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.

精神分裂症是一种无法治愈的神经系统疾病，由于遗传和环境因素而改变了人类的感知和行为。本研究的目的是使用脑电图信号作为生物标志物检测精神分裂症。在这项工作中，从一对电极中提取了两个时域特征，即 Higuchi 分形维数和相关性。此外，还有两个时域统计特征，即，均值和方差也被计算。已从每个电极进行分析，以确定一组用于检测精神分裂症的潜在电极，以降低计算复杂度。该算法已使用留一法进行验证，所得结果显示准确率为 100%。此外，该结果已通过已识别电极的地形图进行了验证。