• DocumentCode
    1786087
  • Title

    Computing stress-related emotional state via frontal cortex asymmetry to be applied in passive-ssBCI

  • Author

    Atencio, A.C. ; Garcia, J.C. ; Benevides, A.B. ; Longo, Berthil B. ; Ferreira, Andre ; Porner-Escher, Alexandre ; Pinheiro de Souza, Maria Dolores ; Bastos, Teodiano

  • Author_Institution
    Post-Grad. Program of Electr. Eng., Fed. Univ. of Espirito Santo, Vitoria, Brazil
  • fYear
    2014
  • fDate
    26-28 May 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The identification of stress-related emotional states allows the use of a passive single-switch BCI (passive-ssBCI) together with a main multi-class BCI. Thus, the passive-ssBCI could work in the background of the main BCI, allowing it to recognize stress-related emotions and to switch to a “stress mode”, which allows a better adaptation to the user current mental state, leading the system to better success rates. Frontal cortex asymmetry gave evidence that greater right frontal activity seems to be more highly related to negative emotional states. In this work, index of asymmetry of alpha band was computed by comparing the power of contra-lateral frontal electrodes. Discrete Wavelet transformation was used to decompose the EEG signals in frequency bands. The power spectral density was then calculated using modified Hamming periodogram. Signals from a public database for the analysis of human affective states, which was labeled with volunteers self-assessment scores, were employed. In order to label negative stress-related emotional state, rules based on valence, arousal and dominance dimensional emotions were defined. The results were promissory, because computed index of asymmetry in the alpha band indicated activity into the right frontal hemisphere was higher than the left one for seven out of nine volunteers during negative emotional states. This index could be employed as switch to a “stress mode” in a passive-ssBCI.
  • Keywords
    biomedical electrodes; brain-computer interfaces; discrete wavelet transforms; electroencephalography; emotion recognition; medical signal processing; neurophysiology; spectral analysis; EEG signal decomposition; alpha band; arousal; contra-lateral frontal electrodes; discrete wavelet transformation; dominance dimensional emotions; frequency bands; frontal cortex asymmetry; human affective state analysis; index of asymmetry; main BCI; main multiclass BCI; mental state; modified Hamming periodogram; negative stress-related emotional state; passive single-switch BCI; power spectral density; public database; right frontal activity; right frontal hemisphere; self-assessment scores; stress mode; stress-related emotional state identification; valence; Electrodes; Electroencephalography; Emotion recognition; Frequency estimation; Indexes; Switches; EEG; Frontal cortex asymmetry; Passive-BCI; Stress emotional state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), 5th ISSNIP-IEEE
  • Conference_Location
    Salvador
  • Print_ISBN
    978-1-4799-5688-3
  • Type

    conf

  • DOI
    10.1109/BRC.2014.6880974
  • Filename
    6880974