Heart Rate Variability and Electrodermal Activity Biosignal Processing: Predicting the Autonomous Nervous System Response in Mental Stress

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The study of the autonomous nervous system (ANS) has played an important role, over the last years, in prognostic and diagnostic of cardiac diseases, as well as, in the assessment of psychological stress. The most common techniques to evalute the balance of the ANS are invasive and unable to provide a continuous monitoring of the patients. The advances in technology and the development of wearable sensors have provided new alternative methods to study the ANS. The analysis of Heart Rate Variability (HRV) and Electrodermal Activity (EDA) are nonivasive methods to assess the ANS with wearables devices. The wearable device used provides information about HRV with the acquisition of photoplethysmography signals from the wrist and EDA from the fingers. The processing of the biosignals was performed by submitting the participants to a mental arithmetic stress test. The results showed that the participants exhibited two distinct response during stress - “Flight or Fight”. These responses were classified using machine-learning techniques. The constructed models were able to predict how the subjects will respond in a situation of stress, based only on baseline features. The accuracy of the models using only HRV baseline features was of approximately 80% and the accuracy using simultaneously HRV and EDA baseline features was of 77%, when assigning the correct response during stress to the participant.

Original languageEnglish
Title of host publicationBiomedical Engineering Systems and Technologies - 12th International Joint Conference, BIOSTEC 2019, Revised Selected Papers
EditorsAna Roque, Hugo Gamboa, Arkadiusz Tomczyk, Elisabetta De Maria, Felix Putze, Roman Moucek, Ana Fred
Place of PublicationCham
PublisherSpringer
Pages328-351
Number of pages24
ISBN (Electronic)978-3-030-46970-2
ISBN (Print)978-3-030-46969-6
DOIs
Publication statusPublished - 2020
Event12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019 - Prague, Czech Republic
Duration: 22 Feb 201924 Feb 2019

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume1211 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019
Country/TerritoryCzech Republic
CityPrague
Period22/02/1924/02/19

Keywords

  • Autonomous nervous system
  • Biosignals
  • Classification
  • Electrodermal activity
  • Heart rate variability
  • Machine-learning
  • Photoplethysmography
  • Wearable device

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