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Abstract

Background

Advancements in digital health technologies (DHTs) hold promise for improving participation rates in home-based cardiac rehabilitation (HBCR). However, the current status of their application in the field of HBCR and existing knowledge gaps has remained unclear since 2019.

Methods

This review adheres to Arksey and O'Malley's framework for scoping reviews. PubMed, Web of Science, Embase, Cochrane Library, CINAHL, Scopus, IEEE Xplore, CNKI, Wanfang, and VIP databases were systematically searched from 2019 to 2025. Search results were reported following the PRISMA-ScR checklist. Descriptive analysis was employed to summarize and interpret the data.

Results

Twenty-two studies were included, conducted across Europe (n = 10), Asia (n = 6), North America (n = 5), and Oceania (n = 1). A total of 2996 participants were involved, with sample sizes ranging from 8 to 449. The intervention group had a mean age of 61.5 ± 10.1 years, mainly including patients with coronary artery disease (CAD), post-percutaneous coronary intervention (PCI), and post-coronary artery bypass graft (CABG). The core component of HBCR interventions was exercise training (n = 21), delivered primarily at home (n = 13) with multidisciplinary teams (n = 17) and targeting individual participants (n = 18). Intervention duration was typically 12 weeks, with follow-up periods ranging from 12 to 52 weeks. Seven studies utilized theories, models, or frameworks and two employed behavior change techniques. The DHTs utilized included mobile applications (15/22, 68%), smartwatches (10/22, 45%), accelerometers (8/22, 36.4%), interactive web-based portals (7/22, 32%), email/short message service (SMS) (7/22, 32%), heart rate monitors (4/22, 18%), activity trackers (3/22, 14%), pedometers (2/22, 9.1%), ECG monitors (2/22,9.1%),etc. Common outcomes encompassed physical activity, physiological indicators, psychological health, quality of life, safety, adherence, feasibility.

Conclusions

The application of DHTs in HBCR holds broad prospects and warrants further research. Future studies could focus on specific subgroups and high-risk populations to verify whether technology-assisted HBCR can be extended to more diverse cohorts and exert sustained positive impacts on broader health outcomes.

Keywords

Digital technology digital health wearable electronic devices cardiovascular diseases cardiac rehabilitation scoping review

Introduction

Noncommunicable diseases (NCDs), also known as chronic diseases, tend to be long-lasting and result from a combination of genetic, physiological, environmental, and behavioral factors. Cardiovascular diseases (CVDs) account for the majority of NCD-related deaths—at least 19 million in 2021—followed by cancers (10 million), chronic respiratory diseases (4 million), and diabetes (2 million).¹ CVDs are a group of disorders affecting the heart and blood vessels, including coronary heart disease, cerebrovascular disease, rheumatic heart disease, and other conditions.² Over four-fifths of CVD deaths are due to heart attacks and strokes, with one-third occurring prematurely in people under 70 years of age³; youths and young adults aged 15–39 years also constitute a significant proportion.⁴ Additionally, the global burden of CVD is projected to increase over the next few decades due to population aging.⁵

Cardiac rehabilitation (CR) is a comprehensive, multidisciplinary intervention grounded in evidence-based practice. It aims to improve exercise capacity, quality of life, and psychological well-being in patients with CVDs, while reducing incidence, hospitalization, disability, and mortality rates.^6–8 Core components include patient assessment, nutritional counseling, weight management and body composition monitoring, CVD and risk factor management, psychosocial support, aerobic exercise training, strength training, and physical activity counseling. CR programs involve a multidisciplinary team of clinicians, including physicians, nurses, clinical exercise physiologists, behavioral health experts, dietitians, physical and respiratory therapists, and other professionals, who collaborate to deliver these services.⁹

Although ample evidence supports the safety, effectiveness, and cost-effectiveness of CR, participation rates remain suboptimal,^10,11 particularly among women, older adults, ethnic or minority groups, patients with lower socioeconomic status, and those living in areas with limited CR programs.^6,12 Multiple barriers hinder the widespread implementation of CR, such as low patient motivation, environmental constraints, dietary habits conflicting with nutritional guidance, inadequate healthcare infrastructure, disparities in health literacy, and distance from CR centers, among others.¹³ Furthermore, limited interpersonal interactions, closure of sports facilities, and reorganization of clinical services during the COVID-19 pandemic may have reduced CR participation and disrupted exercise continuity.^14–17

