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

JANSSEN, D, SCHÖLLHORN, W I, LUBIENETZKI, J, FÖLLING, K, KOKENGE, H and DAVIDS, K (2008). Recognition of emotions in gait patterns by means of artificial neural nets. Journal of Nonverbal Behavior, 32 (2), 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.

Item Type:	Article
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Centre for Sports Engineering Research
Identification Number:	https://doi.org/10.1007/s10919-007-0045-3
Page Range:	79-92
Depositing User:	Carole Harris
Date Deposited:	18 Mar 2011 15:40
Last Modified:	19 Mar 2021 00:45
URI:	https://shura.shu.ac.uk/id/eprint/3271

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