https://orcid.org/0000-0001-7730-5687
Figures
Abstract
Background
Cardiac rehabilitation (CR) is an evidence-based comprehensive program that includes exercise training, health education, physical activity promotion, and extensive counseling for the management of cardiovascular risk factors. Wearable devices monitor certain physiological functions, providing biometric data such as heart rate, movement, sleep, ECG analysis, blood pressure, energy expenditure, and numerous other parameters. Recent evidence supports wearable devices as a likely relevant component in cardiovascular risk assessment and disease prevention. The purpose of this scoping review is to better understand the role of wearable devices in home-based CR (HBCR) and to characterize the evidence regarding the incorporation of wearable devices in HBCR programs and cardiovascular outcomes.
Methods & findings
We created a search strategy for multiple databases, including PubMed, Embase (Elsevier), CINAHL (Ebsco), Cochrane CENTRAL (Wiley), and Scopus (Elsevier). Studies were included if the patients were eligible for CR per Medicare guidelines and >18 years of age and if some type of wearable device was utilized during HBCR. Our search yielded 57 studies meeting all criteria. The studies were classified into 4 groups: patients with coronary heart disease (CHD) without heart failure (HF); patients with HF; patients with heart valve repair or replacement; and patients with exposure to center-based CR. In three groups, there was an upward trend toward improvement in quality of life (QOL) and peak VO2, less sedentary time, and an increase in daily step count in the intervention groups compared to control groups.
Citation: Jones AK, Yan CL, Rivera Rodriquez BP, Kaur S, Andrade-Bucknor S (2023) Role of wearable devices in cardiac telerehabilitation: A scoping review. PLoS ONE 18(5): e0285801. https://doi.org/10.1371/journal.pone.0285801
Editor: Gianmarco Abbadessa, University of Campania Luigi Vanvitelli: Universita degli Studi della Campania Luigi Vanvitelli, ITALY
Received: March 31, 2023; Accepted: April 30, 2023; Published: May 31, 2023
Copyright: © 2023 Jones et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Cardiac rehabilitation (CR) is a personalized, evidence-based, and supervised comprehensive program that includes exercise training, health education, physical activity promotion, and extensive counseling for the management of cardiovascular risk factors [1]. Aside from being a relevant component for secondary prevention, it has been shown to reduce morbidity and mortality in certain cardiac conditions [2, 3]. The American Heart Association and American College of Cardiology guidelines assign a Class I indication for referral to CR for patients after an acute myocardial infarction, coronary revascularization (percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) surgery), chronic stable angina, and heart failure with reduced ejection fraction (HFrEF) [2, 3]. Referral after valve surgery and cardiac transplantation has also been shown to be beneficial [2, 3]. CR is covered for all the aforementioned indications by Medicare and Medicaid services, and it is even included in the consensus core set for cardiovascular performance measures as an area of future development [4]. Despite the strong recommendation for the referral of these patient groups, access to CR remains poor [1, 3]. The recent COVID-19 pandemic has further contributed to the reduction in access to CR programs [1]. Given these obstacles, research around telerehabilitation programs has increased over the past few years.
As technology advances, it permeates all aspects of our lives and plays an increasingly important role in medicine. One such aspect is wearable devices or technology. Wearable devices refer to small electronic and mobile devices or computers with communication capabilities incorporated into gadgets, clothes, or even accessories, that can be worn on the human body. This technology has the ability to monitor certain physiological functions, providing biometric data such as heart rate, movement, sleep, ECG analysis, blood pressure, energy expenditure, and numerous other parameters [5]. As such, studies have examined the use of wearable devices in movement disorders such as multiple sclerosis [6, 7]. Furthermore, recent evidence supports wearable devices as a likely relevant component in cardiovascular risk assessment and disease prevention [8]. CR has many barriers, including low attendance because of the inconveniences and costs associated with attending in-person sessions [8, 9]; however, the use of these devices has the potential to overcome these barriers and allow both affordable and reliable care from the comfort of the patient’s own home [3, 10]. Despite these promising initial results, there is still a need to further examine the role of wearable devices on a larger scale and to understand how their use can affect cardiovascular outcomes in patients who undergo CR.
The purpose of this scoping review is to better understand the role of wearable devices in home-based CR (HBCR) and to characterize the evidence regarding the incorporation of wearable devices in HBCR programs and cardiovascular outcomes. Because this technology is still novel and under development, it is relevant to identify its uses and limitations, so it can be more effectively integrated into CR programs in the future. The integration of wearable technology into CR has the potential to create more sustainable CR models that would narrow the gap in accessibility in underrepresented groups and low to mid-income areas.
Methods
We conducted a scoping review and worked closely with a librarian to ensure that we were following standard guidelines. A study protocol was published on OSF (https://osf.io/yvq2j/). This review aims to give researchers an overview of the role of wearable devices in HBCR. We chose our inclusion criteria based on Medicare guidelines and using a broad definition of a wearable device to ensure that we could provide a broad overview of this topic.
Inclusion criteria
Types of participants.
Studies were included if the patients were eligible for CR as per Medicare guidelines regardless of sex or ethnicity. Patients must have had at least one of the following conditions: acute myocardial infarction in the last 12 months, coronary artery bypass surgery, current stable angina, heart valve repair or replacement, coronary angioplasty or coronary artery stent, heart or a heart-lung transplant, and stable chronic heart failure. Studies of patients younger than 18 years old were excluded from the review.
Concept.
