Automatic identification of schizophrenia using EEG signals based on discrete wavelet transform and RLNDiP technique with ANN
Schizophrenia (ScZ) is a detrimental condition of the brain often associated with depression,
anxiety, and socio-psychological problems. In the traditional diagnosis approach, the results …
anxiety, and socio-psychological problems. In the traditional diagnosis approach, the results …
An efficient classifier to diagnose of schizophrenia based on the EEG signals
In this paper, electroencephalogram (EEG) signals of 13 schizophrenic patients and 18 age-
matched control participants are analyzed with the objective of classifying the two groups …
matched control participants are analyzed with the objective of classifying the two groups …
An accurate automated schizophrenia detection using TQWT and statistical moment based feature extraction
M Baygin - Biomedical Signal Processing and Control, 2021 - Elsevier
Nowadays, abnormal brain activities can be automatically detected and classified by
processing EEG signals. In this paper, the classification process of EEG signals collected …
processing EEG signals. In this paper, the classification process of EEG signals collected …
Automatic diagnosis of schizophrenia in EEG signals using functional connectivity features and CNN-LSTM model
Schizophrenia (SZ) is a mental disorder that threatens the health of many people around the
world. People with schizophrenia always suffer from symptoms that include hallucinations …
world. People with schizophrenia always suffer from symptoms that include hallucinations …
A self-learned decomposition and classification model for schizophrenia diagnosis
Background: Schizophrenia (SZ) is a type of neurological disorder that is diagnosed by
professional psychiatrists based on interviews and manual screening of patients. The …
professional psychiatrists based on interviews and manual screening of patients. The …
A hybrid deep neural network for classification of schizophrenia using EEG Data
J Sun, R Cao, M Zhou, W Hussain, B Wang, J Xue… - Scientific Reports, 2021 - nature.com
Schizophrenia is a serious mental illness that causes great harm to patients, so timely and
accurate detection is essential. This study aimed to identify a better feature to represent …
accurate detection is essential. This study aimed to identify a better feature to represent …
Automated detection of schizophrenia using nonlinear signal processing methods
Examination of the brain's condition with the Electroencephalogram (EEG) can be helpful to
predict abnormality and cerebral activities. The purpose of this study was to develop an …
predict abnormality and cerebral activities. The purpose of this study was to develop an …
Automated detection of schizophrenia using optimal wavelet-based norm features extracted from single-channel EEG
M Sharma, UR Acharya - Cognitive Neurodynamics, 2021 - Springer
Schizophrenia (SZ) is a mental disorder, which affects the ability of human thinking, memory,
and way of living. Manual screening of SZ patients is tedious, laborious and prone to human …
and way of living. Manual screening of SZ patients is tedious, laborious and prone to human …
Artificial intelligence-based classification of schizophrenia: A high density electroencephalographic and support vector machine study
Background: Interview-based schizophrenia (SCZ) diagnostic methods are not completely
valid. Moreover, SCZ-the disease entity is very heterogeneous. Supervised-Machine …
valid. Moreover, SCZ-the disease entity is very heterogeneous. Supervised-Machine …
Selection of relevant features for EEG signal classification of schizophrenic patients
M Sabeti, R Boostani, SD Katebi, GW Price - Biomedical Signal Processing …, 2007 - Elsevier
In this paper, EEG signals of 20 schizophrenic patients and 20 age-matched control
participants are analyzed with the objective of determining the more informative channels …
participants are analyzed with the objective of determining the more informative channels …