To address these challenges, growing evidence supports home-based CR (HBCR) as an alternative or adjunct to center-based CR (CBCR). Cochrane systematic reviews have shown that HBCR(digital/telehealth platforms) and CBCR formally supported by healthcare professionals seem to be similarly effective in improving clinical and health-related quality of life outcomes in patients after myocardial infarction, or revascularisation, or with heart failure.¹⁸ HBCR can be delivered in homes, community centers, health clubs, or parks, with core components including patient assessment, exercise training, dietary/weight management, psychological support/management, medication adherence, and risk factor management. HBCR helps overcome geographic, logistical, and other access-related barriers. Moreover, it has the potential to expand and enhance patient education, counseling, and monitoring, as HBCR services are accessible 24/7, most CBCR programs typically limit face-to-face interactions between patients and staff to just 3–4 h per week.^19,20

Notably, the rapid advancement of digital health technologies (DHTs) in recent years—such as smartphone applications, smartwatches, fitness trackers, patches, and other wearable devices; non-wearable devices (e.g., blood pressure monitors, weight scales); text messaging (SMS); telemedicine; virtual reality (VR); and artificial intelligence (AI)—has further supported CR. These technologies can be used individually or in combination across various areas of cardiovascular health (e.g., wellness, cardio-metabolic risk, coronary disease, atrial fibrillation, heart failure, valve disease, mental/brain health, behavioral health, and cardiac/stroke rehabilitation), with applications ranging from maintaining well-being to pre-acute, acute, post-acute, and home care.^21,22 As defined by the U.S. Food and Drug Administration, DHTs are systems that use computing platforms, connectivity, software, and/or sensors for healthcare and related purposes. They often take the form of wearable devices, mobile applications, and internet-based tools.²³

A systematic review published by Wongvibulsin et al. in 2021 only summarized the applications of DHTs in CR from 1990 to 2018,²⁴ without focusing on the research progress of HBCR since 2019. Therefore, it is necessary to review original studies on the applications of DHTs in HBCR—with a specific focus on wearable devices and sensors, artificial intelligence—to propose targeted strategies for promoting HBCR adoption and participation, and to advance progress in this critical area of healthcare.

Methods

This scoping review adopts the methodological framework proposed by Arksey and O'Malley,²⁵ which was later advanced by Levac.²⁶ This framework comprises five stages: (1) identifying research questions, (2) identifying relevant studies, (3) research selection, (4) data visualization, and (5) organizing, summarizing, and reporting results.²⁶ The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist was used as a guideline for reporting the study results.²⁷ The protocol for this review has been published in the OSF registries(https://osf.io/2bwcs),with the registration DOI: 10.17605/OSF.IO/T584 M.

Identifying the research questions

To achieve the aims of the study, the following research questions were formulated:

In which countries or regions were these studies conducted?

What study designs were adopted?

What were the characteristics of the participants and sample size?

What were the components, intervention location, and delivery?

What were the duration, intensity, and follow-up time?

Was a multidisciplinary team used?

What was the dropout rate during the intervention and/or follow-up phases?

What TMFs, BCTs, and evidence-based resources were used?

What digital health technologies were used?

What were the outcome indicators and measurement tools?

Identifying relevant studies

A search was conducted from January 1, 2019, to January 11, 2025, using the following electronic databases: PubMed, Web of Science, Embase, Cochrane Library, CINAHL, Scopus, IEEE Xplore, CNKI, Wanfang, and VIP. Peer-reviewed journal articles written in English or Chinese were included. A comprehensive search strategy was developed and refined in collaboration with our research team. The following terms as example were used in the PubMed database:

