Backpropagation Artificial Neural Network Detects Changes in Electro-Encephalogram Power Spectra of Syncopic Patients

Authors:
Rakesh Kumar Sinha;Yogender Aggarwal;Barda Nand Das
Affiliations:
Department of Biomedical Instrumentation, Birla Institute of Technology, Mesra, Ranchi, India 835215;Department of Electrical & Electronics Engineering, Birla Institute of Technology, Mesra, Ranchi, India 835215;Department of Biomedical Instrumentation, Birla Institute of Technology, Mesra, Ranchi, India 835215
Venue:
Journal of Medical Systems
Year:
2007

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Abstract

This paper presents an effective application of backpropagation artificial neural network (ANN) in differentiating electroencephalogram (EEG) power spectra of syncopic and normal subjects. Digitized 8-channel EEG data were recorded with standard electrodes placement and amplifier settings from five confirmed syncopic and five normal subjects. The preprocessed EEG signals were fragmented in two-second artifact free epochs for calculation and analysis of changes due to syncope. The results revealed significant increase in percentage 驴 and 驴 (pp