Anxiety and Depression Detection using Statistical Features
Publish place: 2rd International Conference on Soft Computing
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
View: 610
This Paper With 7 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
CSCG02_154
تاریخ نمایه سازی: 7 اسفند 1396
Abstract:
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
Keywords:
Authors
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