(Heart disease* OR Heart disorder* OR Cardiac disease* OR Cardiac disorder* OR Cardiac event* OR Cardiovascular disease* OR Myocardial infarction OR Myocardial ischemia OR Coronary disease OR Coronary artery bypass OR Heart bypass OR Myocardial revascularization OR Heart failure OR Coronary* OR Myocard* OR Cardiac* OR Heart attack* OR Heart infarct* OR Angina OR CABG OR PTCA OR Postmyocardial*) AND (Cardiac rehabilitation OR Cardiovascular rehabilitation OR Home-based cardiac rehabilitation OR Home-based CR OR HBCR OR Hybrid CR OR Asynchronous CR OR Real-time audiovisual CR OR Virtual CR) AND (Smartphone OR Telephone OR Application OR Bluetooth OR text message OR SMS OR Smartwatch OR Wristband OR Activity tracker OR Accelerometer OR Sensor OR Virtual reality OR VR glasses OR AR glasses OR Apple Vision Pro OR Wearable electronic device OR e-Health OR Telemedicine OR Telehealth OR mHealth OR Digital health OR digital health technology OR DHT OR Artificial intelligence OR AI)

Study selection

Inclusion criteria: (1) participants are patients with CVDs aged ≥ 18 years; (2) study designs are experimental or observational; (3) studies involve the use of DHTs in HBCR with detailed descriptions of the technologies and their applications; and (4) interventions are delivered at home, community centers, health clubs, or parks.

Exclusion criteria: (1) reviews, editorials, study protocols, meeting abstracts, or qualitative studies; (2) duplicate publications; (3) inability to obtain the full text of the study; (4) studies not published in Chinese or English; and (5) studies with incomplete content required for this review.

Charting the data

All study abstracts were downloaded into NoteExpress (http://www.inoteexpress.com/aegean/) to remove duplicates. Titles and abstracts were independently and randomly screened by two reviewers, who categorized them as “include,” “exclude,” or “potentially include.” Conflicts were resolved by a third reviewer. Studies selected for full-text review were independently screened by two authors, with conflicts resolved through individual article discussions. A data extraction template was developed to extract relevant information from included articles, which was refined based on feedback from our research team. The following data categories were extracted for each article: authors, publication year, country, study design, participants, sample size, age, characteristics of the intervention group, control group, theory, evidence, devices, outcomes, and measurements.

Collating, summarizing and reporting the results

The data were extracted into a spreadsheet and analyzed using descriptive statistics; the characteristics of the included studies are presented in Supplementary Table 1.

Results

Search results

A total of 1027 studies were retrieved from ten databases, as illustrated in the PRISMA flowchart (Fig. 1). Altogether, 286 duplicates were removed, and 696 studies were excluded during the title and abstract screening process. A total of 45 full-text studies were retrieved and evaluated. Additionally, 2 studies were manually retrieved from reference lists. Ultimately, 22 studies met the inclusion criteria and were included in the review.

Figure 1.

PRISMA flowchart.

Study characteristics

Twenty-two studies were published from 2019 to 2024, conducted across various countries: the United Kingdom (n = 4), the United States (n = 3), China (n = 3), Canada (n = 2), Japan (n = 2), the Netherlands (n = 2), Australia (n = 1), Denmark (n = 1), Greece (n = 1), Israel (n = 1), Finland (n = 1), and Lithuania (n = 1). Most studies used randomized controlled trial/experimental designs (n = 12).

A total of 2996 participants were included in this study, with the sample size of individual studies ranging from 8 to 449. The intervention group had a mean age of 61.5 ± 10.1 years, and the main disease types/participant groups involved included coronary artery disease (CAD, n = 6/22), post-percutaneous coronary intervention (PCI, n = 6/22), post-coronary artery bypass graft (CABG, n = 6/22), CR participants/graduates (n = 5/22), myocardial infarction (MI, n = 5/22), coronary heart disease (CHD, n = 4/22), heart failure (HF, n = 3/22), valve repair/replacement (n = 2/22), and acute coronary syndrome (ACS, n = 2/22), among others.

The most common core component of HBCR interventions was exercise training (n = 21). Interventions were primarily delivered at home (n = 13) and involved multidisciplinary teams (n = 17), including physicians/cardiologists, nurse specialists/cardiac nurses, healthcare specialists, CR trainers, exercise specialists/instructors, rehabilitation therapists/physiotherapists, physiologists, psychologists, nutritionists, health coaches/instructors, social workers, graduate students, supervisors/facilitators, and healthcare assistants.

