New Measurement Analysis for Emotion Detection using ECG Data

Verena Dorner, Cesar Enrique Uribe Ortiz*

*Corresponding author for this work

Publication: Chapter in book/Conference proceedingContribution to conference proceedings


Electrocardiography (ECG) offers a lot of information that can be processed to make inferences about levels of arousal, stress, and emotions. One of the most popular measures is the Heart Rate Variability (HRV), a measure of the variation on the heart beats, which is only taken from one heart movement of the cardiac cycle, the R-wave. We explore the other heart movements of the cardiac cycle observed in the ECG with the aim of deriving new proxy measures for stress and arousal to enrich and complement HRV analysis. This article discusses existing approaches, suggests new measurements for stress and arousal detected in an ECG, and examines their potential to contribute new information based on their correlations with two HRV measures.
Original languageEnglish
Title of host publicationInformation Systems and Neuroscience
Subtitle of host publicationNeuroIS Retreat 2022
EditorsFred D. Davis, René Riedl, Jan vom Brocke, Pierre-Majorique Léger, Adriane B. Randolph, Gernot R. Müller-Putz
Place of PublicationCham
ISBN (Electronic)978-3-031-13064-9
ISBN (Print)978-3-031-13063-2
Publication statusPublished - 2022

Publication series

SeriesLecture Notes in Information Systems and Organisation


  • EEG
  • Heart Rate Variability
  • Algorithm
  • Experiment

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