Detecting stress from imaging photoplethysmography using high frame rate video and a yellow-green filter: A pilot study

Abstract

We investigate the use of a yellow-green filter to increase the signal-to-noise ratio (snr) in imaging photoplethysmography (iPPG) and test if high frame rate (HFR) video improves the accuracy of the derived heart rate variability (HRV). This pilot study is associated with a broader program to use iPPG to detect and monitor stress levels using HRV. To improve the snr of the iPPG signal, we employ two HFR colour video cameras of which one was fitted with a yellow-green filter (corresponding to the haemoglobin absorption peak within the visible spectrum). To our knowledge, the benefit of a yellow-green filter has never been explored. The predominant influence on HRV comes from the autonomic nervous system (ANS), which connects directly to the heart and cues the human body to relax or to stress. The linkage of HRV to the ANS makes HRV a proxy for stress levels. The HRV is derived from the iPPG signal by first using a cubic spline interpolation for more precise peak detection, and then calculating the inter-beat intervals from the peak-to-peak time differences. Instead of interpolating the signal, we hypothesise that a more accurate HRV measurement can be obtained using a HFR video camera, in our case at 200 frames per second.