ArticleSensors (Basel, Switzerland)2017
Real-Time Monitoring in Home-Based Cardiac Rehabilitation Using Wrist-Worn Heart Rate Devices.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Heart Rate Monitors for the Estimation of Physical Activity in Patients With Cardiovascular Disease: Systematic Review.JMIR mHealth and uHealth · 2026Pooled it
- Efficacy of Phase II Remote Home Rehabilitation in Patients with Acute Myocardial Infarction after Percutaneous Coronary Intervention.Contrast media & molecular imaging · 2022Trial
- Effect of Smartphone-Based Telemonitored Exercise Rehabilitation among Patients with Coronary Heart Disease.Journal of cardiovascular translational research · 2020Trial
- Prescribed Rest Intervals in Home-Based Exercise Therapy and Rehabilitation: A Narrative Review and Conceptual Framework for Temporal Fidelity.Healthcare (Basel, Switzerland) · 2026Review
- Self-directed cardiac rehabilitation using a novel game-based mobile application paired with sensor: is it feasible?Singapore medical journal · 2026Article
- Leveraging Emerging Technologies to Expand Accessibility and Improve Precision in Rehabilitation and Exercise for People with Disabilities.International journal of environmental research and public health · 2024Review
- Continuous Monitoring of Health and Mobility Indicators in Patients with Cardiovascular Disease: A Review of Recent Technologies.Sensors (Basel, Switzerland) · 2023Review
- A Conceptual Model of Home-Based Cardiac Rehabilitation Exercise Adherence in Patients with Chronic Heart Failure: A Constructivist Grounded Theory Study.Patient preference and adherence · 2023Article
- UJAmI Location: A Fuzzy Indoor Location System for the Elderly.International journal of environmental research and public health · 2021Article
- Fuzzy Protoform for Hyperactive Behaviour Detection Based on Commercial Devices.International journal of environmental research and public health · 2020Article
- Accuracy of wearable heart rate monitors in cardiac rehabilitation.Cardiovascular diagnosis and therapy · 2019Article
- Current progress of photoplethysmography and SPOBiomedical engineering letters · 2019Review
- Smart Sensing Technologies for Personalised e-Coaching.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiac rehabilitation is a key program which significantly reduces the mortality in at-risk patients with ischemic heart disease; however, there is a lack of accessibility to these programs in health centers. To resolve this issue, home-based programs for cardiac rehabilitation have arisen as a potential solution. In this work, we present an approach based on a new generation of wrist-worn devices which have improved the quality of heart rate sensors and applications. Real-time monitoring of rehabilitation sessions based on high-quality clinical guidelines is embedded in a wearable application. For this, a fuzzy temporal linguistic approach models the clinical protocol. An evaluation based on cases is developed by a cardiac rehabilitation team.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.