Anxiety and Depression Detection using Statistical Features
محل انتشار: دومین کنفرانس ملی محاسبات نرم
سال انتشار: 1396
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 654
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شناسه ملی سند علمی:
CSCG02_154
تاریخ نمایه سازی: 7 اسفند 1396
چکیده مقاله:
Human action is caused by the neuron activities. The distributed signals from throughout the scalp, due by these activities,can be recorded and analyzed subsequently. Concerning, receiving and recording brain signals can be performed by Electroencephalogram (EEG) recorder. The objective of the present study is to detect the anxiety and depression disorders using EEG signals. In order to get this purpose, some statistical features are extracted using wavelet coefficients in timefrequency domain. Experimental results using 50 subjects is achieved by 96 percent of accuracy to detect disorder
کلیدواژه ها:
نویسندگان
Tahereh Najafi
Department of Computer Engineering, Faculty of Engineering, University of Guilan, Rasht, Guilan
Babak Abad Fomani
Department of Computer Engineering, Faculty of Engineering, University of Guilan, Rasht, Guilan
Asadollah Shahbahrami
Department of Computer Engineering, Faculty of Engineering, University of Guilan, Rasht, Guilan