The core concept of this scoping review was to assess the use of wearable devices. Any study that utilized some type of wearable device during HBCR was eligible for inclusion. Wearable device was defined as any device that can be worn on any part of the body that has the capability of recording biometric data used as parameters for monitoring CR. Many wearable devices are associated with smartphone or web-based applications, and studies that include the usage of both the device and the application were eligible for inclusion. However, studies that solely use an application without a device were not eligible.
Context.
The context element of this scoping review is limited to CR that is home-based or at least with a home-based component. CR taking place in only a medical facility, either a rehabilitation center or inpatient, were not eligible either.
Types of evidence sources.
Primary research studies were included as the source of the information for this scoping review. Review articles such as systematic reviews and meta-analyses were reviewed for primary research studies but not included as a source of information in their entirety. Case reports, letters, abstracts, and opinion articles were excluded. We excluded any articles outside of English and Spanish languages where the translation was not available. Primary research studies were excluded if no results were reported.
Search strategy
Our search strategy consisted of three steps and searched health and science and multidisciplinary databases for published studies and reviews. The first step involved searching PubMed with a more limited strategy to identify additional keywords. Additionally, the results from these searches were analyzed using the Yale MeSH Analyzer (http://mesh.med.yale.edu). Next, a comprehensive search strategy was written for PubMed, peer-reviewed by a librarian, and adapted for other databases including Embase (Elsevier), CINAHL (Ebsco), Cochrane CENTRAL (Wiley), and Scopus (Elsevier). Fig 1 shows the PubMed search strategy. This search was modified and rerun as needed to ensure that all data sources were included. The final searches for each data base were run in March 2023.
The reference lists of studies were examined and extracted from the main databases by two authors. The extracted citations of the studies from the initial search were placed on Endnote and then uploaded to Covidence (https://app.covidence.org/) by one reviewer. Covidence eliminated duplicates. The initial search was only limited by language, only including articles either in Spanish or English or with an available translation.
Source of evidence selection
Selection of the titles and abstracts from the initial search was performed independently by five reviewers. For inclusion or exclusion of an article, two reviewers had to agree. If there were discrepancies in the study selection, a third reviewer made the final decision. After the initial evidence selection was finalized, the full text of all potentially eligible studies was read by four authors independently. The team met to discuss discrepancies and disagreements of the articles selected and reached a consensus by either the team or by a third party. Review articles that met inclusion criteria were not included as a whole but rather the individual studies from each review article were evaluated for inclusion or exclusion.
Data extraction
Data was extracted by four reviewers independently using a form that had been tested by the team before their use. The extracted data was then confirmed by a second reviewer.
Data items
Study and participant characteristic variables were collected and included the country the study was conducted, number of study participants, number of study participants who did not complete the study, study population, study design, CR phase, and participant age and sex. Furthermore, the type of wearable device, intervention description, intervention duration, control group description, study outcomes, and study results were collected.
Results
Fig 2 shows a PRISMA diagram [11] that demonstrates our study selection process. We searched five databases (PubMed, CINAHL, EMBASE, Cochrane Central, and SCOPUS). Covidence removed 12,276 duplicates leaving us with 21,061 articles to screen. We then screened titles and abstracts for relevance. In this initial screening process, 20,780 studies were removed. The full texts for the remaining 274 articles were reviewed to determine if they met eligibility criteria. At this point, 23 individual articles that met eligibility criteria from review articles were added. A total of 57 articles met our criteria.
We found 57 studies from 2003 to 2022, of which there were 44 randomized controlled trials, 9 cohort studies, and 2 non-randomized trials. There were four main group classifications:
- Patients with CHD without HF (n = 27)
- Patients with HF (n = 15) and
- Patients with exposure to center-based CR (n = 14)
- Patients with heart valve repair or replacement (n = 1)
Table 1 summarizes the study and participant characteristics of each study. The most studies were conducted in the United States at 8 studies [12–19], followed by 6 studies in Belgium [20–25]; 4 in Canada [17, 26–28], the Czech Republic [29–32], Japan [33–36], the Netherlands [37–40], and Poland [41–44]; 3 in China [45–47], and Spain [48–50]; 2 in Australia [51, 52], France [17, 53], Germany [49, 50], Iran [54, 55], Italy [56, 57], and New Zealand [58, 59]; and 1 in Denmark [60], Finland [61], Israel [62], Kenya [63], Korea [64], and Portugal [65]. Three studies were conducted across 3 different countries [17, 49, 50]. Of the 57 studies, 39 were conducted in phase 2 CR only, 16 in phase 3 CR only, and 2 in both CR phases 2 and 3 [13, 61]. The number of participants ranged from 5 [28] to 2331 [17]. The number of participants who did not complete the study ranged from 0 [26, 44, 52, 57, 66] to 150 [58] participants, translating to an incompletion rate of 0% to 92.6%. Three studies did not report a dropout rate [37, 19, 62]. The mean age of the study participants ranged from 54.17 [47]– 74 [36] years in intervention group and from 54.83 [47]– 70 [19] in the control group. Mean age was not reported in 3 studies [37, 46, 56], and 1 study did not report age for the control group [59]. Gender recruitment was significantly imbalanced. Most studies included >70% males compared to females. Three studies did not report gender breakdown [37, 56, 65] and 2 studies did not report gender breakdown for the control group [54, 65].
