to the literature on eHealth, personalized medicine, precision medicine, and information engineering to identify potential issues and developed a process-oriented ethical map to structure the inquiry in a more systematic way. The ethical map allows us to see how each of the major ethical concerns emerges during the process of transforming raw data into valuable information. Developers of a digital twin for personalized health care service may use this map to identify ethical risks during the development stage in a more systematic way and can proactively address them. RESULTS This paper provides a working definition of digital twins for personalized health care services by identifying 3 features that distinguish the new application from other eHealth services. On the basis of the working definition, this paper further layouts 10 major operational problems and the corresponding ethical risks. CONCLUSIONS It is challenging to address all the major ethical risks that a digital twin for a personalized health care service might encounter proactively without a conceptual map at hand. The process-oriented ethical map we propose here can assist the developers of digital twins for personalized health care services in analyzing ethical risks in a more systematic manner.
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Affiliation(s)
- Pei-Hua Huang
- Department of Medical Ethics, Philosophy and History of Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands
| | - Ki-Hun Kim
- Department of Industrial Engineering, Pusan National University, Busan, Republic of Korea
| | - Maartje Schermer
- Department of Medical Ethics, Philosophy and History of Medicine, Erasmus MC University Medical Center, Rotterdam, Netherlands
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Basza M, Krzowski B, Balsam P, Grabowski M, Opolski G, Kołtowski L. An Apple Watch a day keeps the doctor away? Cardiol J 2022; 28:801-803. [PMID: 34985118 PMCID: PMC8747830 DOI: 10.5603/cj.2021.0140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 08/05/2021] [Indexed: 11/25/2022] Open
Affiliation(s)
| | - Bartosz Krzowski
- 1st Department of Cardiology, Medical University of Warsaw, Poland
| | - Paweł Balsam
- 1st Department of Cardiology, Medical University of Warsaw, Poland
| | - Marcin Grabowski
- 1st Department of Cardiology, Medical University of Warsaw, Poland
| | - Grzegorz Opolski
- 1st Department of Cardiology, Medical University of Warsaw, Poland
| | - Lukasz Kołtowski
- 1st Department of Cardiology, Medical University of Warsaw, Poland.
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Ho WT, Yang YJ, Li TC. Accuracy of wrist-worn wearable devices for determining exercise intensity. Digit Health 2022; 8:20552076221124393. [PMID: 36081752 PMCID: PMC9445511 DOI: 10.1177/20552076221124393] [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: 08/08/2022] [Accepted: 08/08/2022] [Indexed: 11/15/2022] Open
Abstract
Objective As an indicator of exercise intensity, heart rate can be measured in a timely manner using wrist-worn devices. No study has attempted to estimate a target exercise intensity using wearable devices. The objective of the study was to evaluate the validity of prescribing exercise intensity using wrist-worn devices. Methods Thirty healthy subjects completed a maximal cardiopulmonary exercise test. Their heart rates were recorded using an electrocardiogram and two devices—Apple Watch Series 6 and Garmin Forerunner 945. Exercise intensity with the target heart rate was defined as resting heart rate + (maximal heart rate − resting heart rate) * n% ( n%: 40–60% for moderate-intensity exercise and 60–89% for vigorous-intensity exercise). Heart rate was analyzed at the lower and upper limits of each exercise intensity (HR40, HR60, and HR89). The mean absolute percentage error and concordance correlation coefficient were calculated, and Bland–Altman plots and scatterplots were constructed. Results Both devices showed a low mean absolute error (1.16–1.48 bpm for Apple and 1.35–2.25 for Garmin) and mean absolute percentage error (<1% for Apple and 1.16–1.39% for Garmin) in all intensities. A substantial correlation with electrocardiogram-measured heart rate was observed for moderate to vigorous intensity with concordance correlation coefficient > 0.95 for both devices, except that Garmin showed moderate correlation at the upper limit of vigorous activity with concordance correlation coefficient = 0.936. Moreover, Bland–Altman plots and scatterplots demonstrated a strong correlation without systematic error when the values obtained via the two devices were compared with electrocardiogram measurements. Conclusions Our findings indicate the high validity of exercise prescriptions based on the heart rate measured by the two devices. Additional research should explore other populations to confirm these findings.
