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Recognition of emotions in gait patterns by means of artificial neural nets

Janssen, Daniel, Schöllhorn, Wolfgang I., Lubienetzki, Jessica, Fölling, Karina, Kokenge, Henrike, & Davids, Keith W. (2008) Recognition of emotions in gait patterns by means of artificial neural nets. Journal of Nonverbal Behavior, 32(2), pp. 79-92.

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Abstract

This paper describes an application of emotion recognition in human gait by means of kinetic and kinematic data using artificial neural nets. Two experiments were undertaken, one attempting to identify participants’ emotional states from gait patterns, and the second analyzing effects on gait patterns of listening to music while walking. In the first experiment gait was analyzed as participants attempted to simulate four distinct emotional states (normal, happy, sad, angry). In the second experiment, participants were asked to listen to different types of music (excitatory, calming, no music) before and during gait analysis. Derived data were fed into different types of artificial neural nets. Results showed not only a clear distinction between individuals, but also revealed clear indications of emotion recognition in nets.

Impact and interest:

20 citations in Scopus
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17 citations in Web of Science®

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ID Code: 18098
Item Type: Journal Article
Additional URLs:
Keywords: Emotion, Gait, Music, Neural network, Pattern recognition
DOI: 10.1007/s10919-007-0045-3
ISSN: 0191-5886
Subjects: Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > HUMAN MOVEMENT AND SPORTS SCIENCE (110600) > Motor Control (110603)
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Schools > School of Exercise & Nutrition Sciences
Deposited On: 27 Apr 2009 08:14
Last Modified: 29 Feb 2012 23:43

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