Abstract
Heart rate (HR) and HR variability (HRV) infer readiness to perform exercise in athletic populations. Technological advancements have facilitated HR and HRV quantification via photoplethysmography (PPG). This study evaluated the validity of WHOOP’s PPG-derived HR and HRV against electrocardiogram-derived (ECG) measures. HR and HRV were assessed via HR and HRV were assessed via WHOOP 2.0 and ECG over 15 opportunities during October–December 2018. WHOOP-derived pulse-to-pulse (PP) intervals were edited with WHOOP’s proprietary filter, in addition to various filter strengths via Kubios HRV software. HR and HRV (Ln RMSSD) were quantified for each filter strength. Agreement was assessed via bias and limits of agreement (LOA), and contextualised using smallest worthwhile change (SWC) and coefficient of variation (CV). Regardless of filter strength, bias (≤0.39 ± 0.38%) and LOA (≤1.56%) in HR were lower than the CV (10–11%) and SWC (5–5.5%) for this parameter. For Ln RMSSD, bias (1.66 ± 1.80%) and LOA (±5.93%) were lowest for a 200 ms filter and WHOOP’s proprietary filter, which approached or exceeded the CV (3–13%) and SWC (1.5–6.5%) for this parameter. Acceptable agreement was found between WHOOP- and ECG-derived HR. Bias and LOA in Ln RMSSD approached or exceeded the SWC/CV for this variable and should be interpreted against its own level of bias precision.
Highlights
Published: 20 May 2021Resting heart rate (HR) quantification and monitoring have been common in exercise physiology research and practice for centuries [1]
HR and HR variability (HRV) assessments that occur without a chest strap, such as photoplethysmography (PPG), are advantageous
With regard to WHOOP’s proprietary filter, trivial but statistically significant biases were found between WHOOP- and ECG-derived Ln RMSSD across both slow-wave sleep (SWS) quantification methods, and RMSSD during PSG-derived SWS, but not RMSSD during WHOOPderived SWS
Summary
Published: 20 May 2021Resting heart rate (HR) quantification and monitoring have been common in exercise physiology research and practice for centuries [1]. HRV has been used to infer training tolerance or readiness to perform exercise in athletes [4,5]. Advancements in HR monitor technology, namely the first wireless HR monitor [6], have facilitated frequent and accurate HR quantification. This technology is reliant on the wireless communication of the heart’s electrical activity from an elastic electrode chest strap to relevant receivers, and such reliance on chest straps can be inconvenient and problematic. Regarding HR and HRV assessment for the day-to-day monitoring of readiness to perform compliance is challenged by wearing a chest strap during daily recordings [7]. HR and HRV assessments that occur without a chest strap, such as photoplethysmography (PPG), are advantageous
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