Analysis of Users' Emotions Through Physiology

Myroniv, Bohdan, Wu, Cheng-Wei, Ren, Yi ORCID: https://orcid.org/0000-0001-7423-6719 and Tseng, Yu-Chee (2017) Analysis of Users' Emotions Through Physiology. In: Genetic and Evolutionary Computing - Proceedings of the Eleventh International Conference on Genetic and Evolutionary Computing, ICGEC 2017, November 6-8, 2017, Kaohsiung, Taiwan. UNSPECIFIED, pp. 136-143.

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Abstract

Most of the existing studies focus on physical activities recognition, such as running, cycling, swimming, etc. But what affects our health, it is not only physical activities, it is also emotional states that we experience throughout the day. These emotional states build our behavior and affect our physical health significantly. Therefore, emotion recognition draws more and more attention of researchers in recent years. In this paper, we propose a system that uses off-the-shelf wearable sensors, including heart rate, galvanic skin response, and body temperature sensors to read physiological signals from the users and applies machine learning techniques to recognize their emotional states. We consider three types of emotional states and conduct experiments on real-life scenarios with ten users. Experimental results show that the proposed system achieves high recognition accuracy.

Item Type:	Book Section
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Smart Emerging Technologies
Depositing User:	LivePure Connector
Date Deposited:	02 Apr 2019 14:30
Last Modified:	24 Sep 2024 08:11
URI:	https://ueaeprints.uea.ac.uk/id/eprint/70447
DOI:	10.1007/978-981-10-6487-617

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