EEG data from basic sensory task in Schizophrenia

This dataset contains electroencephalogram (EEG) signals, event-related potentials (ERP), and demographic attributes aimed at the early identification of schizophrenia. EEG signals and ERP data capture neural and cognitive markers that aid in distinguishing individuals with schizophrenia from healthy controls. Demographic factors such as age, gender, education level, and other relevant attributes are included to enhance the predictive capability of machine learning models. This comprehensive dataset enables researchers to explore and validate novel machine learning techniques for diagnostic purposes, contributing to advancements in the early detection and understanding of schizophrenia.