Intervention durations ranged from 6 to 50 weeks, with 11 studies lasting 12 weeks. Twelve studies did not include a follow-up period, while the remaining studies had follow-up periods of 12 to 52 weeks, with 5 studies lasting 24 weeks. Eight studies did not include a control group, and “usual care” was the most common intervention. Table 1 summarizes the intervention characteristics.

Table 1.

Summary of intervention characteristics.

Intervention characteristics	n(%)
Study design by JBI levels of evidence
Level 1 – RCT/Experimental Designs^28–38	12(54.5%)
Level 2 – Quasi-experimental Designs^39–41	3(13.6%)
Level 3 – Observational-Analytic Designs^42–48	7(31.9%)
Level 4 – Observational-Descriptive Studies	0(0%)
Level 5 – Expert Opinion and Bench Research	0(0%)
Intervention core component by HBCR
Exercise training^28–48	21(95.5%)
Exercise training + dietary management³¹	1(4.5%)
Intervention setting
Home^28–32^{,37–41,45,46,48}	13(59.1%)
Rehabilitation center + home^33,35	2(9.2%)
Hospital + home^34,44	2(9.2%)
Hospital or a local health centre⁴⁸	1(4.5%)
Home or in any convenient community facility⁴⁷	1(4.5%)
Home + community³⁶	1(4.5%)
Community⁴³	1(4.5%)
Outpatient community-based CR facilities⁴²	1(4.5%)
Who with
Individual only^28–30^{,32,33,35,37–41,44–49}	17(77.3%)
Group only^31,34,42,43	4(18.2%)
Individual + group³⁶	1(4.5%)
Delivery mode
Face to face^42,43	2(9.1%)
eHealth^29–35^{,38–41,45–47,49}	15(68.2%)
Face to face+ eHealth^{28,33,36,37,44,48}	5(22.7%)
Multidisciplinary team
Yes^28–31^{,33–41,43,46–48}	17(77.3%)
No^{29,32,42,44,45}	5(22.7%)
Intervention duration
6 weeks⁴²	1(4.5%)
8 weeks⁴³	1(4.5%)
12 weeks^{28,34,35,37–41}^,44,45,48	11(50.0%)
13 weeks⁴⁶	1(4.5%)
24 weeks^{29,31,32,47,49}	5(23.0%)
26 weeks³⁰	1(4.5%)
48 weeks³³	1(4.5%)
50 weeks³⁶	1(4.5%)
Follow up duration
Not followed up^{29,31,34,37,39–43}^,47–49	12(54.6%)
12 weeks^{32,35,38,44,45}	5(22.8%)
13 weeks⁴⁶	1(4.5%)
24 weeks^28,30	2(9.1%)
48 weeks³³	1(4.5%)
52 weeks³⁶	1(4.5%)

Theoretical foundation and BCTs

Among all included studies, only 7 studies (31.8%) reported using theories, models, and frameworks (TMFs), namely, intervention mapping (IM),²⁸ health action process approach (HAPA),⁴⁸ MRC complex intervention framework,⁴⁸ conceptual behavioral health theories (goal setting, implementation intentions),⁴⁹ Do something different approach,³² control theory,⁴⁶ trans-theoretical model (TTM), social cognitive theory (SCT), self-determination theory (SDT), theory of reasoned action (TRA), theory of planned behavior (TPB), information-motivation-behavioral skills (IMB), operant conditioning,⁴⁶ ecological perspective,³⁶ and health behavior change theory.³⁸ Two studies (9.1%) reported the use of BCTs, including action planning, social support, prompt, attention to action plans, self-monitoring, and positive reinforcement,⁴⁸ goals and planning, feedback and monitoring, shaping knowledge, repetition and substitution.⁴⁶

Digital health technologies available for HBCR

The DHTs used in the 22 studies can be roughly categorized into four types: (1) Mobile applications (15/22, 68%); (2) Interactive web-based portals (7/22, 32%); (3) Email/short message service (SMS) (7/22, 32%); and (4) Wearable devices and sensors, including smartwatches (10/22, 45%), accelerometers (8/22, 36.4%), heart rate monitor chest straps (4/22, 18%), activity trackers (3/22, 14%), pedometers (2/22, 9.1%), portable ECG monitors (2/22, 9.1%), and muscle oxygen monitors (1/22, 4.5%) (see Table 2).

