Analysis of physiological responses from multiple subjects for emotion recognition
Psychological disorders, including emotion and behavioral disorders, are common in the modern society. For example, previous studies by the New Zealand Mental Health Survey and the US National Co-morbidity Surveys (NCS), have found that the incidence of depression from ages 18 to 32 to be around 18%...
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sg-ntu-dr.10356-965042020-05-28T07:17:16Z Analysis of physiological responses from multiple subjects for emotion recognition Gu, Yuan Wong, Kai-Juan Tan, Su-Lim School of Computer Engineering IEEE International Conference on e-Health Networking, Applications and Services (14th : 2012 : Beijing, China) DRNTU::Engineering::Computer science and engineering Psychological disorders, including emotion and behavioral disorders, are common in the modern society. For example, previous studies by the New Zealand Mental Health Survey and the US National Co-morbidity Surveys (NCS), have found that the incidence of depression from ages 18 to 32 to be around 18%. Thus, there is a need to effectively monitor the emotional or affective states of these patients with psychological illness. Whilst real-time and continuous psychological monitoring systems are still not prevalent, the monitoring of physiological signals are made easier with mobile sensors that can be attached to the human body. These physiological signals can then be processed using an embedded processor to provide an alternative means for automatic emotion recognition. However, for such a system to be developed, the relationship between physiological and psychological signals has to be understood. This paper aims to address this by investigating the relationship between the emotional experiences from multiple subjects and their physiological responses, including the skin conductance, heart rate, respiration and movements of the facial muscles. In summary, preliminary evaluations described in this paper demonstrated that the heart rate, respiration, blood volume pulse and electromyography signals have an impact on the recognition rate achievable by the proposed multi-user physiological response-based emotion detection system. 2013-07-22T03:36:30Z 2019-12-06T19:31:32Z 2013-07-22T03:36:30Z 2019-12-06T19:31:32Z 2012 2012 Conference Paper Gu, Y., Wong, K.-J., & Tan, S.-L. (2012). Analysis of physiological responses from multiple subjects for emotion recognition. 2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom). https://hdl.handle.net/10356/96504 http://hdl.handle.net/10220/11940 10.1109/HealthCom.2012.6379388 en © 2012 IEEE. |
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DRNTU::Engineering::Computer science and engineering Gu, Yuan Wong, Kai-Juan Tan, Su-Lim Analysis of physiological responses from multiple subjects for emotion recognition |
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Psychological disorders, including emotion and behavioral disorders, are common in the modern society. For example, previous studies by the New Zealand Mental Health Survey and the US National Co-morbidity Surveys (NCS), have found that the incidence of depression from ages 18 to 32 to be around 18%. Thus, there is a need to effectively monitor the emotional or affective states of these patients with psychological illness. Whilst real-time and continuous psychological monitoring systems are still not prevalent, the monitoring of physiological signals are made easier with mobile sensors that can be attached to the human body. These physiological signals can then be processed using an embedded processor to provide an alternative means for automatic emotion recognition. However, for such a system to be developed, the relationship between physiological and psychological signals has to be understood. This paper aims to address this by investigating the relationship between the emotional experiences from multiple subjects and their physiological responses, including the skin conductance, heart rate, respiration and movements of the facial muscles. In summary, preliminary evaluations described in this paper demonstrated that the heart rate, respiration, blood volume pulse and electromyography signals have an impact on the recognition rate achievable by the proposed multi-user physiological response-based emotion detection system. |
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School of Computer Engineering |
author_facet |
School of Computer Engineering Gu, Yuan Wong, Kai-Juan Tan, Su-Lim |
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Conference or Workshop Item |
author |
Gu, Yuan Wong, Kai-Juan Tan, Su-Lim |
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Gu, Yuan |
title |
Analysis of physiological responses from multiple subjects for emotion recognition |
title_short |
Analysis of physiological responses from multiple subjects for emotion recognition |
title_full |
Analysis of physiological responses from multiple subjects for emotion recognition |
title_fullStr |
Analysis of physiological responses from multiple subjects for emotion recognition |
title_full_unstemmed |
Analysis of physiological responses from multiple subjects for emotion recognition |
title_sort |
analysis of physiological responses from multiple subjects for emotion recognition |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/96504 http://hdl.handle.net/10220/11940 |
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1681058839871356928 |