Information evaluation and classification of scaling exponents of EEG signals corresponding to visual perception, mental imagery & mental rest for artists and non-artists

  • سال انتشار: 1390
  • محل انتشار: هجدهمین کنفرانس مهندسی پزشکی ایران
  • کد COI اختصاصی: ICBME18_113
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 1086
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نویسندگان

Nasrin Shourie

BioMedical Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran.

S Mohammad

Ph.D student of the BioMedical Engineering Department of Science and Research Branch, Islamic Azad University,Tehran, Iran

P Firoozabadi

Professor of BioMedical Engineering and Head of BioMedical Informatics Department at Tarbiat Modares University and President of Iranian Society of the Biomedical Engineering

Kambiz Badie

Professor of BioMedical Engineering and Head of BioMedical Informatics Department at Tarbiat Modares University and President of Iranian Society of the Biomedical Engineering

چکیده

In this paper, we extracted scaling exponents of multichannel EEG signals recorded from two groups of artistsand non-artists. We compared them to investigate the difference between artists and non-artists. The EEG signalswere recorded while the subjects performed four tasks of visual perception, four tasks of mental imagery and at resting condition. We used Davies-Bouldin’s index for evaluation of the feature space quality and the discrimination between the two groups. We observed a noticeable similarity in scaling exponents between visual perception and mental imagery. A considerable discrimination in scaling exponents was observed between the two groups at resting condition. However, the differentiation in scaling exponents between visual perceptions of the two groups was low. This result was observed in scaling exponents between the two groups’ mental imageries, too.Thereby, the discrimination in scaling exponents between the two groups decreased with performing a same cognitive task. Additionally, we classified the scaling exponents which were related to the resting conditions and the visual perceptions of the two groups by the Neural Gas classifier. The average accuracies were 87.5% and 46.87%, respectively. These results confirmed the discrimination and the similarity in scaling exponents between resting conditions and visual perceptions of the two groups, respectively.

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