Table 2.

Summary of digital health technologies in studies.

Digital health technologies	n(%)
Mobile applications^28–30^{,32,33,35,37,39–41,43,44,46,47,49}	15(68.0%)
Interactive web-based portals^29–31^,45–47,49	7(32.0%)
Email/SMS^{29,32,44–46}^,48,49	7(32.0%)
Wearable devices and sensors
·Smartwatches^{29,30,33,35,42–44}^,46,47,49	10(45.0%)
·Accelerometers^{32,33,35,36,38,42,45,48}	8(36.0%)
·Heart rate monitor chest straps^34,37,39,41	4(18.0%)
·Activity trackers^28,32,48	3(14.0%)
·Pedometers^31,36	2(9.1%)
·Portable ECG monitors^37,40	2(9.1%)
·Muscle oxygen monitors⁴¹	1(4.5%)

Note:Accelerometer is a hardware sensor component that only captures raw motion data. Activity tracker is an end device that uses accelerometer to process raw data into user-friendly activity metrics for daily health monitoring.

Outcomes and measurements

The 22 studies included in the review cover indicators related to physical activity, physiological indicators, psychological health, quality of life, safety, adherence, feasibility etc. Table 3 provides a summary of the most frequently reported outcomes and corresponding measurements.

Table 3.

Summary of outcomes and measurements.

Outcome Category	Specific Outcomes	Corresponding Measurements
Physical Activity	ST,step count,MVPA,LPA,VPA,6MWD/6MWT,ISWT,TUG,30-STS,VO₂ peak/VO₂ max,METs,muscle strength	accelerometer,smartwatch,activity tracker,pedometer,CPET system,App,daily log,IPAQ,GLTEQ
Physiological Indicators	HR,BP,BMI, WC, WHR,LVEF, CO, LVDd/LVDs,BNP, lipids, FBG, eGFR,FMD, CIMT	smartwatch,HR monitor,sphygmomanometer,echocardiography,ECG,weighing scale,venous blood sampling
Psychological Health	anxiety,depression,self-efficacy	HADS,GAD-7,PHQ-9,ESE
Quality of Life	HRQoL,disease burden	MLHFQ,HeartQoL,EQ-5D-3L/EQ-5D-5L/EQ-VAS,AQoL-6D,WHOQOL-BREF,KVL-H,SF-12,Bayliss Burden of Illness Measure
Safety	adverse events,non-elective hospital admissions,all-cause mortality	medical records(ED visit records),follow-up logs,researcher records,participant self-report
Adherence	exercise prescription adherence,text message adherence,diet adherence,wearing device adherence (≥10 h/day),usage frequency	attendance records,wearable devices and sensors data,audio-recorded session audits,web-based app logs
Feasibility	recruitment rate,retention rate,participant completion rate,data completeness,system usability,cost-effectiveness	·researcher records, flowcharts, coordinator time record form,wearable devices and sensors data logs, app usage records, SUS,resource use questionnaires,cost logs, medical consumption questionnaire, productivity cost questionnaire, valuation of informal care questionnaire,cost-effectiveness acceptability curve
Others	disease-related knowledge,self-management,behavior change	CADE-Q SV,PAM-13,SCHFI,RICAS-E2,EFS

