CONTINUOUS monitoring of heart rate recovery (HRR) using wearable ECG technology can identify individuals at higher risk of cardiovascular and metabolic disorders, achieving an 86% accuracy in risk classification, according to a study published in the IEEE Journal of Health Informatics.
HRR, the time it takes for the heart to return to baseline rhythm after exercise, is a key indicator of autonomic nervous system function and cardiovascular health. Slower HRR has been linked to conditions such as heart failure, coronary artery disease, diabetes, hypertension, and sudden cardiac death. This study aimed to develop an accessible method for HRR assessment using wearable technology. Researchers at the University of Illinois Urbana-Champaign used a smart shirt equipped with an electrocardiogram (ECG) to collect data from 38 participants aged 20–76 during treadmill trials conducted in 2021. The device captured continuous cardiac signals, which were analysed using machine learning algorithms. Participants with HRR values of 28 beats per minute or below were classified as high-risk. The Support Vector Classifier (SVC) achieved an area under the curve (AUC) score of 86%, demonstrating the feasibility of wearable-based HRR monitoring. Interestingly, age did not emerge as a significant predictor of HRR, possibly due to lifestyle changes during the COVID-19 lockdown.
These findings hold promise for integrating wearable technology into routine clinical practice to improve cardiovascular risk assessment and early intervention. The ability to continuously monitor HRR through wearable devices could enable physicians to track patients’ heart health remotely, particularly in rural or underserved areas with limited access to advanced medical facilities. Future research should focus on expanding sample sizes, conducting longitudinal studies, and comparing HRR during exercise and rest to refine predictive models. Efforts should also aim at integrating wearable technology into standard healthcare workflows to ensure clinical applicability and actionable insights for early diagnosis and treatment planning.
Reference
Dogan A et al. Continuous heart rate recovery monitoring with ECG signals from wearables: identifying risk groups in the general population. IEEE Journal of Biomedical and Health Informatics. DOI:10.1109/JBHI.2025.3550092.