Table 2 summarizes the parameters and outcomes for each study. The common outcomes measured in these studies were cardiovascular (CV) risk factors, costs, daily steps, exercise capacity, physical activity (PA), psychological status, quality of life (QOL), and user experience. Psychological status was measured using various questionnaires for depression, anxiety, and self-efficacy such as the Hospital Anxiety and Depression Scale and General Self-Efficacy Scale. Similarly, QOL was measured using various questionnaires such as the SF-36 and HeartQol questionnaires. Nineteen studies mentioned risk factor outcomes with 7 reporting no difference between the two groups [20, 21, 27, 34, 40, 48, 50] and 2 reporting improved waist-hip circumference [58, 66]. The wearable devices used varied. Seventeen studies used heart rate monitors [15, 17, 20, 25, 26, 29–31, 37–40, 46, 47, 52, 56]. 10 used ECG monitors [12, 28, 34, 41–44, 48, 57, 64], 10 used pedometers [13, 18, 19, 33, 36, 51, 54, 55, 63, 67], 9 used accelerometers [21–24, 37, 53, 65, 66, 68], 7 used health watches [14, 16, 18, 35, 60–62], and 6 used other wearable sensors [27, 45, 49, 50, 58, 59].
Patients with CHD (without HF)
Most studies were conducted among patients with obstructive coronary artery disease, but 4 studies did not specifically include these patients [18, 27, 47, 68]. Out of the 27 studies in this group, 21 measured exercise capacity, 15 measured QOL, 8 measured PA/sedentary level or CV risk factors, 6 measured psychological status, 5 measured daily step count, 4 measured user acceptability/satisfaction, 2 measured cost/cost-effectiveness, and 1 measured rehospitalization.
Five studies noted improvement in peak VO2 in both groups [12, 29, 38, 39, 58], while 5 studies noted significant improvement in the intervention group [21, 31, 47, 54, 55], however, 2 studies noted no difference in peak VO2 between intervention and control group [27, 30]. Five studies noted QOL improvement in both groups [12, 29, 37, 38, 56], 3 studies noted QOL improvement in intervention group [45, 64, 68], while only one study noted QOL improvement in control group [48]. One study noted no change in QOL [14]. Intervention groups in 6 studies had a significant increase in daily steps from baseline and improvement in walking time and exercise habits [18, 30, 45, 57, 68, 69], while one study noted no significant change in daily steps [27]. Two studies found that HBCR was cost effective compared to center-based CR [56, 58]. In one study, 87% of patients reported that they would choose the intervention if available as part of usual care [59].
Patients with HF
Nine studies were conducted in patients with HF of any left ventricular ejection fraction (LVEF) [19, 21–23, 34, 35, 46, 63, 66], while six studies included patients with heart failure with reduced ejection fraction (LVEF ≤40%) only [17, 28, 41–44]. Nine studies had New York Heart Association (NYHA) classification criteria [17, 28, 35, 41–44, 46, 63], while 6 studies did not [19, 21–23, 34, 66].
Out of the 15 studies in this group, 11 measured exercise capacity; 9 measured QOL; 5 measured CV risk factors and/or hospitalization; 3 measured mortality, NYHA classification, PA, and/or psychological status; 2 measured adherence, cost-effectiveness, and/or daily step count; and 1 measured frailty, LVEF, patient activation, and/or resting heart rate.
Six studies noted significant improvement in peak VO2 in intervention group [21, 23, 41–44], and 6 studies noted significant improvement in QOL [21, 23, 28, 41–43, 46]. Two studies noted significant improvement in PA in the intervention group compared to the control [21, 23]. There was also a significant cost effectiveness in the intervention group compared to control group [21, 23]. Two studies noted significant reduction in composite CV mortality and heart failure hospitalization [17, 19], whereas another study noted no significant difference in either group [42].
Patients with exposure to center-based CR
Majority of these studies were conducted in patients with coronary heart disease and only 1 study included patients with heart failure [53]. All of the patients in these studies had exposure to center-based CR prior to starting HBCR. Out of the 14 studies in this group, 10 measured PA, 6 measured exercise capacity, 5 measured CV risk factors and/or daily step count, 4 measured QOL, 2 measured psychological status, and 1 measured LVEF, sedentary level, self-efficacy for PA, functional status, or training adherence.
Three studies noted improved peak VO2 in intervention group [16, 20, 50], while one study noted peak VO2 improvement in both groups [40]. Four studies noted no improvement in QOL in either group [20, 40, 50, 67]. Five studies noted significant PA improvement in the intervention group at the end of the intervention [16, 33, 51, 53, 61], while 2 studies noted no significant difference in the control or intervention group. In addition, 3 studies noted PA improvement at follow up [16, 25, 51]; however, one study noted no PA improvement at follow up in the control or intervention group [61]. The intervention group had a significant improvement or uptrend in daily step count [16, 33, 67], while there was no improvement in 2 studies [20, 61]. One study noted the intervention group had significant improvement in waist to hip ratio, compared to the center-based CR group that had an increase in sedentary time [65]. LVEF significantly improved in the intervention group, while no improvement or a decrease in LVEF was noted in the control group [50]. One study also noted there was no difference in adherence to training between different age groups of women compared to men [15].
Patients with heart valve repair or replacement
One study explored HBCR in patients after transaortic valve implantation (TAVI). Most patients were elderly (>80 years old) and 60% were men. The small cohort consistent of thirteen patients underwent HBCR with two different devices. By the end of the study, there was a large variability of physical activity between participants and a significant drop-out rate of 60%. Both physicians and patients faced many technical challenges during the intervention period. In this group of patients, HBCR was not feasible [58].
Overall, in three of the main study groups, there was a trend toward improvement in QOL and peak VO2, less sedentary time, and an increase in daily step count in the intervention groups compared to control groups.