Note: ST: Sedentary Time;MVPA: Moderate-to-Vigorous Physical Activity;LPA: Light Physical Activity;VPA: Vigorous Physical Activity;6MWD: 6-Minute Walking Distance;6MWT: 6-Minute Walking Test;ISWT: Incremental Shuttle Walk Test;TUG: Timed Up and Go;30-STS: 30-Second Sit-to-Stand;VO₂peak: Peak Oxygen Uptake;VO₂max: Maximal Oxygen Uptake;METs: Metabolic Equivalents;CPET: Cardiopulmonary Exercise Testing;IPAQ: International Physical Activity Questionnaire;GLTEQ: Godin Leisure-Time Exercise Questionnaire;HR: Heart Rate;BP: Blood Pressure;BMI: Body Mass Index;WC: Waist Circumference;WHR: Waist-Hip Ratio;LVEF: Left Ventricular Ejection Fraction;CO: Cardiac Output;LVDd: Left Ventricular End-Diastolic Diameter;LVDs: Left Ventricular End-Systolic Diameter;BNP: B-type Natriuretic Peptide;FBG: Fasting Blood Glucose;eGFR: Estimated Glomerular Filtration Rate;FMD: Flow-Mediated Dilation;CIMT: Carotid Intima-Media Thickness;HRQoL: Health-Related Quality of Life;MLHFQ: Minnesota Living with Heart Failure Questionnaire;EQ-5D-3L: EuroQol 5 Dimension 3 Level Questionnaire;EQ-5D-5L: EuroQol 5 Dimension 5 Level Questionnaire;EQ-VAS: EuroQol Visual Analogue Scale;AQoL-6D: Assessment of Quality of Life-6D;WHOQOL-BREF: World Health Organization Quality of Life Instrument-BREF;KVL-H: Dutch Version of the MacNew Heart Disease Health Related Quality of Life Questionnaire;SF-12: 12-Item Short Form Survey;HADS: Hospital Anxiety and Depression Scale;GAD-7: General Anxiety Disorder-7;PHQ-9: Patient Health Questionnaire-9;ESE: Exercise Self-Efficacy Scale;ED: Emergency Department;SUS: System Usability Scale;CADE-Q SV: Coronary Artery Disease Education Questionnaire-Short Version;PAM-13: Patient Activation Measure-13;SCHFI: Self-Care of Heart Failure Index;RICAS-E2: Readiness for Interpersonal Change Assessment Scale-Exercise 2;EFS: Edmonton Frailty Scale.

Discussion

This scoping review focuses on DHTs, particularly the application research of wearable devices and sensors, AI, and other related technologies in HBCR since 2019. By analyzing the characteristics of these studies, we derived several key findings: mobile applications still dominate the HBCR field, while wearable devices and sensors are increasingly used for remote monitoring of cardiovascular and physical activity objective indicators. However, only a few studies have reported indicators such as data accuracy, wearing adherence, and economic benefits; the application of AI in HBCR is extremely limited, as current practices still rely on remote or face-to-face guidance from multidisciplinary teams. The application of theories and BCTs is limited, making it difficult to explain the underlying mechanisms of intervention effectiveness. The core components of interventions are mainly focused on exercise training, lacking more comprehensive intervention elements.

HBCR has been recognized as a highly promising solution to narrow the accessibility gap of CR, particularly for populations in regions with inadequate medical resources; its advantages in breaking geographical barriers and reducing medical costs are more prominent.⁶ In the studies included in this review, the study populations were predominantly patients with CVDs, and highly concentrated in groups requiring prioritized rehabilitation interventions such as those post-percutaneous coronary intervention (PCI) and coronary artery bypass graft (CABG); the age structure of participants was dominated by middle-aged and elderly groups, with no studies led by young populations under 45 years old or elderly populations over 80 years old; the gender distribution is predominantly male, which may reflect insufficient attention to and inclusion of female populations in the studies; only a few studies focused on populations with low educational levels, unemployed individuals, retirees, and those in rural areas, indicating inadequate representation of vulnerable or geographically specific populations in the studies. Some of the included studies have small sample sizes, lack control groups, and are mainly descriptive studies or preliminary explorations. These limitations result in a relatively low overall level of evidence for current HBCR.

A systematic review indicated that among 31 studies utilizing digital technologies for CR, approximately one-third incorporated core CR components such as nutritional counseling, psychological management, and weight management.⁵⁰ However, the relevant interventions in this review still focus on exercise training, suggesting that multi-dimensional comprehensive interventions remain in an underdeveloped stage in HBCR. eHealth provides efficient support for home-based and individualized interventions, and over 70% of the studies involved multidisciplinary teams, which ensures the scientificity and safety of the interventions. The intervention duration is concentrated in the short-to-medium term, but nearly 60% of the studies lack follow-up, and the follow-up in the remaining studies is also mainly short-to-medium term. This indicates that current interventions mostly focus on the effects during the implementation phase, with insufficient tracking of patients’ long-term rehabilitation maintenance and the sustainability of effects, and the long-term management system still needs to be improved. At present, research on the ability of DHTs to continuously track and improve long-term clinical outcomes after the completion of interventions remains relatively limited.

