3rd International Workshop on Pervasive Computing Paradigms for Mental Health

Research Article

Pervasive and Unobtrusive Emotion Sensing for Human Mental Health

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  • @INPROCEEDINGS{10.4108/icst.pervasivehealth.2013.252133,
        author={Rui Guo and Shuanjiang Li and Li He and Wei Gao and Hairong Qi and Gina Owens},
        title={Pervasive and Unobtrusive Emotion Sensing for Human Mental Health},
        proceedings={3rd International Workshop on Pervasive Computing Paradigms for Mental Health},
        publisher={IEEE},
        proceedings_a={MINDCARE},
        year={2013},
        month={5},
        keywords={emotion sensing gsr data analysis emotion classification},
        doi={10.4108/icst.pervasivehealth.2013.252133}
    }
    
  • Rui Guo
    Shuanjiang Li
    Li He
    Wei Gao
    Hairong Qi
    Gina Owens
    Year: 2013
    Pervasive and Unobtrusive Emotion Sensing for Human Mental Health
    MINDCARE
    IEEE
    DOI: 10.4108/icst.pervasivehealth.2013.252133
Rui Guo1, Shuanjiang Li1, Li He1, Wei Gao1,*, Hairong Qi1, Gina Owens2
  • 1: Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville
  • 2: Department of Psychology, University of Tennessee, Knoxville
*Contact email: weigao@utk.edu

Abstract

In this paper, we present a pervasive and unobtrusive system for sensing human emotions, which are inferred based on the recording, processing, and analysis of the Galvanic Skin Response (GSR) signal from human bodies. Being different from traditional multimodal emotion sensing systems, our proposed system recognizes human emotions with the single modularity of GSR signal, which is captured by wearable sensing devices. A comprehensive set of features is extracted from GSR signal and fed into supervised classifiers for emotion identification. Our system has been evaluated by specific experiments to investigate the characteristics of human emotions in practice. The high accuracy of emotion classification highlights the great potential of this system in improving humans' mental health in the future.