Classifying Schizophrenia Disorder through EEG Signal Analysis and Machine Learning

N Nattudurai - 2023 IEEE MIT Undergraduate Research …, 2023 - ieeexplore.ieee.org
Schizophrenia can lead to a patient's death up to 20 years earlier than those who do not
have the neurological disorder. Electroencephalograms (EEG) are a noninvasive …

Scz-scan: An automated schizophrenia detection system from electroencephalogram signals

G Sahu, M Karnati, A Gupta, A Seal - Biomedical Signal Processing and …, 2023 - Elsevier
Schizophrenia (SCZ) is a severe neurological and physiological syndrome that perverts a
patient's perception of reality. SCZ exhibits several symptoms, including hallucinations …

Chronologically Arranged Convolutional Gated Recurrent Network for EEG-Based Schizophrenia Detection

S Swati, M Kumar - International Conference on Pattern Recognition and …, 2023 - Springer
Schizophrenia is a severe brain disorder having disruptive effects on human behavior,
which can progressively turn out to be worst if left undiagnosed and untreated in its early …

EEG signals feature extraction and artificial neural networks classification for the diagnosis of schizophrenia

L Zhang - 2020 IEEE 19th International Conference on …, 2020 - ieeexplore.ieee.org
This paper presents the design of artificial neural networks (ANN) for the classification of
Electroencephalograph (EEG) signals collected from 49 Schizophrenia patients and 32 …

An Intelligent Schizophrenia Detection based on the Fusion of Multivariate Electroencephalography Signals

EM Aldaz, RA Berrezueta, NH Bandera - Full Length Article, 2023 - americaspg.com
Schizophrenia, a complex psychiatric disorder, presents a significant challenge in early
diagnosis and intervention. In this study, we introduce an intelligent approach to …

A pyramidal spatial-based feature attention network for schizophrenia detection using electroencephalography signals

M Karnati, G Sahu, A Gupta, A Seal… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Automatic signal classification is utilized in various medical and industrial applications,
particularly in schizophrenia (SZ) diagnosis, one of the most prevalent chronic neurological …

[PDF][PDF] Evaluating domain knowledge and time series features for automated detection of schizophrenia from EEG signals

S Hussain, N Pirzada, E Saba… - … Journal of Advanced …, 2021 - researchgate.net
Over the recent years, Schizophrenia has become a serious mental disorder that is affecting
almost 21 million people globally. There are different symptoms to recognize schizophrenia …

SZ-RAN: A Residual Attention Network for Early Detection of Schizophrenia using EEG Signals

S Singh, S Singh, G Sahu, J Jadon… - 2023 9th International …, 2023 - ieeexplore.ieee.org
Schizophrenia (SZ) is a complex and debilitating mental disorder which affects 1% of the
global population. Electroencephalogram (EEG) emerged as a promising, low-cost and non …

A deep learning approach for diagnosis of schizophrenia disorder via data augmentation based on convolutional neural network and long short-term memory

AM Shams, S Jabbari - Biomedical Engineering Letters, 2024 - Springer
Schizophrenia (SZ) is a severe, chronic mental disorder without specific treatment. Due to
the increasing prevalence of SZ in societies and the similarity of the characteristics of this …

[PDF][PDF] Automatic Diagnosis of Schizophrenia using EEG Signals and CNN-LSTM Models

JM Gorriz - academia.edu
Schizophrenia (SZ) is a mental disorder whereby due to the secretion of specific chemicals
in the brain, the function of some brain regions is out of balance, leading to the lack of …