IEEE Transactions on Biomedical Engineering, volume 68, issue 4, pages 1273-1281

Photoplethysmographic Waveform Analysis for Autonomic Reactivity Assessment in Depression

Spyridon Kontaxis ^{1, 2}

Eduardo Gil ^{3, 4}

Vaidotas Marozas ⁵

P. Castellví ^{3, 4}

Esther Garcia ⁶

Mar Posadas-de Miguel ⁷

Sara Siddi ⁸

Maria Luisa Bernal ⁷

Jordi Aguilo ⁶

Josep Maria Haro ⁹

Concepcion De la Camara ¹⁰

Pablo Laguna ^{3, 4}

Raquel Bailon ^{3, 4}

Show full list: 13 authors

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BSICoS group at the Aragón Institute of Engineering Research (I3A), Instituto de Investigación Sanitaria de Aragón (IIS Aragón), University of Zaragoza, Zaragoza, Spain |

CIBER in Bioengineering, Biomaterials & Nanomedicine (CIBER-BBN), Madrid, Spain |

BSICoS group at the Aragón Institute of Engineering Research (I3A), Instituto de Investigación Sanitaria de Aragón (IIS Aragón), University of Zaragoza |

⁴

CIBER in Bioengineering, Biomaterials & Nanomedicine (CIBER-BBN) |

⁵

Biomedical Engineering Institute and Department of Electronics Engineering, Kaunas University of Technology |

⁶

CIBER-BBN and Microelectronics and Electronic Systems Deptartment, Autonomous University of Barcelona |

⁷

IIS Aragón Zaragoza |

⁸

CIBER de Salud Mental

⁹

CIBER de Salud Mental and Parc Sanitari Sant Joan de Déu

¹⁰

IIS Aragón Zaragoza and CIBER de Salud Mental |

Publication type: Journal Article

Publication date: 2021-04-01

Institute of Electrical and Electronics Engineers (IEEE)

Journal: IEEE Transactions on Biomedical Engineering

scimago Q1

SJR: 1.239

CiteScore: 9.4

Impact factor: 4.4

ISSN: 00189294, 15582531

DOI: 10.1109/tbme.2020.3025908

Copy DOI

Biomedical Engineering

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 (

$A_{13}$

) in both HC and MDD group. However, autonomic reactivity indices related to

$A_{13}$

reached higher values in HC than in MDD subjects (Cohen's

${d=\!-0.81},{\,\text {AUC}=0.74}$

), implying that the stress response in depressed patients is reduced. A statistically significant (

$p \,<\, 0.001$

) negative correlation (

$r=-0.5$

) between depression severity scores and

$A_{13}$

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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Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Journal

IEEE Transactions on Biomedical Engineering

scimago Q1

SJR

1.239

CiteScore

9.4

Impact factor

4.4

ISSN

00189294 (Print)

15582531 (Electronic)

Photoplethysmographic Waveform Analysis for Autonomic Reactivity Assessment in Depression

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