Centers for Medicare & Medicaid Services (CMS). Decision memo for cardiac rehabilitation programs - chronic HF (CAG-00372R) [Internet]. Medicare Coverage Database. 2024. https://www.cms.gov/medicare-coverage-database/view/ncacal-decision-memo.aspx?proposed=N&NCAId=164. Accessed July 2024.

Thomas RJ. Cardiac rehabilitation - challenges, advances, and the road ahead. N Engl J Med. 2024;390(9):830–41. https://doi.org/10.1056/NEJMra2302291

Turk-Adawi K, Supervia M, Lopez-Jimenez F, et al. Cardiac rehabilitation availability and density around the globe. EClinicalMedicine. 2019;13:31–45. https://doi.org/10.1016/j.eclinm.2019.06.007.

Article  PubMed  PubMed Central  Google Scholar 

Beatty AL, Truong M, Schopfer DW, et al. Geographic variation in cardiac rehabilitation participation in medicare and veterans affairs populations: opportunity for improvement. Circulation. 2018;137(18):1899–908. https://doi.org/10.1161/CIRCULATIONAHA.117.029471.

Article  PubMed  PubMed Central  Google Scholar 

Pack QR, Squires RW, Lopez-Jimenez F, et al. The current and potential capacity for cardiac rehabilitation utilization in the United States. J Cardiopulm Rehabil Prev. 2014;34(5):318–26.

Article  PubMed  Google Scholar 

IQVIA Institute. Digital health trends 2021 [Internet]. IQVIA. 2021. https://www.iqvia.com/-/media/iqvia/pdfs/institute-reports/digital-health-trends-2021/iqvia-institute-digital-health-trends-2021.pdf. Accessed July 2024.

Vogels EA. Home broadband and mobile use [Internet]. Pew Research Center; 2024 Jan 31. https://www.pewresearch.org/internet/wp-content/uploads/sites/9/2024/01/PI_2024.01.31_Home-Broadband-Mobile-Use_FINAL.pdf. Accessed July 2024.

Wang H, Ho AF, Wiener RC, Sambamoorthi U. The association of mobile health applications with self-management behaviors among adults with chronic conditions in the United States. Int J Environ Res Public Health. 2021;18(19):10351. https://doi.org/10.3390/ijerph181910351.

Article  PubMed  PubMed Central  Google Scholar 

Paradis S, Roussel J, Bosson JL, et al. Use of smartphone health apps among patients aged 18 to 69 years in primary care: population-based cross-sectional survey. JMIR Form Res. 2022;6(6). https://doi.org/10.2196/34882.

Meddar JM, Ponnapalli A, Azhar R, et al. A structured review of commercially available cardiac rehabilitation mHealth applications using the mobile application rating scale. J Cardiopulm Rehabil Prev. 2022;42(3):141–7. https://doi.org/10.1097/HCR.0000000000000667.

Article  PubMed  PubMed Central  Google Scholar 

Thomas RJ, Beatty AL, Beckie TM, et al. Home-based cardiac rehabilitation: a scientific statement from the American Association of Cardiovascular and Pulmonary Rehabilitation, the American Heart Association, and the American College of Cardiology. J Am Coll Cardiol. 2019;74(1):133–53. https://doi.org/10.1016/j.jacc.2019.03.008.

Article  PubMed  PubMed Central  Google Scholar 

U.S. Food and Drug Administration. Policy for device software functions and mobile medical applications: guidance for industry and Food and Drug Administration staff (Docket No. FDA-2011-D-0530) [Internet]. Center for Devices and Radiological Health and Center for Biologics Evaluation and Research. 2019. https://www.fda.gov/media/80958/download. Accessed July 2024.

Donevant SB, Estrada RD, Culley JM, et al. Exploring app features with outcomes in mHealth studies involving chronic respiratory diseases, diabetes, and hypertension: a targeted exploration of the literature. J Am Med Inf Assoc. 2018;25(10):1407–18. https://doi.org/10.1093/jamia/ocy104.

Article  Google Scholar 

Bostrom J, Sweeney G, Whiteson J et al. Mobile health and cardiac rehabilitation in older adults. Clin Cardiol. 2020;43(2):118–26. https://doi.org/10.1002/clc.23306.

Golbus JR, Lopez-Jimenez F, Barac A, Exercise, Cardiac Rehabilitation and Secondary Prevention Committee of the Council on Clinical Cardiology; Council on Lifelong Congenital Heart Disease and Heart Health in the Young; Council on Quality of Care and Outcomes Research; and Council on Cardiovascular and Stroke Nursing, et al. Digital technologies in cardiac rehabilitation: a science advisory from the American Heart Association. Circulation. 2023;148(1):95–107.

Article  PubMed  Google Scholar 

Coorey GM, Neubeck L, Mulley J, et al. Effectiveness, acceptability and usefulness of mobile applications for CVD self-management: systematic review with meta-synthesis of quantitative and qualitative data. Eur J Prev Cardiol. 2018;25:505–21.

Article  PubMed  Google Scholar 

Sim I. Mobile devices and health. N Engl J Med. 2019;381(10):956–68. https://doi.org/10.1056/NEJMra1806949.

Article  PubMed  Google Scholar 

Lu L, Zhang J, Xie Y et al. Wearable health devices in health care: narrative systematic review. JMIR Mhealth Uhealth. 2020;8(11). Published 2020 Nov 9. https://doi.org/10.2196/18907

Kasoju N, Remya NS, Sasi R, et al. Digital health: trends, opportunities and challenges in medical devices, pharma and biotechnology. CSI Trans ICT. 2023;11(1):11–30. https://doi.org/10.1007/s40012-023-00380-3.

