JACIII Vol.26 No.1 pp. 58-66
doi: 10.20965/jaciii.2022.p0058


PPG Signal Morphology-Based Method for Distinguishing Stress and Non-Stress Conditions

Solaiman Ahmed*,†, Tanveer Ahmed Bhuiyan**, and Manabu Nii*

*Graduate School of Engineering, University of Hyogo
2167 Shosha, Himeji, Hyogo 671-2280, Japan

**Demant A/S
9 Kongebakken, Smorum 2765, Denmark

Corresponding author

September 1, 2021
November 2, 2021
January 20, 2022
signal quality index, cross-correlation coefficient, dynamic time warping, morphology
PPG Signal Morphology-Based Method for Distinguishing Stress and Non-Stress Conditions

PPG morphology based stress estimation process

In this study, the morphology of the PPG signal has been analyzed to be a potential cardiovascular marker for physiological stress. The morphology of the PPG signal was quantified as signal quality index by comparing the template beat (extracted from resting conditions) to the PPG beats recorded during vigorous physical activity. Data was taken from eight subjects where they performed some physical activities ranging from low to high intensity. It was found that, the mean and standard deviation of correlation coefficient between non-stress condition template beat and annotated PPG beat, 89.43±5.17 (%) and 44.23±10.48 (%) for non-stress and stress beat respectively with P value of 2.04*10-06 shows significantly difference between correlation coefficients (stress and non-stress). Whereas, mean and standard deviation of dynamic time warping correlation coefficients are 93.43±5.06 (%) and 85.93±4.18 (%) for non-stress and stress beat respectively with P value of .04. The morphology results corroborate the findings from the traditional HRV parameters generally used for stratifying stress.

Cite this article as:
Solaiman Ahmed, Tanveer Ahmed Bhuiyan, and Manabu Nii, “PPG Signal Morphology-Based Method for Distinguishing Stress and Non-Stress Conditions,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.1, pp. 58-66, 2022.
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Last updated on May. 20, 2022