Discussion
In this scoping review, the goal was to better understand the role wearable devices play in HBCR and to characterize the ways in which wearable devices have been used. In reviewing the articles that met the inclusion criteria, we found four main categories of studies: patients enrolled in HBCR for CHD (without HF); patients enrolled in HBCR for HF; patients who also had exposure to center-based CR; and patients enrolled in HBCR for heart valve repair or replacement. Except for patients with heart valve repair or replacement, each category had a substantial number of studies that met that criterion, allowing us to look at wearable devices in HBCR from both a more general and focused view.
Our study shows that there are many different wearable devices that can be utilized in CR. The most commonly used devices were heart rate monitors followed by ECG monitors and accelerometers. Pedometers and health watches were used slightly less frequently, and six studies [27, 45, 49, 50, 58, 59] mentioned another type of device. Regardless of the device used, HBCR seems to be an effective alternative to center-based CR. Despite the variable cost between devices, most studies showed they could be effectively used in HBCR [15, 52].
Of the 57 studies reviewed, only one had equal male and female representation [55]. Although CVD continues to be a leading cause of death for women, the CR referral rates for women are significantly lower than men [70]. Healthcare disparities between genders continues to be a significant obstacle for RCTs, and this review continues to emphasize this point. Therefore, statements about HBCR can only be generalized to men. More research regarding HBCR for women must be conducted.
Patients often express that adherence to CR is difficult because of barriers such as cost and lack of flexibility in scheduling [8, 9]. As such, HBCR is a desirable option to improve compliance. Our study demonstrates that HBCR is comparable to center-based CR in three patient groups. This is further supported by 44 of the 57 studies being RCTs. RCTs reduce selection bias of patients who might be more motivated to complete HBCR; thus, this further supports HBCR being a comparable option.
The duration of many of the studies in our review were less than three months. Only two studies reported 1 year follow-up data of previously published studies [25, 32]. Thus, more work should be done to follow patients over a longer period to see the long-term benefits and drawbacks of HBCR compared to center-based CR. With the current data, it is hard to make conclusions about the long-term sustainability of HBCR.
Additionally, a key component of CR is risk factor management and education [1]. In the studies that discussed CV risk factors, seven studies reported that there was no difference between the two groups. This shows that HBCR is as effective at managing risk factors as center-based CR further making the case that HBCR is a comparable option.
Patients with CHD (without HF)
Many of the studies included in this group compared HBCR to center-based CR. Center-based CR has proven to be effective at reducing cardiovascular risk factors, improving overall patient wellbeing, and QOL [1]. It is imperative that home-based interventions meet the same standards. As more studies are done regarding this topic, there is growing evidence in support of home-based methods as appropriate alternatives, providing patients with more flexibility and less expenses [1]. The studies that we reviewed correlated with these findings, as many studies found no differences between the two groups with both groups showing improvement in the respective measured outcomes. Of note, a few studies noted that the intervention group had a greater improvement in QOL than the control group [27, 45, 64, 68]. Thus, one may argue that this is a result of the flexibility of home-based interventions and their ability to fit more compatibly into one’s daily routine.
Patients with HF
Similarly to the CHD category, many of the studies in this subset compared home-based exercise interventions with usual care or centered-based CR and showed an increase in QOL, exercise capacity, and peak VO2 in the intervention group compared to the control group. Of note, two studies in this group focused on cost effectiveness [22, 23], and 5 studies focused CV readmission or CV hospitalization [17, 19, 22, 23, 42]. These outcomes were not as prevalently studied in the articles included in the other categories. Cost effectiveness was shown to be better in the intervention groups [22, 23], again making the case for expanding HBCR from an economic perspective. Furthering this economic argument, patients in the intervention groups also had decreased hospitalizations compared to the control groups [17, 22]. Thus, HBCR can be an effective way in saving healthcare costs.
Patients with exposure to center-based CR
In this subset of studies, most interventions involved PA monitoring after center-based CR. They then compared patients who were instructed to remotely monitor their PA with those who were in the usual care group. A majority of studies found that the intervention group had increased PA over time. It is important for patients to maintain the improvements that they make in center-based CR, and these studies make a case for the use of wearable devices for PA monitoring. If patients know that their data is being recorded, they may be more likely to continue their exercise regimen which leads to more long-term benefits.
Patients with heart valve repair or replacement
The only RCT exploring HBCR in post-TAVI patients had a very small cohort in an elderly population (>80 years old). Due to technical issues, there was a large percentage of the cohort who did not complete the study. As TAVI is becoming increasingly popular as one of the standards of care for severe aortic stenosis, more RCTs are required in this population to determine a real benefit for HBCR.
Limitations
As technology continues to advance, there are more and better wearable devices on the market that can be utilized during CR. This is an area of active research, and our review is a snapshot of the studies at the time that the search was conducted in March 2023. Additionally, the COVID-19 pandemic significantly changed how physicians and healthcare systems think about telemedicine and telerehabilitation. Although our search was conducted in early 2023, it may not reflect the full effect of the pandemic on how physicians approach CR. Lastly, because most of the patients evaluated in the included studies were males, there might be a lack of generalizability reflected in our results.
Conclusion
This review included 57 articles discussing the role of wearable devices in HBCR. These studies were divided into four main categories: patients with CHD without HF, patients with HF, patients with exposure to center-based CR, and patients with heart valve repair or replacement. Our study shows that wearable devices and HBCR can be a comparable alternative or adjunct to center-based CR for patients with CHD and HF. When comparing center-based CR and HBCR, HBCR leads to an improved QOL and peak VO2, less sedentary time, and an increase in daily step count. It is also more cost effective. More studies are needed to draw conclusions about the comparability of HBCR to center-based CR in patients with heart valve repair or replacement.