In the past, telephone communication served as the primary mode of information transmission in HBCR. Nowadays, digital technologies have overcome the barriers of traditional CR and provided significant opportunities for improving its quality.²³ In this study, smartphone and tablet-based applications (Apps) have emerged as the dominant digital tools in HBCR, largely attributed to their convenience and functional integration that well meet the needs of home-based rehabilitation; smartwatches are the most widely used, followed by accelerometers, which is consistent with the core requirements of convenient monitoring and safe rehabilitation in home settings. A systematic review and network meta-analysis confirmed that wearable devices combined with smartphone Apps are the most effective intervention for improving peak oxygen uptake in remote medical CR for patients with CVD; smartphone Apps and instant messaging tools are the most effective interventions for improving compliance.⁵¹

The latest review indicated that with advancements in connectivity, computing power, and wearable technology, AI has demonstrated an emerging role in CR. It can be applied to data interpretation, risk stratification, decision support, personalized program development, and behavioral support—for example, recommending exercise goals based on wearable data or monitoring heart rate in real time to ensure the safety of home exercise.²³ Additionally, conversational AI holds enormous potential in the field of behavior modification. However, only 2 of the studies^32,46 included in this review adopted machine learning algorithms, integrating data from wearable and mobile devices to serve as the basis for personalized interventions—representing a promising direction for future research.

Intelligent wearable sensors, empowered by machine learning and innovative smart materials, enable rapid, accurate disease diagnosis, personalized therapy, and continuous health monitoring without disrupting daily life. This integration facilitates a shift from traditional, hospital-centered healthcare to a more decentralized, patient-centric model, where wearable sensors can collect real-time physiological data, provide deep analysis of these data streams, and generate actionable insights for point-of-care precise diagnostics and personalized therapy.⁵² However, some studies have also noted that although patients often use wearable devices in daily life, several factors limit their clinical use, including concerns about data accuracy, cost-effectiveness, privacy, regulatory and reimbursement policies, and a lack of specialized clinical staff to monitor, interpret, and respond to the large volume of data generated by these devices. In the future, a collaborative multidisciplinary approach involving patients, clinicians, scientists, policymakers, and industry leaders is needed to transform the digital health landscape and fully leverage the clinical benefits of wearable devices.⁵³

Behavior change techniques (BCTs) are widely referred to as the smallest, observable, and replicable active components within intervention programs. In 2013, Michie et al. released the first complete version of the “Behavior Change Techniques Taxonomy v1 (BCTTv1)”, which enables researchers to accurately describe, replicate, and evaluate interventions, thereby greatly advancing the scientific rigor and practical application of behavioral science.⁵⁴ Additionally, several prevalent theories, models, and frameworks exist, providing systematic processes for understanding and modifying behaviors.⁵⁵ Over the recent decades, research on how digital technologies influence health behaviors has increased significantly⁵⁶; however, in this study, only 2 studies explicitly reported the use of BCTs,^46,48 and merely one-third of the studies employed TMFs.^{28,29,32,36,38,46,48} This reflects a significant deficiency in the research regarding evidence-based theoretical guidance and precise facilitation of patients’ behavior change. Research indicates that closer collaboration and interaction between the fields of behavioral science and technology are required; ultimately, this may help enhance the effectiveness of digital technologies in modifying health behaviors and deepen the understanding of the relationship between behavior change strategies and persuasive techniques.⁵⁶

While quantitative studies have demonstrated that digital CR has emerged as a promising alternative to face-to-face cardiac rehabilitation, understanding patients’ experiences and perceptions can provide valuable insights into the success factors of these programs and identify opportunities for improvement.⁵⁷ A qualitative study indicated that digital cardiac rehabilitation provides patients with the knowledge, tools, and support necessary for rehabilitation, enhancing their sense of empowerment and control; however, limited opportunities for social interaction may pose challenges for patients seeking social support.⁵⁷ Integrating the findings of qualitative studies can deepen the understanding of the adoption mechanisms of interventions, which should be identified as a key research direction for future reviews.

