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

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. References E. B. Blackford, J. R. Estepp, and D. J. McDuff. Remote spectral measurements of the blood volume pulse with applications for imaging photoplethysmography. In G. L. Cote, editor, Optical Diagnostics and Sensing XVIII: Toward Point-of-Care Diagnostics, volume 10501, page 105010Z. International Society for Optics and Photonics, SPIE, 2018. doi:10.1117/12.2291073. M. Brayne. Trauma and Journalism: A Guide For Journalists, Editors and Managers. DART Center for Journalism and Trauma, 2007. https://dartcenter.org/sites/default/files/DCE_JournoTraumaHandbook.pdf. L. F. C. Martinez, G. Paez, and M. Strojnik. Optimal wavelength selection for noncontact reflection photoplethysmography. In Proceedings of the 22nd Congress of the International Commission for Optics: Light for the Development of the World, volume 8011, page 801191. International Society for Optics and Photonics, SPIE, 2011. doi:10.1117/12.903190. Y. Sun, S. Hu, V. Azorin-Peris, R. Kalawsky, and S. E. Greenwald. Noncontact imaging photoplethysmography to effectively access pulse rate variability. J. Biomed. Optics, 18(6):061205, 2013. doi:10.1117/1.JBO.18.6.061205. A. M. Unakafov. Pulse rate estimation using imaging photoplethysmography: generic framework and comparison of methods on a publicly available dataset. Biomed. Phys. Eng. Exp., 4(4):045001, 2018. doi:10.1088/2057-1976/aabd09