Supporting information
S1 Checklist. Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist.
https://doi.org/10.1371/journal.pone.0285801.s001
(PDF)
Acknowledgments
We would like to thank Barbara M. Sorondo, PhD, MLIS of the Louis Calder Memorial Library at the University of Miami Miller School of Medicine for consulting on the search strategy and review methodology. We would also like to thank Mikayla Bowen, BS of the University of Miami Miller School of Medicine for assisting with the abstract and title screening.
References
- 1. Taylor RS, Dalal HM, McDonagh STJ. The role of cardiac rehabilitation in improving cardiovascular outcomes. Nat Rev Cardiol. 2022;19(3):180–94. pmid:34531576
- 2. Thomas RJ, Balady G, Banka G, Beckie TM, Chiu J, Gokak S, et al. 2018 ACC/AHA Clinical Performance and Quality Measures for Cardiac Rehabilitation: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures. J Am Coll Cardiol. 2018;71(16):1814–37.
- 3. Thomas RJ, Beatty AL, Beckie TM, Brewer LC, Brown TM, Forman DE, 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. pmid:31097258
- 4.
CQMC Core Sets: Core Quality Measures Collaborative; Available from: https://www.qualityforum.org/cqmc/.
- 5. Ometov A, Shubina V, Klus L, Skibińska J, Saafi S, Pascacio P, et al. A survey on wearable technology: History, state-of-the-art and current challenges. Computer Networks. 2021;193:108074.
- 6. Sparaco M, Lavorgna L, Conforti R, Tedeschi G, Bonavita S. The Role of Wearable Devices in Multiple Sclerosis. Mult Scler Int. 2018;2018:7627643. pmid:30405913
- 7. Abbadessa G, Lavorgna L, Miele G, Mignone A, Signoriello E, Lus G, et al. Assessment of Multiple Sclerosis Disability Progression Using a Wearable Biosensor: A Pilot Study. J Clin Med. 2021;10(6). pmid:33802029
- 8. Bayoumy K, Gaber M, Elshafeey A, Mhaimeed O, Dineen EH, Marvel FA, et al. Smart wearable devices in cardiovascular care: where we are and how to move forward. Nature Reviews Cardiology. 2021;18(8):581–99. pmid:33664502
- 9. McMahon SR, Ades PA, Thompson PD. The role of cardiac rehabilitation in patients with heart disease. Trends Cardiovasc Med. 2017;27(6):420–5. pmid:28318815
- 10. Sana F, Isselbacher EM, Singh JP, Heist EK, Pathik B, Armoundas AA. Wearable Devices for Ambulatory Cardiac Monitoring: JACC State-of-the-Art Review. J Am Coll Cardiol. 2020;75(13):1582–92.
- 11. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Bmj. 2021;372:n71. pmid:33782057
- 12. Ades PA, Pashkow FJ, Fletcher G, Pina IL, Zohman LR, Nestor JR. A controlled trial of cardiac rehabilitation in the home setting using electrocardiographic and voice transtelephonic monitoring. Am Heart J. 2000;139(3):543–8. pmid:10689271
- 13. Chokshi NP, Adusumalli S, Small DS, Morris A, Feingold J, Ha YP, et al. Loss-Framed Financial Incentives and Personalized Goal-Setting to Increase Physical Activity Among Ischemic Heart Disease Patients Using Wearable Devices: The ACTIVE REWARD Randomized Trial. J Am Heart Assoc. 2018;7(12). pmid:29899015
- 14. Ding EY, Erskine N, Stut W, McManus DD, Peterson A, Wang Z, et al. MI-PACE Home-Based Cardiac Telerehabilitation Program for Heart Attack Survivors: Usability Study. JMIR Hum Factors. 2021;8(3):e18130. pmid:34255660
- 15. Dolansky MA, Stepanczuk B, Charvat JM, Moore SM. Women’s and men’s exercise adherence after a cardiac event: does age make a difference? Research in Gerontological Nursing. 2010;3(1):30–8.
