The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2023.0141147
PDF

Linear and Nonlinear Analysis of Photoplethysmogram Signals and Electrodermal Activity to Recognize Three Different Levels of Human Stress

Author 1: Yan Su
Author 2: Yuanyuan Li
Author 3: Shumin Zhang
Author 4: Hui Wang

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 11, 2023.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: All human beings experience different levels of psychological stress during their daily activities, and stress is an integral part of human life. So far, few studies have attempted to identify different levels of stress by analyzing physiological signals. However, it should be noted that developing a practical system for detecting multiple stress levels is a challenging task, and no standard system has been developed for this purpose. Therefore, in the current study, we propose a new detection system based on linear and nonlinear analysis of photoplethysmogram (PPG) and electrodermal activity (EDA) signals to classify three levels of stress (low, medium and high). In the current study, we recorded the physiological signals of EDA and PPG during three trials of a Stroop color word test that induced three levels of stress in 42 healthy male volunteers. Mean, median, standard deviation, variance, skewness, kurtosis, minimum, maximum, and RMS features in the time domain were calculated from physiological signals as linear features. Also, approximate entropy, sample entropy, permutation entropy, Hurst exponent, Katz fractal dimension, Higuchi fractal dimension, Petrosian fractal dimension, detrended fluctuation analysis (DFA), and embedding dimension and time delay parameters from phase space reconstruction of the signals were calculated as nonlinear features. The combination of nonlinear and linear features extracted from both PPG and EDA signals resulted in the highest mean accuracy (88.36%), intraclass correlation (ICC) (98.82%) and F1 (89.24%) values in the classification of three levels of mental stress through multilayer perceptron neural network. Our findings showed that the combination of nonlinear and linear approaches for biological data analysis (PPG and EDA) could help to develop a stress detection system.

Keywords: Stress detection; biological signal; linear analysis; nonlinear analysis; classification

Yan Su, Yuanyuan Li, Shumin Zhang and Hui Wang, “Linear and Nonlinear Analysis of Photoplethysmogram Signals and Electrodermal Activity to Recognize Three Different Levels of Human Stress” International Journal of Advanced Computer Science and Applications(IJACSA), 14(11), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0141147

@article{Su2023,
title = {Linear and Nonlinear Analysis of Photoplethysmogram Signals and Electrodermal Activity to Recognize Three Different Levels of Human Stress},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0141147},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0141147},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {11},
author = {Yan Su and Yuanyuan Li and Shumin Zhang and Hui Wang}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org