Why the study?
Schizophrenia is a major cause of disability, and EEG analysis may help medical staff accurately and effectively classify and diagnose its different symptoms.
Can EEG signal analysis accurately classify and diagnose positive and negative symptoms of schizophrenia compared to normal controls?
Can EEG signal analysis accurately classify and diagnose positive and negative symptoms of schizophrenia compared to normal controls?
EEG signal analysis may provide a useful objective tool for classifying and diagnosing positive versus negative symptoms in schizophrenia.
Answers are grounded in this paper and cite their sources.
EEG analysis may aid schizophrenia symptom classification; leaves open validation versus controls in prospective studies.
Schizophrenia is a type of major mental illness characterized by split personality in thinking and behaviour. Schizophrenia has become the fourth leading cause of disability among adolescents in developing countries. This article is based on the EEG signals of normal people, schizophrenia-positive patients, and schizophrenianegative patients. From the neuropsychological background and cognitive ability test results, the level of EEG amplitude, the frequency distribution of EEG in performing functional tasks, and the analysis of a comparative analysis of the degree of brain injury can help medical staff to accurately and effectively classify and diagnose the different symptoms of schizophrenia.
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Fan et al. (2020) studied this question.
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