- 16. Duscha BD, Piner LW, Patel MP, Craig KP, Brady M, McGarrah RW, 3rd, et al. Effects of a 12-week mHealth program on peak VO(2) and physical activity patterns after completing cardiac rehabilitation: A randomized controlled trial. Am Heart J. 2018;199:105–14. pmid:29754647
- 17. O’Connor CM, Whellan DJ, Lee KL, Keteyian SJ, Cooper LS, Ellis SJ, et al. Efficacy and safety of exercise training in patients with chronic heart failure: HF-ACTION randomized controlled trial. Jama. 2009;301(14):1439–50. pmid:19351941
- 18. Park LG, Elnaggar A, Lee SJ, Merek S, Hoffmann TJ, Von Oppenfeld J, et al. Mobile Health Intervention Promoting Physical Activity in Adults Post Cardiac Rehabilitation: Pilot Randomized Controlled Trial. JMIR Form Res. 2021;5(4):e20468. pmid:33861204
- 19. Jafri SH, Imran TF, Medbury E, Ursillo J, Ahmad K, Imran H, et al. Cardiovascular Outcomes of Patients Referred to Home Based Cardiac Rehabilitation. Heart Lung. 2022;52:1–7. pmid:34801771
- 20. Avila A, Claes J, Goetschalckx K, Buys R, Azzawi M, Vanhees L, et al. Home-Based Rehabilitation With Telemonitoring Guidance for Patients With Coronary Artery Disease (Short-Term Results of the TRiCH Study): Randomized Controlled Trial. J Med Internet Res. 2018;20(6):e225. pmid:29934286
- 21. Frederix I, Hansen D, Coninx K, Vandervoort P, Vandijck D, Hens N, et al. Medium-Term Effectiveness of a Comprehensive Internet-Based and Patient-Specific Telerehabilitation Program With Text Messaging Support for Cardiac Patients: Randomized Controlled Trial. J Med Internet Res. 2015;17(7):e185. pmid:26206311
- 22. Frederix I, Hansen D, Coninx K, Vandervoort P, Vandijck D, Hens N, et al. Effect of comprehensive cardiac telerehabilitation on one-year cardiovascular rehospitalization rate, medical costs and quality of life: A cost-effectiveness analysis. Eur J Prev Cardiol. 2016;23(7):674–82. pmid:26289723
- 23. Frederix I, Solmi F, Piepoli MF, Dendale P. Cardiac telerehabilitation: A novel cost-efficient care delivery strategy that can induce long-term health benefits. Eur J Prev Cardiol. 2017;24(16):1708–17. pmid:28925749
- 24. Frederix I, Van Driessche N, Hansen D, Berger J, Bonne K, Alders T, et al. Increasing the medium-term clinical benefits of hospital-based cardiac rehabilitation by physical activity telemonitoring in coronary artery disease patients. Eur J Prev Cardiol. 2015;22(2):150–8. pmid:24249840
- 25. Avila A, Claes J, Buys R, Azzawi M, Vanhees L, Cornelissen V. Home-based exercise with telemonitoring guidance in patients with coronary artery disease: Does it improve long-term physical fitness? Eur J Prev Cardiol. 2020;27(4):367–77. pmid:31787026
- 26. Lear SA, Singer J, Banner-Lukaris D, Horvat D, Park JE, Bates J, et al. Improving access to cardiac rehabilitation using the internet: a randomized trial. Stud Health Technol Inform. 2015;209:58–66. pmid:25980706
- 27. Prince SA, Reed JL, Cotie LM, Harris J, Pipe AL, Reid RD. Results of the Sedentary Intervention Trial in Cardiac Rehabilitation (SIT-CR Study): A pilot randomized controlled trial. Int J Cardiol. 2018;269:317–24. pmid:30072156
- 28. Tousignant M, Mampuya WM, Bissonnette J, Guillemette E, Lauriault F, Lavoie J, et al. Telerehabilitation with live-feed biomedical sensor signals for patients with heart failure: a pilot study. Cardiovasc Diagn Ther. 2019;9(4):319–27. pmid:31555536
- 29. Batalik L, Dosbaba F, Hartman M, Batalikova K, Spinar J. Benefits and effectiveness of using a wrist heart rate monitor as a telerehabilitation device in cardiac patients: A randomized controlled trial. Medicine (Baltimore). 2020;99(11):e19556. pmid:32176113
- 30. Batalik L, Konecny V, Dosbaba F, Vlazna D, Brat K. Cardiac Rehabilitation Based on the Walking Test and Telerehabilitation Improved Cardiorespiratory Fitness in People Diagnosed with Coronary Heart Disease during the COVID-19 Pandemic. Int J Environ Res Public Health. 2021;18(5). pmid:33668304
- 31. Batalik L, Pepera G, Papathanasiou J, Rutkowski S, Líška D, Batalikova K, et al. Is the Training Intensity in Phase Two Cardiovascular Rehabilitation Different in Telehealth versus Outpatient Rehabilitation? J Clin Med. 2021;10(18). pmid:34575185
- 32. Batalik L, Dosbaba F, Hartman M, Konecny V, Batalikova K, Spinar J. Long-term exercise effects after cardiac telerehabilitation in patients with coronary artery disease: 1-year follow-up results of the randomized study. Eur J Phys Rehabil Med. 2021;57(5):807–14. pmid:33619944
- 33. Izawa KP, Watanabe S, Omiya K, Hirano Y, Oka K, Osada N, et al. Effect of the self-monitoring approach on exercise maintenance during cardiac rehabilitation: a randomized, controlled trial. Am J Phys Med Rehabil. 2005;84(5):313–21. pmid:15829777
- 34. Kikuchi A, Taniguchi T, Nakamoto K, Sera F, Ohtani T, Yamada T, et al. Feasibility of home-based cardiac rehabilitation using an integrated telerehabilitation platform in elderly patients with heart failure: A pilot study. J Cardiol. 2021;78(1):66–71. pmid:33579602
- 35. Nagatomi Y, Ide T, Higuchi T, Nezu T, Fujino T, Tohyama T, et al. Home-based cardiac rehabilitation using information and communication technology for heart failure patients with frailty. ESC Heart Fail. 2022;9(4):2407–18. pmid:35534907
- 36. Saitoh M, Takahashi T, Morisawa T, Honzawa A, Yokoyama M, Abulimiti A, et al. Remote Cardiac Rehabilitation in Older Cardiac Disease: A Randomized Case Series Feasibility Study. Cardiol Res. 2022;13(1):57–64. pmid:35211224
