Feature-level fusion of multimodal physiological signals for emotion recognition

Jing Chen, Bin Hu, Lixin Xu, Philip Moore, Yun Su

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

54 Citations (Scopus)

Abstract

Objective: This paper aims to use multimodal physiological signals to automatically recognize human emotions, and a novel multimodal feature fusion approach is proposed. Methods: In the proposed approach, significant multimodal features are selected respectively by two comparative feature selection methods: Fisher Criterion Score and Davies-Bouldin index. Emotion recognition is performed on the valence-arousal emotion space by using hidden Markov models (HMMs) and multimodal feature sets. Four physiological modalities, including electroencephalogram (EEG) from central nervous system and peripheral physiological signals (PERI) from peripheral nervous system as shown in the DEAP database, are employed. Results: We show the best recognition accuracies of 85.63% for arousal and 83.98% for valence. The proposed feature fusion approach is compared with decision-level fusion and non-fusion approaches on the same database; and the comparison demonstrates significant improvements in accuracy obtained by the feature fusion approach. Conclusion: Our work supports the observation that the proposed feature-level fusion approach represents a promising methodology for emotion recognition.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Editorslng. Matthieu Schapranow, Jiayu Zhou, Xiaohua Tony Hu, Bin Ma, Sanguthevar Rajasekaran, Satoru Miyano, Illhoi Yoo, Brian Pierce, Amarda Shehu, Vijay K. Gombar, Brian Chen, Vinay Pai, Jun Huan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages395-399
Number of pages5
ISBN (Electronic)9781467367981
DOIs
Publication statusPublished - 16 Dec 2015
Externally publishedYes
EventIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 - Washington, United States
Duration: 9 Nov 201512 Nov 2015

Publication series

NameProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015

Conference

ConferenceIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Country/TerritoryUnited States
CityWashington
Period9/11/1512/11/15

Keywords

  • emotion recognition
  • information fusion
  • multimodal physiological signals

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