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Affiliation(s)
- Wei-Te Ho
- Department of Physical Medicine and Rehabilitation, Cathay General Hospital, Taipei
- Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital
| | - Yi-Jen Yang
- Office of Physical Education, National Pingtung University of Science and Technology
| | - Tung-Chou Li
- Department of Physical Medicine and Rehabilitation, Cathay General Hospital, Taipei
- School of Medicine, Fu Jen Catholic University, New Taipei City
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Golbus JR, Pescatore NA, Nallamothu BK, Shah N, Kheterpal S. Wearable device signals and home blood pressure data across age, sex, race, ethnicity, and clinical phenotypes in the Michigan Predictive Activity & Clinical Trajectories in Health (MIPACT) study: a prospective, community-based observational study. Lancet Digit Health 2021; 3:e707-e715. [PMID: 34711377 DOI: 10.1016/s2589-7500(21)00138-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 06/10/2021] [Accepted: 06/23/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Wearable technology has rapidly entered consumer markets and has health-care potential; however, wearable device data for diverse populations are scarce. We therefore aimed to describe and compare key wearable signals (ie, heart rate, step count, and home blood pressure measurements) across age, sex, race, ethnicity, and clinical phenotypes. METHODS In the Michigan Predictive Activity & Clinical Trajectories in Health (MIPACT) prospective observational study, we enrolled participants from Michigan Medicine, Ann Abor, MI, USA, and followed them up for at least 90 days. Patients were included if they were aged 18 years or older, were fluent in English, owned an iPhone 6 or newer model with a supported iOS version, and had regular access to the internet throughout the study period. All participants were provided with an Apple Watch Series 3 or 4, an Omron Evolv Wireless Blood Pressure Monitor, and the MyDataHelps study smartphone application. Participants were asked to wear their watch for 12 h per day or longer and to do daily or weekly tasks, including home blood pressure measurements and breathing tasks. Heart rate, blood pressure, step counts, and distance walked were collected. The study was divided into two phases: an intensive 45-day collection phase (phase 1); and a 3-year longitudinal monitoring phase (phase 2). Here we report the first 90 days of data for all participants, which includes all of phase 1 and the first 45 days of phase 2. Participants' electronic health records were used to establish clinical diagnoses for analysis. FINDINGS We enrolled 6765 eligible participants between Aug 14, 2018, and Dec 19, 2019, of whom 6454 participants from Michigan Medicine completed the phase 1 study protocol and were included in this analysis (3482 [54%] women and 2972 [46%] men; 3657 [57%] participants were White, with 1094 [17%] Asian and 1090 [17%] Black participants). On days when participants wore their smart watches, median daily watch wear time was 15·5 h (IQR 14-17). Participants contributed a total of 1 107 320 blood pressure and 202 198 347 heart rate measurements over 90 days, with 172 (SD 50) blood pressure and 31 329 (SD 24 620) heart rate measurements per participant. Mean systolic blood pressure was 122 mm Hg (SD 10) and mean diastolic blood pressure was 77 mm Hg (SD 8), with 167 312 (15%) measurements having a systolic blood pressure higher than 140 mm Hg or diastolic blood pressure higher than 90 mm Hg. Mean resting heart rate was 64 beats per min (SD 8). Blood pressure and resting heart rate varied by sex, age, race, and ethnicity, with higher blood pressures in males and lower heart rate in participants aged 65 years or older (p<0·0001). Participants took 7511 steps per day (SD 2805) and walked 6009 metres per day (SD 2608), varying across demographic and clinical subgroups. INTERPRETATION These data could inform clinical trial design, interpretation of wearable data in clinical practice, and health-care interventions. FUNDING Apple, University of Michigan.
