A Computerized Method for Automatic Detection of Schizophrenia Using EEG Signals

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 28; no. 11; pp. 2390 - 2400
• Main Authors: Siuly, Siuly, Khare, Smith K., Bajaj, Varun, Wang, Hua, Zhang, Yanchun
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; classification; Classifiers; decision tree; Decomposition; Diagnosis; EEG; Electroencephalogram; Electroencephalography; Electronic mail; empirical mode decomposition; ensemble bagged tree; Feature extraction; Frequency modulation; Interviews; K-nearest neighbor; Mental disorders; Schizophrenia; Statistical analysis; support vector machine; Support vector machines; Time-frequency analysis

Diagnosis of schizophrenia (SZ) is traditionally performed through patient's interviews by a skilled psychiatrist. This process is time-consuming, burdensome, subject to error and bias. Hence the aim of this study is to develop an automatic SZ identification scheme using electroencephalogram (E...