WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402
Volume 9, 2012
Feature Extraction in P 100 Detection for Classification of Pattern Visual Evoked Potential (P-VEP) Signals Correlated with Occlusion Therapy for Squint Eyes
Authors: ,
Abstract: In this work, we carried out a detailed study of various features of pattern visual evoked potential (P-VEP) signal. P-VEP tests are commonly used in ophthalmology to estimate bioelectrical function of the retina and optic nerve. P-VEP signal which consist of extracted information could assist ophthalmologist in making appropriate decisions during occlusion therapy. The extraction and detection of P100 from P-VEP signal with powerful and advance methodologies is becoming a very important requirement for monitoring the effectiveness of occlusion therapy in squint eye patient. By analyzing the features in different domains we conclude that amplitude and time domain features are more powerful in finding P100 signals from non-P100 signals. The method we proposed in this work is based on the extraction of five out of nine main features of P-VEP signal. Five features are: Latency, Amplitude, Peak-to-peak, Peak of N100 and Latency of N100. The performance of each feature assessed by Linear Discriminate Analysis (LD) classifier. The experiment was performed with different number of channels to analyze the effect of the number of channels.
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Keywords: Occlusion Therapy, Squint eye, Latency, Amplitude, Peak-to-peak, Peak of N100, Latency of N100, P100 detection