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New Measurement Analysis for Emotion Detection Using ECG Data

In: Information Systems and Neuroscience

Author

Listed:
  • Verena Dorner

    (Vienna University of Economics and Business)

  • Cesar Enrique Uribe Ortiz

    (Vienna University of Economics and Business
    Vienna University of Technology)

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.

Suggested Citation

  • Verena Dorner & Cesar Enrique Uribe Ortiz, 2022. "New Measurement Analysis for Emotion Detection Using ECG Data," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph & Gernot (ed.), Information Systems and Neuroscience, pages 219-227, Springer.
    • Handle: RePEc:spr:lnichp:978-3-031-13064-9_23
    DOI: 10.1007/978-3-031-13064-9_23
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