• DocumentCode
    2975649
  • Title

    Emotion Recognition Using Physiological Signals from Multiple Subjects

  • Author

    Li, Lan ; Chen, Ji-hua

  • Author_Institution
    Jiangsu University, China
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    355
  • Lastpage
    358
  • Abstract
    The ability to recognize emotion is one of the hallmarks of emotional intelligence. This paper proposed to recognize emotion using physiological signals obtained from multiple subjects without much discomfort from the body surface. Four signals, electrocardiogram (ECG), skin temperature (SKT), skin conductance (SC) and respiration were selected to extract features for recognition. We collected a set of data from 60 undergraduates when experiencing the target emotion elicited by film clips. Canonical correlation analysis was used to find the relationship between emotion and extracted features. Using 17 features, 20 features and 22 features, recognition accuracy is 82%, 85.3%, 85.3% respectively.
  • Keywords
    Biomedical engineering; Biomedical monitoring; Data mining; Electrocardiography; Emotion recognition; Feature extraction; Skin; Support vector machine classification; Support vector machines; Temperature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Hiding and Multimedia Signal Processing, 2006. IIH-MSP '06. International Conference on
  • Conference_Location
    Pasadena, CA, USA
  • Print_ISBN
    0-7695-2745-0
  • Type

    conf

  • DOI
    10.1109/IIH-MSP.2006.265016
  • Filename
    4041736