Key result
Contactless pulse rate variability monitoring via video streams showed high agreement with ECG-derived heart rate variability during controlled respiratory maneuvers (spectral correlation ≥0.98).
Why the study?
The effectiveness of pulse rate variability measurement remains unclear during controlled breathing rates, which exert profound effects on autonomic nervous system balance.
Can contactless pulse rate variability (PRV) measured via video streams accurately reflect heart rate variability (HRV) during controlled respiratory maneuvers in healthy volunteers?
Observational
Can contactless pulse rate variability (PRV) measured via video streams accurately reflect heart rate variability (HRV) during controlled respiratory maneuvers in healthy volunteers?
Effect estimate: Correlation ≥0.98
Contactless PRV monitoring using standard video cameras provides a reliable surrogate for ECG-derived HRV during various controlled breathing rates.
Heart rate variability (HRV) is a noninvasive marker for the cardiovascular system and the substantial influence of this system on the autonomous nervous system (ANS). Contact and remote photoplethysmography (PPG) proved to be a reliable means of pulse rate variability (PRV) measurement as in wearable devices or imaging PPG using video cameras with evolved technical specifications. However, PRV effectiveness remains unclear during controlled breathing rate. Specifically, respiratory rate, among other physiological factors, applies profound effects on ANS balance. In this study, we demonstrated that PRV can be a reliable marker, as HRV, during various controlled breathing rates. We evaluated the proposed PRV monitoring study against reference HRV obtained from an ECG measurement device. PRV was measured from video streams captured using a smartphone and a webcam for the upper abdominal section of healthy volunteers while in standing position and performing six different respiratory maneuvers. We evaluated frequency and nonlinear HRV indices. Agreement between all indices was tested for camera-based devices and ground truth for all performed tasks. The agreement presented a consistent mean close to 95% limit of agreement (LoA). Also, we employed spectral analysis and measured the spectral divergences, normalized root mean squared error (NRMSE), and correlation. Kullback-Leibler Divergence median and percentiles results indicate congruent spectrums, where the maximum median was 0.18. A significant spectral correlation with minimum value of 0.98, and relatively low spectrum NRMSE of 0.24 were observed. Moreover, the results led to HRV physiological related phenomena which agreed with physiologically interpretations found in the literature.
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Shoushan et al. (2022) conducted an observational in Healthy. Contactless pulse rate variability (PRV) monitoring via video streams vs. ECG-derived heart rate variability (HRV) was evaluated on Agreement of frequency and nonlinear HRV indices between camera-based devices and ECG (Correlation ≥0.98). Contactless pulse rate variability monitoring via video streams showed high agreement with ECG-derived heart rate variability during controlled respiratory maneuvers (spectral correlation ≥0.98).
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