Schizophrenia detection and classification by advanced analysis of EEG recordings using a single electrode approach

Schizophrenia detection and classification by advanced analysis of EEG recordings using a single electrode approach

Electroencephalographic (EEG) analysis has emerged as a powerful tool for brain state interpretation and diagnosis, but not for the diagnosis of mental disorders; this may be explained by its low spatial resolution or depth sensitivity. This paper concerns the diagnosis of schizophrenia using EEG, w...

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Bibliographic Details
Published in:PloS one 2015-04, Vol.10 (4), p.e0123033-e0123033
Main Authors: Dvey-Aharon, Zack, Fogelson, Noa, Peled, Avi, Intrator, Nathan
Format: Article
Language:eng
Subjects:
Algorithms
Analysis
Brain
Brain - physiology
Brain research
Brain Waves - physiology
Classification
Computer science
Computer simulation
Data acquisition
Diagnosis
Diagnostic systems
EEG
Electrodes
Electroencephalography
Electroencephalography - methods
Health aspects
Humans
Medical research
Mental disorders
Methods
Neurosciences
Optimization
Psychiatry
Schizophrenia
Schizophrenia - diagnosis
Schizophrenia - physiopathology
Severity of Illness Index
Signal processing
Signal Processing, Computer-Assisted
Spatial discrimination
Spatial resolution
Studies
Transformation
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Summary:Electroencephalographic (EEG) analysis has emerged as a powerful tool for brain state interpretation and diagnosis, but not for the diagnosis of mental disorders; this may be explained by its low spatial resolution or depth sensitivity. This paper concerns the diagnosis of schizophrenia using EEG, which currently suffers from several cardinal problems: it heavily depends on assumptions, conditions and prior knowledge regarding the patient. Additionally, the diagnostic experiments take hours, and the accuracy of the analysis is low or unreliable. This article presents the "TFFO" (Time-Frequency transformation followed by Feature-Optimization), a novel approach for schizophrenia detection showing great success in classification accuracy with no false positives. The methodology is designed for single electrode recording, and it attempts to make the data acquisition process feasible and quick for most patients.
ISSN:1932-6203
1932-6203