Continuous wavelet filtering on webcam photoplethysmographic signals to remotely assess the instantaneous heart rate

Abstract

Photoplethysmographic signals obtained from a webcam are analyzed through a continuous wavelet transform to assess the instantaneous heart rate. The measurements are performed on human faces. Robust image and signal processing are introduced to overcome drawbacks induced by light and motion artifacts. In addition, the respiration signal is recovered using the heart rate series by respiratory sinus arrhythmia, the natural variation in heart rate driven by the respiration. The presented algorithms are implemented on a mid-range computer and the overall method works in real-time. The performance of the proposed heart and breathing rates assessment method was evaluated using approved contact probes on a set of 12 healthy subjects. Results show high degrees of correlation between physiological measurements even in the presence of motion. This paper provides a motion-tolerant method that remotely measures the instantaneous heart and breathing rates. These parameters are particularly used in telemedicine and affective computing, where the heart rate variability analysis can provide an index of the autonomic nervous system.

Using imaging photoplethysmography for heart rate estimation in non-human primates

“…Therefore we post-processed iPPG using three following steps, typical for iPPG signal processing [22, 25, 42, 43]. …”

Robust heart rate from fitness videos

“…Figure 3 exemplifies the snapshots of some recordings in our benchmark dataset. Since a skincontrasting background is used in the setup, we apply a simple thresholding method in YCrCb space (Bousefsaf et al 2013) to detect and segment the skin-region across the video and save the temporal RGB traces of spatially averaged skin-pixels for processing. In this way, we ensure that the experimental results are minimally affected by non-rPPG techniques, and thus the essence of the proposed method is highlighted and the replication of the experiment is facilitated.…”

Single-Trial Analysis of Inter-Beat Interval Perturbations Accompanying Single-Switch Scanning: Case Series of Three Children With Severe Spastic Quadriplegic Cerebral Palsy

“…At this stage the time series was irregularly sampled in accordance with the time positions of the blood volume pulse maxima. Thus, the inter-beat interval time series was further processed by cubic spline interpolation [28] followed by resampling of the regression curve, so that the derived signals were continuous and shared a common sampling rate.…”

“…First, the blood volume pulse waveform was detrended, denoised and filtered in the continuous wavelet domain using the Morlet mother wavelet [28] in order to attenuate the effects of sensor noise and motion artifacts. Only wavelet coefficients at scales corresponding to the frequency band of 60-200 beats per minute were retained and used to reconstruct a filtered version of the signal in the time domain [28]. This range encompasses typical heart rates for children with cerebral palsy [29].…”