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Affiliation(s)
- Jessica R Golbus
- Division of Cardiovascular Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Nicole A Pescatore
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Brahmajee K Nallamothu
- Division of Cardiovascular Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Michigan Integrated Center for Health Analytics and Medical Prediction, University of Michigan, Ann Arbor, MI, USA; The Center for Clinical Management and Research, Ann Arbor VA Medical Center, MI, USA
| | - Nirav Shah
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Sachin Kheterpal
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
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Weng D, Ding J, Sharma A, Yanek L, Xun H, Spaulding EM, Osuji N, Huynh PP, Ogunmoroti O, Lee MA, Demo R, Marvel FA, Martin SS. Heart rate trajectories in patients recovering from acute myocardial infarction: A longitudinal analysis of Apple Watch heart rate recordings. CARDIOVASCULAR DIGITAL HEALTH JOURNAL 2021; 2:270-281. [PMID: 35265918 PMCID: PMC8890343 DOI: 10.1016/j.cvdhj.2021.05.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Background Using mobile health, vital signs such as heart rate (HR) can be used to assess a patient’s recovery process from acute events including acute myocardial infarction (AMI). Objective We aimed to characterize clinical correlates associated with HR change in the subacute period among patients recovering from AMI. Methods HR measurements were collected from 91 patients (4447 HR recordings) enrolled in the MiCORE study using the Apple Watch and Corrie smartphone application. Mixed regression models were used to estimate the associations of patient-level characteristics during hospital admission with HR changes over 30 days postdischarge. Results The mean daily HR at admission was 78.0 beats per minute (bpm) (95% confidence interval 76.1 to 79.8), declining 0.2 bpm/day (-0.3 to -0.1) under a linear model of HR change. History of coronary artery bypass graft, history of depression, or being discharged on anticoagulants was associated with a higher admission HR. Having a history of hypertension, type 2 diabetes mellitus (T2DM), or hyperlipidemia was associated with a slower decrease in HR over time, but not with HR during admission. Conclusion While a declining HR was observed in AMI patients over 30 days postdischarge, patients with hypertension, T2DM, or hyperlipidemia showed a slower decrease in HR relative to their counterparts. This study demonstrates the feasibility of using wearables to model the recovery process of patients with AMI and represents a first step in helping pinpoint patients vulnerable to decompensation.
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Affiliation(s)
- Daniel Weng
- Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jie Ding
- Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Apurva Sharma
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Lisa Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Biostatistics, Epidemiology, and Data Management Core Faculty, Baltimore, Maryland
| | - Helen Xun
- Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Erin M. Spaulding
- Johns Hopkins University School of Nursing, Baltimore, Maryland
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland
| | - Ngozi Osuji
- Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Pauline P. Huynh
- Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Oluseye Ogunmoroti
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Matthias A. Lee
- Johns Hopkins University Whiting School of Engineering, Baltimore, Maryland
| | - Ryan Demo
- Johns Hopkins University Whiting School of Engineering, Baltimore, Maryland
| | - Francoise A. Marvel
- Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Seth S. Martin
- Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Address reprint requests and correspondence: Dr Seth S. Martin, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Johns Hopkins Hospital, Carnegie 591, 600 N Wolfe St, Baltimore, MD 21287.
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Arakawa T. A Review of Heartbeat Detection Systems for Automotive Applications. SENSORS 2021; 21:s21186112. [PMID: 34577320 PMCID: PMC8469255 DOI: 10.3390/s21186112] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 09/07/2021] [Accepted: 09/08/2021] [Indexed: 01/16/2023]
Abstract
Many accidents are caused by sudden changes in the physical conditions of professional drivers. Therefore, it is quite important that the driver monitoring system must not restrict or interfere with the driver’s action. Applications that can measure a driver’s heartbeat without restricting the driver’s action are currently under development. In this review, examples of heartbeat-monitoring systems are discussed. In particular, methods for measuring the heartbeat through sensing devices of a wearable-type, such as wristwatch-type, ring-type, and shirt-type devices, as well as through devices of a nonwearable type, such as steering-type, seat-type, and other types of devices, are discussed. The emergence of wearable devices such as the Apple Watch is considered a turning point in the application of driver-monitoring systems. The problems associated with current smartwatch- and smartphone-based systems are discussed, as are the barriers to their practical use in vehicles. We conclude that, for the time being, detection methods using in-vehicle devices and in-vehicle cameras are expected to remain dominant, while devices that can detect health conditions and abnormalities simply by driving as usual are expected to emerge as future applications.
