Emotion recognition from physiological signals using multi-hypergraph neural networks

Junjie Zhu, Xibin Zhao, Han Hu, Yue Gao

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

19 Citations (Scopus)

Abstract

Emotion recognition from physiological signals is an effective way to discern the inner state of users. Existing works are lack in the exploration of latent correlation among multiple physiological signals and relationship among different subjects. To tackle this issue, we propose to recognize emotion from physiological signals using multi-hypergraph neural networks (MHGNN). In this method, the correlation among different subjects is formulated in the multi-hypergraph structure, where each type of physiological signal is used to generate one hypergraph. In each hypergraph, the hyperedges are used to represent the connections among the vertices (subject, stimuli). Thus, the emotion recognition task is modeled as classifying each vertex in the multi-hypergraph. Experimental results and comparisons with the state-of-the-art methods in the DEAP dataset demonstrate the superior performance of our method. The comparative experiments based on available biological knowledge verify that MHGNN can depict the real biological response process in a much more precise way.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Multimedia and Expo, ICME 2019
PublisherIEEE Computer Society
Pages610-615
Number of pages6
ISBN (Electronic)9781538695524
DOIs
Publication statusPublished - Jul 2019
Event2019 IEEE International Conference on Multimedia and Expo, ICME 2019 - Shanghai, China
Duration: 8 Jul 201912 Jul 2019

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
Volume2019-July
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Conference

Conference2019 IEEE International Conference on Multimedia and Expo, ICME 2019
Country/TerritoryChina
CityShanghai
Period8/07/1912/07/19

Keywords

  • Emotion recognition
  • Multi-hypergraph neural networks
  • Multi-modal fusion
  • Physiological signals

Fingerprint

Dive into the research topics of 'Emotion recognition from physiological signals using multi-hypergraph neural networks'. Together they form a unique fingerprint.

Cite this

Zhu, J., Zhao, X., Hu, H., & Gao, Y. (2019). Emotion recognition from physiological signals using multi-hypergraph neural networks. In Proceedings - 2019 IEEE International Conference on Multimedia and Expo, ICME 2019 (pp. 610-615). Article 8784727 (Proceedings - IEEE International Conference on Multimedia and Expo; Vol. 2019-July). IEEE Computer Society. https://doi.org/10.1109/ICME.2019.00111