- 37. Brouwers RWM, Kraal JJ, Regis M, Spee RF, Kemps HMC. Effectiveness of Cardiac Telerehabilitation With Relapse Prevention: SmartCare-CAD Randomized Controlled Trial. Journal of the American College of Cardiology. 2021;77(21):2754–6. pmid:34045031
- 38. Kraal JJ, Peek N, Van den Akker-Van Marle ME, Kemps HM. Effects of home-based training with telemonitoring guidance in low to moderate risk patients entering cardiac rehabilitation: short-term results of the FIT@Home study. Eur J Prev Cardiol. 2014;21(2 Suppl):26–31. pmid:25354951
- 39. Kraal JJ, Van den Akker-Van Marle ME, Abu-Hanna A, Stut W, Peek N, Kemps HM. Clinical and cost-effectiveness of home-based cardiac rehabilitation compared to conventional, centre-based cardiac rehabilitation: Results of the FIT@Home study. Eur J Prev Cardiol. 2017;24(12):1260–73. pmid:28534417
- 40. Snoek JA, Meindersma EP, Prins LF, Van’t Hof AW, de Boer MJ, Hopman MT, et al. The sustained effects of extending cardiac rehabilitation with a six-month telemonitoring and telecoaching programme on fitness, quality of life, cardiovascular risk factors and care utilisation in CAD patients: The TeleCaRe study. J Telemed Telecare. 2021;27(8):473–83. pmid:31760855
- 41. Piotrowicz E, Baranowski R, Bilinska M, Stepnowska M, Piotrowska M, Wójcik A, et al. A new model of home-based telemonitored cardiac rehabilitation in patients with heart failure: effectiveness, quality of life, and adherence. Eur J Heart Fail. 2010;12(2):164–71. pmid:20042423
- 42. Piotrowicz E, Pencina MJ, Opolski G, Zareba W, Banach M, Kowalik I, et al. Effects of a 9-Week Hybrid Comprehensive Telerehabilitation Program on Long-term Outcomes in Patients With Heart Failure: The Telerehabilitation in Heart Failure Patients (TELEREH-HF) Randomized Clinical Trial. JAMA Cardiol. 2020;5(3):300–8. pmid:31734701
- 43. Piotrowicz E, Zieliński T, Bodalski R, Rywik T, Dobraszkiewicz-Wasilewska B, Sobieszczańska-Małek M, et al. Home-based telemonitored Nordic walking training is well accepted, safe, effective and has high adherence among heart failure patients, including those with cardiovascular implantable electronic devices: a randomised controlled study. Eur J Prev Cardiol. 2015;22(11):1368–77. pmid:25261268
- 44. Smolis-Bąk E, Dąbrowski R, Piotrowicz E, Chwyczko T, Dobraszkiewicz-Wasilewska B, Kowalik I, et al. Hospital-based and telemonitoring guided home-based training programs: effects on exercise tolerance and quality of life in patients with heart failure (NYHA class III) and cardiac resynchronization therapy. A randomized, prospective observation. Int J Cardiol. 2015;199:442–7. pmid:26276068
- 45. Fang J, Huang B, Xu D, Li J, Au WW. Innovative Application of a Home-Based and Remote Sensing Cardiac Rehabilitation Protocol in Chinese Patients After Percutaneous Coronary Intervention. Telemed J E Health. 2019;25(4):288–93. pmid:30192210
- 46. Peng X, Su Y, Hu Z, Sun X, Li X, Dolansky MA, et al. Home-based telehealth exercise training program in Chinese patients with heart failure: A randomized controlled trial. Medicine (Baltimore). 2018;97(35):e12069. pmid:30170422
- 47. Song Y, Ren C, Liu P, Tao L, Zhao W, Gao W. Effect of Smartphone-Based Telemonitored Exercise Rehabilitation among Patients with Coronary Heart Disease. J Cardiovasc Transl Res. 2020;13(4):659–67. pmid:31820334
- 48. Bravo-Escobar R, González-Represas A, Gómez-González AM, Montiel-Trujillo A, Aguilar-Jimenez R, Carrasco-Ruíz R, et al. Effectiveness and safety of a home-based cardiac rehabilitation programme of mixed surveillance in patients with ischemic heart disease at moderate cardiovascular risk: A randomised, controlled clinical trial. BMC Cardiovasc Disord. 2017;17(1):66. pmid:28219338
- 49. Salvi D, Ottaviano M, Muuraiskangas S, Martínez-Romero A, Vera-Muñoz C, Triantafyllidis A, et al. An m-Health system for education and motivation in cardiac rehabilitation: the experience of HeartCycle guided exercise. J Telemed Telecare. 2018;24(4):303–16. pmid:28350282
- 50. Skobel E, Knackstedt C, Martinez-Romero A, Salvi D, Vera-Munoz C, Napp A, et al. Internet-based training of coronary artery patients: the Heart Cycle Trial. Heart Vessels. 2017;32(4):408–18. pmid:27730298
- 51. Butler L, Furber S, Phongsavan P, Mark A, Bauman A. Effects of a pedometer-based intervention on physical activity levels after cardiac rehabilitation: a randomized controlled trial. J Cardiopulm Rehabil Prev. 2009;29(2):105–14. pmid:19305235
- 52. Hannan AL, Hing W, Coombes JS, Gough S, Climstein M, Adsett G, et al. Effect of personal activity intelligence (PAI) monitoring in the maintenance phase of cardiac rehabilitation: a mixed methods evaluation. BMC Sports Sci Med Rehabil. 2021;13(1):124. pmid:34629086
- 53. Guiraud T, Granger R, Gremeaux V, Bousquet M, Richard L, Soukarié L, et al. Telephone support oriented by accelerometric measurements enhances adherence to physical activity recommendations in noncompliant patients after a cardiac rehabilitation program. Arch Phys Med Rehabil. 2012;93(12):2141–7. pmid:22813832
- 54. Dehghani M, Namdari M, Rafieian-Kopaei M, Baharvand-Ahmadi B, Mokhayeri Y, Namdari P, et al. Comparison of the effects of the time of home-based cardiac rehabilitation program on the changes in cardiometabolic risk factors in patients with phase-IV myocardial infarction: A randomized controlled trial. ARYA Atheroscler. 2022;18(1):1–9. pmid:36818148
- 55. Dehghani M, Cheraghi M, Namdari M, Roshan VD. Effects of Phase IV Pedometer Feedback Home-Based Cardiac Rehabilitation on Cardiovascular Functional Capacity in Patients With Myocardial Infarction: A Randomized Controlled Trial. Int J Basic Sci Med. 2019;4(2):75–80.
