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. 2021 Apr;68(4):1273-1281.
doi: 10.1109/TBME.2020.3025908. Epub 2021 Mar 18.

Photoplethysmographic Waveform Analysis for Autonomic Reactivity Assessment in Depression

Photoplethysmographic Waveform Analysis for Autonomic Reactivity Assessment in Depression

Spyridon Kontaxis et al. IEEE Trans Biomed Eng. 2021 Apr.

Abstract

Objective: In the present study, a photoplethysmographic (PPG) waveform analysis for assessing differences in autonomic reactivity to mental stress between patients with Major Depressive Disorder (MDD) and healthy control (HC) subjects is presented.

Methods: PPG recordings of 40 MDD and 40 HC subjects were acquired at basal conditions, during the execution of cognitive tasks, and at the post-task relaxation period. PPG pulses are decomposed into three waves (a main wave and two reflected waves) using a pulse decomposition analysis. Pulse waveform characteristics such as the time delay between the position of the main wave and reflected waves, the percentage of amplitude loss in the reflected waves, and the heart rate (HR) are calculated among others. The intra-subject difference of a feature value between two conditions is used as an index of autonomic reactivity.

Results: Statistically significant individual differences from stress to recovery were found for HR and the percentage of amplitude loss in the second reflected wave ( A13) in both HC and MDD group. However, autonomic reactivity indices related to A13 reached higher values in HC than in MDD subjects (Cohen's [Formula: see text]), implying that the stress response in depressed patients is reduced. A statistically significant ( ) negative correlation ( r=-0.5) between depression severity scores and A13 was found.

Conclusion: A decreased autonomic reactivity is associated with higher degree of depression.

Significance: Stress response quantification by dynamic changes in PPG waveform morphology can be an aid for the diagnosis and monitoring of depression.

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