Currently, the DHTs have brought revolutionary opportunities to HBCR, accompanied by several challenges: they may widen the digital divide, making it difficult for the elderly or vulnerable populations to use; device errors or data security risks may affect treatment efficacy and privacy; remote communication may weaken the doctor-patient emotional bond, with insufficient emergency response to sudden situations. Additionally, the impact of digital literacy and equitable access to cultural resources—especially among high-risk and vulnerable groups—remain pressing issues. Further research needs to focus on long-term outcomes to evaluate the safety, effectiveness, and cost-effectiveness of digital CR interventions. Digital health holds enormous potential in transforming CR and reducing the burden of CVDs, which is worthy of further investigation.^23,58

Limitations

Firstly, DHTs may appear in titles or abstracts as specific technologies or devices. Although we searched multiple databases, there remains a possibility of missing some studies. Secondly, this study did not rigorously evaluate or grade the methodological quality of included studies, which may lead to the inclusion of low-quality literature or overgeneralization of research conclusions. Thirdly, this study includes only Chinese and English literature, which may result in the omission of important research findings published in other languages. Fourthly, different data extractors may interpret the same literature differently. For complex studies, data classification and synthesis are challenging, potentially leading to classification errors or information loss. Fifthly, the search was limited to January of this year, meaning a large number of new studies in the field of digital technology may emerge after the completion of this review.

Conclusion

The DHTs provide enhanced support for the dissemination and participation of HBCR by offering flexible and scalable solutions. Although global research and applications in this field have grown consistently since 2019, digital interventions for CR still face multiple challenges that warrant further investigation. In the future, with the popularization of smartphones, advancement of communication technologies, progress in consumer-grade wearable devices and sensor technologies, and application of big data and AI, HBCR will ultimately be driven toward a more efficient, equitable, and personalized direction, providing more solid technical support for the long-term rehabilitation of patients with CVDs.

Supplemental Material

sj-pdf-1-dhj-10.1177_20552076261415922 - Supplemental material for Digital health technologies in home-based cardiac rehabilitation: A scoping review

Supplemental material, sj-pdf-1-dhj-10.1177_20552076261415922 for Digital health technologies in home-based cardiac rehabilitation: A scoping review by Rongrong Huang, Li Qiao, Xingyi Tang, Jianping Zhang, Sijia Li, Haoming Ma and Meihua Piao in DIGITAL HEALTH

Supplemental Material

sj-pdf-2-dhj-10.1177_20552076261415922 - Supplemental material for Digital health technologies in home-based cardiac rehabilitation: A scoping review

Supplemental material, sj-pdf-2-dhj-10.1177_20552076261415922 for Digital health technologies in home-based cardiac rehabilitation: A scoping review by Rongrong Huang, Li Qiao, Xingyi Tang, Jianping Zhang, Sijia Li, Haoming Ma and Meihua Piao in DIGITAL HEALTH

Footnotes

Acknowledgement

We acknowledge the funding provided by the National Key R&D Program of China (No.2025YFE0204500) and the Non-Profit Central Research Institute Fund of the Chinese Academy of Medical Sciences (No. 2023-RC320-01).

ORCID iDs

Rongrong Huang

Li Qiao

Jianping Zhang

Sijia Li

Haoming Ma

Meihua Piao

Ethics approval

Not applicable.

Author contributions

RR and L conceived of the scoping review and participated in the design. JP and SJ participated in screening literature, coding, and drafting the manuscript. XY,HM and MH participated in the revision of titles, abstracts, and reviews. All authors have contributed to manuscript refinement.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Chinese Academy of Medical Sciences, National Key R&D Program of China, (No.2023-RC320-01, No.2025YFE0204500).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Additional Notes

This manuscript has not been published previously, nor is it under consideration for publication elsewhere.

All authors have made substantial contributions to the work, approved the final version, and agree to be accountable for all aspects of the work.

Guarantor

MH and RR.

Supplemental material

Supplemental material for this study is available online.

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