Article  Google Scholar 

Dhingra LS, Aminorroaya A, Oikonomou EK, et al. Use of wearable devices in individuals with or at risk for CVD in the US, 2019 to 2020. JAMA Netw Open. 2023;6(6). https://doi.org/10.1001/jamanetworkopen.2023.16634.

Romagnoli S, Ripanti F, Morettini M, et al. Wearable and portable devices for acquisition of cardiac signals while practicing sport: a scoping review. Sens (Basel). 2023;23(6):3350. https://doi.org/10.3390/s23063350.

Article  Google Scholar 

Ruiz-Alias SA, Marcos-Blanco A, Clavero-Jimeno A, et al. Examining weekly heart rate variability changes: a comparison between monitoring methods. Sports Eng. 2022;25:7. https://doi.org/10.1007/s12283-022-00371-8.

Article  Google Scholar 

Quinn R, Leader N, Lebovic G et al. Accuracy of wearable heart rate monitors during exercise in sinus rhythm and atrial fibrillation. J Am Coll Cardiol. 2024;83(12):1177-9. https://doi.org/10.1016/j.jacc.2024.01.024.

Hosanee M, Chan G, Welykholowa K, et al. Cuffless single-site photoplethysmography for blood pressure monitoring. J Clin Med. 2020;9(3):723. https://doi.org/10.3390/jcm9030723.

Article  PubMed  PubMed Central  Google Scholar 

Freeberg KA, Baughman BR, Vickey T, et al. Assessing the ability of the Fitbit Charge 2 to accurately predict VO2max. Mhealth. 2019;5:39. https://doi.org/10.21037/mhealth.2019.09.07. Published 2019 Sep 23.

Article  PubMed  PubMed Central  Google Scholar 

Rodin D, Kirby M, Sedogin N, et al. Comparative accuracy of optical sensor-based wearable system for non-invasive measurement of blood glucose concentration. Clin Biochem. 2019;65:15–20. https://doi.org/10.1016/j.clinbiochem.2018.12.014.

Article  CAS  PubMed  Google Scholar 

Pipek LZ, Nascimento RFV, Acencio MMP, et al. Comparison of SpO2 and heart rate values on Apple Watch and conventional commercial oximeters devices in patients with lung disease. Sci Rep. 2021;11(1):18901. https://doi.org/10.1038/s41598-021-98453-3.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Rao P, Seshadri DR, Hsu JJ. Current and potential applications of wearables in sports cardiology. Curr Treat Options Cardiovasc Med. 2021;23(10):65. https://doi.org/10.1007/s11936-021-00942-1.

Article  PubMed  PubMed Central  Google Scholar 

Caillol T, Strik M, Ramirez FD, et al. Accuracy of a smartwatch-derived ECG for diagnosing bradyarrhythmias, tachyarrhythmias, and cardiac ischemia. Circ Arrhythm Electrophysiol. 2021;14(1). https://doi.org/10.1161/CIRCEP.120.009260.

Müller M, Hanssen TA, Johansen D, et al. Validity of a smartwatch for detecting atrial fibrillation in patients after heart valve surgery: a prospective observational study. Scand Cardiovasc J. 2024;58(1):2353069. https://doi.org/10.1080/14017431.2024.2353069.

Article  PubMed  Google Scholar 

Lee C, Lee C, Fernando C, Chow CM. Comparison of Apple Watch vs KardiaMobile: a tale of two devices. CJC Open. 2022;4(11):939–45. https://doi.org/10.1016/j.cjco.2022.07.011.

Article  PubMed  PubMed Central  Google Scholar 

Bent B, Goldstein BA, Kibbe WA, et al. Investigating sources of inaccuracy in wearable optical HR sensors. NPJ Digit Med. 2020;3:18. https://doi.org/10.1038/s41746-020-0226-6.

Article  PubMed  PubMed Central  Google Scholar 

Falter M, Scherrenberg M, Driesen K, et al. Smartwatch-based blood pressure measurement demonstrates insufficient accuracy. Front Cardiovasc Med. 2022;9:958212. https://doi.org/10.3389/fcvm.2022.958212.

Article  PubMed  PubMed Central  Google Scholar 

Fletcher GF, Ades PA, Kligfield P, et al. Exercise standards for testing and training: a scientific statement from the American Heart Association. Circulation. 2013;128(8):873–934. https://doi.org/10.1161/CIR.0b013e31829b5b44.

Article  PubMed  Google Scholar 

Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine. Gastrointest Endosc. 2020;92(4):807–12.

Article  PubMed  Google Scholar 

Tripoliti EE, Karanasiou GS, Kalatzis FG, et al. HEARTEN KMS - A knowledge management system targeting the management of patients with HF. J Biomed Inf. 2019;94:103203.

Article  Google Scholar 

Skobel E, Knackstedt C, Martinez-Romero A, et al. Internet-based training of coronary artery patients: the heart cycle trial. Heart Vessels. 2017;32(4):408–18. https://doi.org/10.1007/s00380-016-0897-8.

Article  PubMed  Google Scholar 

Balady GJ, Williams MA, Ades PA, et al. Core components of cardiac rehabilitation/secondary prevention programs: 2007 update: a scientific statement from the American Heart Association Exercise, Cardiac Rehabilitation, and Prevention Committee, the Council on Clinical Cardiology; the councils on Cardiovascular nursing, Epidemiology and Prevention, and Nutrition, Physical Activity, and metabolism; and the American Association of Cardiovascular and Pulmonary Rehabilitation. Circulation. 2007;115(20):2675–82. https://doi.org/10.1161/CIRCULATIONAHA.106.180945.

Article  PubMed