- 56. Marchionni N, Fattirolli F, Fumagalli S, Oldridge N, Del Lungo F, Morosi L, et al. Improved exercise tolerance and quality of life with cardiac rehabilitation of older patients after myocardial infarction: results of a randomized, controlled trial. Circulation. 2003;107(17):2201–6. pmid:12707240
- 57. Scalvini S, Zanelli E, Comini L, Tomba MD, Troise G, Giordano A. Home-based exercise rehabilitation with telemedicine following cardiac surgery. J Telemed Telecare. 2009;15(6):297–301. pmid:19720767
- 58. Maddison R, Rawstorn JC, Stewart RAH, Benatar J, Whittaker R, Rolleston A, et al. Effects and costs of real-time cardiac telerehabilitation: randomised controlled non-inferiority trial. Heart. 2019;105(2):122–9. pmid:30150328
- 59. Rawstorn JC, Gant N, Rolleston A, Whittaker R, Stewart R, Benatar J, et al. End Users Want Alternative Intervention Delivery Models: Usability and Acceptability of the REMOTE-CR Exercise-Based Cardiac Telerehabilitation Program. Arch Phys Med Rehabil. 2018;99(11):2373–7. pmid:30076800
- 60. Brocki BC, Andreasen JJ, Aaroe J, Andreasen J, Thorup CB. Exercise-Based Real-time Telerehabilitation for Older Adult Patients Recently Discharged After Transcatheter Aortic Valve Implantation: Mixed Methods Feasibility Study. JMIR Rehabil Assist Technol. 2022;9(2):e34819. pmid:35471263
- 61. Hakala S, Kivistö H, Paajanen T, Kankainen A, Anttila MR, Heinonen A, et al. Effectiveness of Distance Technology in Promoting Physical Activity in Cardiovascular Disease Rehabilitation: Cluster Randomized Controlled Trial, A Pilot Study. JMIR Rehabil Assist Technol. 2021;8(2):e20299. pmid:34142970
- 62. Nabutovsky I, Breitner D, Heller A, Scheinowitz M, Klempfner Y, Klempfner R. The First National Program of Remote Cardiac Rehabilitation in Israel-Goal Achievements, Adherence, and Responsiveness in Older Adult Patients: Retrospective Analysis. JMIR Cardio. 2022;6(2):e36947. pmid:36383410
- 63. Ngeno GTK, Barasa F, Kamano J, Kwobah E, Wambui C, Binanay C, et al. Feasibility of Cardiac Rehabilitation Models in Kenya. Ann Glob Health. 2022;88(1):7. pmid:35087707
- 64. Lee YH, Hur SH, Sohn J, Lee HM, Park NH, Cho YK, et al. Impact of home-based exercise training with wireless monitoring on patients with acute coronary syndrome undergoing percutaneous coronary intervention. J Korean Med Sci. 2013;28(4):564–8. pmid:23580444
- 65. Vieira ÁSdS, Cristina Damas Argel de Melo M, Andreia Raquel Santos Noites SP, Machado JP, Joaquim Gabriel MM. The effect of virtual reality on a home-based cardiac rehabilitation program on body composition, lipid profile and eating patterns: A randomized controlled trial. European Journal of Integrative Medicine. 2017;9:69–78.
- 66. Frith G, Carver K, Curry S, Darby A, Sydes A, Symonds S, et al. Changes in patient activation following cardiac rehabilitation using the Active(+)me digital healthcare platform during the COVID-19 pandemic: a cohort evaluation. BMC Health Serv Res. 2021;21(1):1363. pmid:34952575
- 67. Cupples M, Dean A, Tully MA, Taggart M, McCorkell G, O’Neill S, et al. Using pedometer step-count goals to promote physical activity in cardiac rehabilitation: a feasibility study of a controlled trial. Int J Phys Med Rehabil. 2013;1(7):1–5.
- 68. Devi R, Powell J, Singh S. A web-based program improves physical activity outcomes in a primary care angina population: randomized controlled trial. J Med Internet Res. 2014;16(9):e186. pmid:25217464
- 69. Chokshi N, Adusumalli S, Small D, Morris A, Feingold J, Ha Y, et al. Effect of loss-framed financial incentives and personalized goal-setting on physical activity among ischemic heart disease patients using wearable devices: The active reward randomized clinical trial. Journal of General Internal Medicine. 2018;33(2):176.
- 70. Colella TJ, Gravely S, Marzolini S, Grace SL, Francis JA, Oh P, et al. Sex bias in referral of women to outpatient cardiac rehabilitation? A meta-analysis. Eur J Prev Cardiol. 2015;22(4):423–41. pmid:24474091