• DocumentCode
    1656102
  • Title

    Automated detection of paroxysmal gamma waves in meditation EEG

  • Author

    Vazquez, Miguel Angel ; Jing Jin ; Dauwels, Justin ; Vialatte, Francois B.

  • Author_Institution
    Depto. de Teor. de la Senal y Comun., Univ. Carlos III de Madrid, Madrid, Spain
  • fYear
    2013
  • Firstpage
    1192
  • Lastpage
    1196
  • Abstract
    Meditation is a fascinating topic, yet has received limited attention in the neuroscience and signal processing community so far. A few studies have investigated electroencephalograms (EEG) recorded during meditation. Strong EEG activity has been observed in the left temporal lobe of meditators. Meditators exhibit more paroxysmal gamma waves (PGWs) in active regions of the brain. In this paper, a method is proposed to automatically detect PGWs from meditation EEG. The proposed algorithm is able to identify multiple sources in the brain that generate PGWs, and the sources associated with different types of PGWs can be distinguished. The effectiveness of the proposed method is assessed on 3 subjects possessing different degrees of expertise in practicing a yoga type meditation known as Bhramari Pranayama.
  • Keywords
    electroencephalography; medical signal detection; neurophysiology; Bhramari Pranayama; EEG activity; PGW; automated detection; brain active region; brain multiple source identification; electroencephalogram; left temporal lobe; meditation EEG; meditator; neuroscience; paroxysmal gamma waves; signal processing community; yoga type meditation; Blind source separation; Detectors; Electroencephalography; Principal component analysis; Sensitivity; Temporal lobe; Bhramari Pranayama; Electroencephalogram; Meditation; Paroxysmal gamma wave; Spike detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2013.6637839
  • Filename
    6637839