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Article 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, = 0.055) or in between-day consistency of RHR (coefficient of variation: 6 ± 3% vs. 5 ± 3%, = 0.12; maximum between-day range of RHR=14 bpm). However, the median HR (71 ± 6 vs. 62 ± 7 bpm, = 0.001) and HR range (35 ± 6 vs. 23 ± 7 bpm, < 0.01) were significantly greater during sedentary versus sleep.
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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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12357026 | PMC |
| http://dx.doi.org/10.1177/20552076251367506 | DOI Listing |
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