New Measurement Analysis for Emotion Detection Using ECG Data

Verena Dorner () and Cesar Enrique Uribe Ortiz ()
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Verena Dorner: Vienna University of Economics and Business
Cesar Enrique Uribe Ortiz: Vienna University of Economics and Business

A chapter in Information Systems and Neuroscience, 2022, pp 219-227 from Springer

Abstract: Abstract 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.

Keywords: ECG; Heart Rate Variability; Algorithm; Experiment (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-13064-9_23

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DOI: 10.1007/978-3-031-13064-9_23

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