JMIR Publications

ABSTRACT

Background:

Heart rate variability (HRV) is used to assess cardiac health and autonomic nervous system capabilities. With the growing popularity of commercially available wearable technologies, the opportunity to unobtrusively measure HRV via photoplethysmography (PPG) is an attractive alternative to gold standard electrocardiography (ECG). PPG measures blood flow within the vasculature using colour intensity [2]. However, PPG does not directly measure HRV, but rather pulse rate variability (PRV) [3]. Previous studies comparing consumer-grade PRV to HRV have demonstrated mixed results in short durations of activity under controlled conditions. Further research is required to determine the efficacy of PRV to estimate HRV during free-living conditions [4].

Objective:

The objectives of this study were to: (i) compare PRV estimates obtained from a consumer-grade PPG sensor with HRV measurements from a portable ECG during unsupervised free-living conditions, including sleep; (ii) examine factors influencing estimation, including measurement conditions and different filtering parameters to limit motion artifact.

Methods:

10 healthy adults were recruited. Data from a Microsoft Band 2 and a Shimmer3 ECG unit were recorded simultaneously via smartphone. Participants wore the devices for >90 minutes during typical day-to-day activities and while sleeping. After filtering, ECG data was processed using a combination of discrete wavelet transforms and peak-finding methods to identify R-peaks. PPG data was processed using a combination of published thresholding and filtering methods to attenuate motion artifact. A range of common HRV metrics were compared, including mean N-N, standard deviation of N-N intervals (SDNN), percent of subsequent differences >50 ms (pNN50), root mean square of successive differences (RMSSD), low (LF) and high frequency (HF) content, sympathovagal index (SVI). Validity was assessed using normalized root mean square error (nRMSE) and Pearson Correlation Coefficient (R2).

Results:

10 Day and 9 corresponding Night datasets were acquired. nRMSE was 0.14s (0.04) during the Day and 0.12s (0.06) at Night. R2 ranged from 0.21-0.48, with 2/19 (1 Day, 1 Night) considered strong, 4/19 (all Night) moderate, 5/19 (3 Day, 2 Night) fair, and 8 (6 Day, 2 Night) poor correlations. Filtering for motion artifact had a minimal impact on the accuracy of PRV measures. Significant HRV and PRV differences were found for LF during the Day and R-R, SDNN, pNN50, and LF at Night. For 8/9 matched Day and Night datasets, R2 values were higher at Night (P=0.08). P-P intervals were generally less sensitive to rapid R-R interval changes.

Conclusions:

Due to poor overall concurrent validity, and inconsistency among participant data, PRV was found to be a poor surrogate for HRV under free-living conditions. These findings suggest free-living HRV measurements would benefit from examining alternate sensing methods, such as multi-wavelength PPG and wearable ECG.