Electroencephalograph (EEG) signal analysis for the Detection of Schizophrenia using Empirical Wavelet Transform
Author:
Affiliation:
1. National Institute of Technology,Department of Biomedical Engineering,Raipur Raipur,India
2. AIIMS Bibi Nagar,Department of Psychiatry,Hydarabad,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9776593/9776643/09777000.pdf?arnumber=9777000
Reference37 articles.
1. EEG signal classification using variational mode decomposition;ullal;ArXiv,2020
2. Schizophrenia detection using MultivariateEmpirical Mode Decomposition and entropy measures from multichannel EEG signal
3. Entropy and complexity measures for EEG signal classification of schizophrenic and control participants
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1. Schizophrenia diagnosis based on diverse epoch size resting-state EEG using machine learning;PeerJ Computer Science;2024-08-20
2. Schizophrenia Detection using Extreme Gradient Boosting with Enhanced Features on PYNQ-Z2;2023 IEEE 9th International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA);2023-10-17
3. A Machine Learning Framework for Automatic Diagnosis of Schizophrenia Using EEG Signals;2022 IEEE 19th India Council International Conference (INDICON);2022-11-24
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