ArticleDigital health
Measuring resting heart rate during daily life using wearable technology: Examining the impact of behavioral context and methodological criteria.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploiting Unsupervised Free-Living Data for Cardiorespiratory Fitness Estimation: Systematic Review and Meta-Analysis.JMIR mHealth and uHealth · 2026Pooled it
- Toward precision rehabilitation in adolescent mild traumatic brain injury: leveraging physiologic data from commercially available smartwatches to identify patient subgroups.medRxiv : the preprint server for health sciences · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Advances in the collection of high-quality, continuous electrocardiography (ECG) data via wearable technology have the potential to transform heart rate (HR) measurement in daily life. This study aimed to characterize the impact of methodological criteria and behavioral context on estimates of resting heart rate (RHR) to guide recommendations for a standardized approach to measure daily life RHR. Methods: Ten adults (9 female, 61 ± 12 years) wore a chest-mounted ECG device and wrist and ankle movement sensors continuously for 7-10 days. Following signal quality screening and beat-to-beat calculations, HR was analyzed using rolling averages of 15-, 30-, and 60-s windows within periods of device-detected sedentary behavior and sleep. ECG data during sedentary and sleep were compared for differences in: (1) RHR, (2) between-day consistency of daily RHR, and (3) HR median and range. Results: During sedentary and sleep, respectively, there was no difference in RHR (56 ± 7 vs. 54 ± 7 bpm, Conclusions: Behavioral context and method of analysis impact ECG-based HR measures at rest. This study recommends a novel wearable-based method for measuring daily life RHR that maximizes use of available data and confronts variability that exists with extended monitoring. Use of a standard method for measuring daily life RHR may advance the use of HR to inform clinical and/or personal health decisions.
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Registered trials
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