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 …

SchizoNET: a robust and accurate Margenau–Hill time-frequency distribution based deep neural network model for schizophrenia detection using EEG signals

SK Khare, V Bajaj, UR Acharya - Physiological Measurement, 2023 - iopscience.iop.org
Objective. Schizophrenia (SZ) is a severe chronic illness characterized by delusions,
cognitive dysfunctions, and hallucinations that impact feelings, behaviour, and thinking …

IoT-driven augmented reality and virtual reality systems in neurological sciences

M Sahu, R Gupta, RK Ambasta, P Kumar - Internet of Things, 2024 - Elsevier
Research in augmented and virtual reality in congregation with the Internet of Things has
opened many avenues in diagnosing and treating neurological disorders. Augmented reality …

Cognitive function: holarchy or holacracy?

C Birle, D Slavoaca, M Balea, L Livint Popa… - Neurological …, 2021 - Springer
Cognition is the most complex function of the brain. When exploring the inner workings of
cognitive processes, it is crucial to understand the complexity of the brain's dynamics. This …

A self-learned decomposition and classification model for schizophrenia diagnosis

SK Khare, V Bajaj - Computer Methods and Programs in Biomedicine, 2021 - Elsevier
Background: Schizophrenia (SZ) is a type of neurological disorder that is diagnosed by
professional psychiatrists based on interviews and manual screening of patients. The …

[HTML][HTML] Possible neuropathological mechanisms underlying the increased complexity of brain electrical activity in schizophrenia: a computational study

A Khaleghi, MR Mohammadi, K Shahi… - Iranian Journal of …, 2023 - ncbi.nlm.nih.gov
Objective: Schizophrenia is a complex neurodevelopmental illness that is associated with
different deficits in the cerebral cortex and neural networks, resulting in irregularity of brain …

[HTML][HTML] Deep-spindle: An automated sleep spindle detection system for analysis of infant sleep spindles

L Wei, S Ventura, MA Ryan, S Mathieson… - Computers in Biology …, 2022 - Elsevier
Background: Sleep spindles are an indicator of the development and integrity of the central
nervous system in infants. Identifying sleep spindles manually in EEG is time-consuming …

Higuchi fractal dimension: An efficient approach to detection of brain entrainment to theta binaural beats

E Shamsi, MA Ahmadi-Pajouh, TS Ala - Biomedical signal processing and …, 2021 - Elsevier
Binaural beats (BBs) are two pure tones with a small frequency difference (ie, beat)
separately presented to each ear. They cause the beat perception in the brain. BBs are used …

Complexity-based decoding of brain-skin relation in response to olfactory stimuli

S Omam, MH Babini, S Sim, R Tee, V Nathan… - Computer methods and …, 2020 - Elsevier
Abstract Background and Objective Human body is covered with skin in different parts. In
fact, skin reacts to different changes around human. For instance, when the surrounding …

Schizophrenia EEG signal classification based on swarm intelligence computing

SK Prabhakar, H Rajaguru… - Computational Intelligence …, 2020 - Wiley Online Library
One of the serious mental disorders where people interpret reality in an abnormal state is
schizophrenia. A combination of extremely disordered thinking, delusion, and hallucination …