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Affiliation(s)
- Toshiya Arakawa
- Department of Information Technology and Media Design, Nippon Institute of Technology, Miyashiro-machi, Saitama 345-0826, Japan
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Chen K, Dandapani H, Guthrie KM, Goldberg E. Can Older Adult Emergency Department Patients Successfully Use the Apple Watch to Monitor Health? RHODE ISLAND MEDICAL JOURNAL (2013) 2021; 104:49-54. [PMID: 34323880 PMCID: PMC8519485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
OBJECTIVE To determine usability of the Apple Watch in older adult emergency department (ED) patients after a fall. METHODS We recruited older adults who fell and visited two urban EDs. They participated in an Apple Watch orientation and interviews on their experiences using the watch to complete varied tasks for 30 days. Interviews were recorded, transcribed, coded, and analyzed using framework analyses. RESULTS Eight participants (mean age 77.6 years) enrolled from November 2019 to March 2020. Participants reported being able to apply and charge the watch but struggled with navigating screens, monitoring charging status, and responding with de novo text messages. Many cited difficulties with advanced tasks, such as the study's app-based movement and memory activities. Experience with smartphones and caregiver assistance enhanced users' ability to complete tasks. CONCLUSIONS Older adults successfully performed basic Apple Watch functions. Family and community members may be necessary to assist with complex tasks.
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Affiliation(s)
- Kevin Chen
- Warren Alpert Medical School of Brown University, Providence, R
| | | | - Kate M Guthrie
- Brown University, School of Public Health; Warren Alpert Medical School of Brown University, Department of Psychiatry and Human Behavior, Providence, RI
| | - Elizabeth Goldberg
- Brown University, School of Public Health; Warren Alpert Medical School of Brown University, Department of Emergency Medicine, Providence, RI
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Changes in daily energy expenditure and movement behavior in unilateral vestibular hypofunction: Relationships with neuro-otological parameters. J Clin Neurosci 2021; 91:200-208. [PMID: 34373028 DOI: 10.1016/j.jocn.2021.07.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 06/10/2021] [Accepted: 07/06/2021] [Indexed: 11/22/2022]
Abstract
The vestibular system has been found to affect energy homeostasis and body composition, due to its extensive connections to the brainstem and melanocortin nuclei involved in regulating the metabolism and feeding behavior. The aim of this study was to evaluate - by means of a wrist-worn physical activity tracker and bioelectrical impedance analysis (BIA) - the energy expenditure (EE) in resting (REE) and free-living conditions and movement behavior in a group of chronic unilateral vestibular hypofunction (UVH) patients when compared with a control group (CG) of healthy participants. Forty-six chronic UVH and 60 CG participants underwent otoneurological (including video-Head Impulse Test [vHIT] for studying vestibulo-ocular reflex [VOR] and static posturography testing [SPT]), and EE and movement measurements and self-report (SRM) andperformance measures (PM). As well as significant (p < 0.001) changes in SPT variables (area and path length) and SRM/PM, UVH participants also demonstrated significantly (p < 0.001) lower values in REE, movement EE, hours/day spent upright, number of strides and distance covered and total daily EE (p = 0.007) compared to the CG. UVH patients consumed significantly lower Kcal/min in sweeping (p = 0.001) and walking upstairs and downstairs (p < 0.001) compared to the CG. Multiple correlations were found between free-living and resting EE and neuro-otological parameters in UVH participants. Since the melanocortin system could be affected along the central vestibular pathways as a consequence of chronic vestibular deafferentation, data collected by reliable wearables could reflect the phenomena that constitute an increased risk of falls and sedentary lifestyle for patients affected by UVH, and could improve rehabilitation stages.
