Automatic Detection of Acute Mental Stress With Camera-based Photoplethysmography

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Abstract

Autonomic nervous system (ANS) activity reflects in vital signs that can be measured by means of camera-based photoplethysmography (cbPPG). This work investigates the automatic detection of acute mental stress with cbPPG.

Data from the Dresden Multimodal Biosignal Dataset for the Mannheim Multicomponent Stress Test (DMBD-MMST) covering > 40 h uncompressed facial RGB videos of 56 healthy participants were used for rest vs. stress classification on the basis of nine cbPPG vital signs with decision tree ensembles. Also, the impact of normalization, measurement duration, and color channel combination was investigated.

Best performance for rest (baseline and recovery) vs. stress classification (F1=0.81, Cohen's Kappa κ=0.61) was achieved with normalization, 30 s measurement duration, and vital signs from the green channel and the color channel combination called O3C. Without recovery (baseline vs. stress), this configuration achieved F1=0.97 and κ=0.94. Paired t-tests revealed significant changes from rest (baseline and recovery) to stress in eight of the nine vital signs and the maximum effect size amounted to d=0.73, indicating sympathetic excitation.

Findings from this work are central to the non-contact evaluation of ANS activity. Our results demonstrate that automatic detection of acute mental stress with cbPPG is feasible.

Details

Original languageEnglish
Title of host publicationComputing in Cardiology Conference (CinC)
PublisherIEEE
Number of pages4
Volume50
ISBN (electronic)9798350382525
Publication statusPublished - 26 Dec 2023
Peer-reviewedYes

Conference

Title50th Computing in Cardiology conference
Abbreviated titleCinC 2023
Conference number50
Duration1 - 4 October 2023
Website
Degree of recognitionInternational event
LocationEmory University
CityAtlanta
CountryUnited States of America

External IDs

Scopus 85182309956
ORCID /0000-0003-4012-0608/work/165451914

Keywords

Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards

Subject groups, research areas, subject areas according to Destatis

Sustainable Development Goals

Keywords

  • Mental stress, camera-based photoplethysmography, iPPG, non-contact measurement, stress assessment, stress detection