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
Link To Document