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Sardana M, Lin H, Zhang Y, Liu C, Trinquart L, Benjamin EJ, Manders ES, Fusco K, Kornej J, Hammond MM, Spartano N, Pathiravasan CH, Kheterpal V, Nowak C, Borrelli B, Murabito JM, McManus DD. Association of Habitual Physical Activity With Home Blood Pressure in the Electronic Framingham Heart Study (eFHS): Cross-sectional Study. J Med Internet Res 2021; 23:e25591. [PMID: 34185019 PMCID: PMC8277303 DOI: 10.2196/25591] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 02/22/2021] [Accepted: 03/16/2021] [Indexed: 01/18/2023] Open
Abstract
Background When studied in community-based samples, the association of physical activity with blood pressure (BP) remains controversial and is perhaps dependent on the intensity of physical activity. Prior studies have not explored the association of smartwatch-measured physical activity with home BP. Objective We aimed to study the association of habitual physical activity with home BP. Methods Consenting electronic Framingham Heart Study (eFHS) participants were provided with a study smartwatch (Apple Watch Series 0) and Bluetooth-enabled home BP cuff. Participants were instructed to wear the watch daily and transmit BP values weekly. We measured habitual physical activity as the average daily step count determined by the smartwatch. We estimated the cross-sectional association between physical activity and average home BP using linear mixed effects models adjusting for age, sex, wear time, antihypertensive drug use, and familial structure. Results We studied 660 eFHS participants (mean age 53 years, SD 9 years; 387 [58.6%] women; 602 [91.2%] White) who wore the smartwatch 5 or more hours per day for 30 or more days and transmitted three or more BP readings. The mean daily step count was 7595 (SD 2718). The mean home systolic and diastolic BP (mmHg) were 122 (SD 12) and 76 (SD 8). Every 1000 increase in the step count was associated with a 0.49 mmHg lower home systolic BP (P=.004) and 0.36 mmHg lower home diastolic BP (P=.003). The association, however, was attenuated and became statistically nonsignificant with further adjustment for BMI. Conclusions In this community-based sample of adults, higher daily habitual physical activity measured by a smartwatch was associated with a moderate, but statistically significant, reduction in home BP. Differences in BMI among study participants accounted for the majority of the observed association.
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Affiliation(s)
- Mayank Sardana
- Department of Medicine, Division of Cardiology, University of California San Francisco, San Francisco, CA, United States
| | - Honghuang Lin
- Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Yuankai Zhang
- Boston University School of Public Health, Boston, MA, United States
| | - Chunyu Liu
- Boston University School of Public Health, Boston, MA, United States
| | - Ludovic Trinquart
- Boston University School of Public Health, Boston, MA, United States
| | - Emelia J Benjamin
- Department of Medicine, Boston University School of Medicine, Boston, MA, United States.,Boston University School of Public Health, Boston, MA, United States.,Framingham Heart Study, Framingham, MA, United States
| | | | - Kelsey Fusco
- Framingham Heart Study, Framingham, MA, United States
| | - Jelena Kornej
- Framingham Heart Study, Framingham, MA, United States
| | | | - Nicole Spartano
- Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | | | | | | | - Belinda Borrelli
- Henry M Goldman School of Dental Medicine, Center for Behavioral Science Research, Boston University, Boston, MA, United States
| | - Joanne M Murabito
- Department of Medicine, Boston University School of Medicine, Boston, MA, United States.,Framingham Heart Study, Framingham, MA, United States
| | - David D McManus
- Department of Medicine, UMass Medical School, Worcester, MA, United States
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Abstract
Background: Substance use disorders are a highly prevalent group of chronic diseases with devastating individual and public health consequences. Current treatment strategies suffer from high rates of relapse, or return to drug use, and novel solutions are desperately needed. Realize Analyze Engage (RAE) is a digital, mHealth intervention that focusses on real time, objective detection of high-risk events (stress and drug craving) to deploy just-in-time supportive interventions. The present study aims to (1) evaluate the accuracy and usability of the RAE system and (2) evaluate the impact of RAE on patient centered outcomes. Methods: The first phase of the study will be an observational trial of N = 50 participants in outpatient treatment for SUD using the RAE system for 30 days. Accuracy of craving and stress detection algorithms will be evaluated, and usability of RAE will be explored via semi-structured interviews with participants and focus groups with SUD treatment clinicians. The second phase of the study will be a randomized controlled trial of RAE vs usual care to evaluate rates of return to use, retention in treatment, and quality of life. Anticipated findings and future directions: The RAE platform is a potentially powerful tool to de-escalate stress and craving outside of the clinical milieu, and to connect with a support system needed most. RAE also aims to provide clinicians with actionable insight to understand patients’ level of risk, and contextual clues for their triggers in order to provide more personalized recovery support.
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