Abstract
Schizophrenia is an incurable neurological disorder that changes human being’s perception and behavior due to genetic and environmental factors. The objective of this study is to detect Schizophrenia using electroencephalogram signals as biomarker. In this work, two time-domain features, namely Higuchi Fractal Dimension and correlation from a pair of electrodes have been extracted. In addition, two time-domain statistical features i.e., mean and variance are also computed. Analysis has been carried out from each electrode to identify a set of potential electrodes for the detection of schizophrenia to reduce the computational complexity. The algorithm has been validated using leave-one-out strategy and the results obtained show an accuracy of 100%. Also the result has been validated with topographic maps of identified electrodes.
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