IDENTIFICATION OF SCHIZOPHRENIA USING ALPHA POWER AND THETA PEAK FREQUENCY DURING COGNITIVE ACTIVITY

Schizophrenia (SCH) is a psychiatric disorder that causes mental illness and is very difficult to discriminate from the normal subject. As the current diagnostic procedure DSM-V is qualitative, accurate clinical detection is essential. Cognitive dysfunction is widespread in [Formula: see text]CH and it relates to brain activity. The aim of this research is to analyze EEG as a screening tool to identify SCH as it records brain activity. To stimulate cognitive activity, two different types of visual oddball paradigms are designed and are named P1 and P2. Although many researchers have analyzed the EEG of SCH, it remains unclear which recording condition is suitable. Therefore, EEG is recorded from 52 SCH subjects and 29 normal subjects during conventional recording conditions, namely rest, HV, PHV, Photic and cognitive activities (P1 and P2). The Welch power spectrum method is used to find the absolute power of the four EEG bands called [Formula: see text] Pr , [Formula: see text] Pr , [Formula: see text] Pr and [Formula: see text] Pr . In addition to these, each band’s peak power [Formula: see text] PPR , [Formula: see text] PPR , [Formula: see text] PPR and [Formula: see text] PPR and peak frequencies [Formula: see text] PF , [Formula: see text] PF , [Formula: see text] PF and [Formula: see text] PF are also calculated from the power spectrum of the EEG signal. Out of these 12 features, [Formula: see text] Pr and [Formula: see text] PF are considered as the most significant features, because they are significant with [Formula: see text] < 0.001 in all recording conditions. The SVM classifier successfully predicts SCH with a maximum sensitivity of 98% and accuracy of 97% using [Formula: see text] Pr and [Formula: see text] PF . Therefore, it can be concluded that [Formula: see text] Pr and [Formula: see text] PF can be used as features to use EEG as a screening tool for the identification of schizophrenia.