A more complete picture of emotion using electrocardiogram and electrodermal activity to complement cognitive data

Danushka Bandara, Stephen Song, Leanne M Hirshfield, Senem Velipasalar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We describe a method of achieving emotion classification using ECG and EDA data. There have been many studies conducted on usage of heart rate and EDA data to quantify the arousal level of a user [1–3]. Researchers have identified a connection between a person’s ECG data and the positivity or negativity of their emotional state [4]. The goal of this work is to extend this idea to human computer interaction domain. We will explore whether the valence/arousal level of a subject’s response to computer based stimuli is predictable using ECG and EDA, and whether or not that information can complement recordings of participants’ cognitive data to form a more accurate depiction of emotional state. The experiment consists of presenting three types of stimuli, both interactive and noninteractive, to 9 subjects and recording their physiological response via ECG and EDA data as well as fNIRS device. The stimuli were selected from validated methods of inducing emotion including DEAP dataset [5], Multi Attribute Task Battery [6] and Tetris video game [7]. The participants’ responses were captured using Self-Assessment Manikin [8] surveys which were used as the ground truth labels. The resulting data was analyzed using Machine Learning. The results provide new avenues of research in combining physiological data to classify emotion.

Original languageEnglish (US)
Title of host publicationFoundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience - 10th International Conference, AC 2016 and Held as Part of HCI International 2016, Proceedings
PublisherSpringer Verlag
Pages287-298
Number of pages12
Volume9743
ISBN (Print)9783319399546
DOIs
StatePublished - 2016
Event10th International Conference on Foundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience, AC 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016 - Toronto, Canada
Duration: Jul 17 2016Jul 22 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9743
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th International Conference on Foundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience, AC 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016
CountryCanada
CityToronto
Period7/17/167/22/16

Keywords

  • Arousal
  • Electrocardiography
  • Electrodermal activity
  • fNIRS
  • Human computer interaction
  • Valence

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Bandara, D., Song, S., Hirshfield, L. M., & Velipasalar, S. (2016). A more complete picture of emotion using electrocardiogram and electrodermal activity to complement cognitive data. In Foundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience - 10th International Conference, AC 2016 and Held as Part of HCI International 2016, Proceedings (Vol. 9743, pp. 287-298). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9743). Springer Verlag. https://doi.org/10.1007/978-3-319-39955-3_27