Deep learning models for diagnosis of schizophrenia using EEG signals: emerging trends, challenges, and prospects
Schizophrenia (ScZ) is a chronic neuropsychiatric disorder characterized by disruptions in
cognitive, perceptual, social, emotional, and behavioral functions. In the traditional …
cognitive, perceptual, social, emotional, and behavioral functions. In the traditional …
Schizo-Net: A novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning on Electroencephalogram-Based Brain Connectivity Indices
N Grover, A Chharia, R Upadhyay… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions,
and disordered thinking. Traditionally, SCZ diagnosis involves the subject's interview by a …
and disordered thinking. Traditionally, SCZ diagnosis involves the subject's interview by a …
Deep autoencoder for real-time single-channel EEG cleaning and its smartphone implementation using TensorFlow Lite with hardware/software acceleration
Objective: To remove signal contamination in electroencephalogram (EEG) traces coming
from ocular, motion, and muscular artifacts which degrade signal quality. To do this in real …
from ocular, motion, and muscular artifacts which degrade signal quality. To do this in real …
Analysis of the impact of deep learning know-how and data in modelling neonatal EEG
A Daly, G Lightbody, A Temko - Scientific Reports, 2024 - nature.com
The performance gains achieved by deep learning models nowadays are mainly attributed
to the usage of ever larger datasets. In this study, we present and contrast the performance …
to the usage of ever larger datasets. In this study, we present and contrast the performance …
EEG Data Analysis Techniques for Precision Removal and Enhanced Alzheimer's Diagnosis: Focusing on Fuzzy and Intuitionistic Fuzzy Logic Techniques
M Versaci, F La Foresta - Signals, 2024 - mdpi.com
Effective management of EEG artifacts is pivotal for accurate neurological diagnostics,
particularly in detecting early stages of Alzheimer's disease. This review delves into the …
particularly in detecting early stages of Alzheimer's disease. This review delves into the …
Deep learning for grasp-and-lift movement forecasting based on electroencephalography by brain-computer interface
Y Gordienko, K Kostiukevych, N Gordienko… - Advances in Artificial …, 2021 - Springer
Several deep neural networks (DNNs) were compared to classify some basic hand
movements (actions) on the grasp-and-lift (GAL) dataset by analysis of prior-action, in …
movements (actions) on the grasp-and-lift (GAL) dataset by analysis of prior-action, in …
Deep learning with noise data augmentation and detrended fluctuation analysis for physical action classification by brain-computer interface
Y Gordienko, K Kostiukevych… - … Conference on Soft …, 2021 - ieeexplore.ieee.org
Deep neural networks (DNNs) demonstrate their high potential for investigation of time
sequences in many domains, including analysis of electroencephalography (EEG) signals …
sequences in many domains, including analysis of electroencephalography (EEG) signals …
Convolutional ProteinUnetLM competitive with long short‐term memory‐based protein secondary structure predictors
K Kotowski, P Fabian, I Roterman… - … Structure, Function, and …, 2023 - Wiley Online Library
The protein secondary structure (SS) prediction plays an important role in the
characterization of general protein structure and function. In recent years, a new generation …
characterization of general protein structure and function. In recent years, a new generation …
Convolutional and recurrent neural networks for physical action forecasting by brain-computer interface
K Kostiukevych, S Stirenko, N Gordienko… - 2021 11th IEEE …, 2021 - ieeexplore.ieee.org
Recently deep neural networks (DNNs) were intensively investigated for analysis of time
sequences like electroencephalography (EEG) signals that can be measured by brain …
sequences like electroencephalography (EEG) signals that can be measured by brain …
Acta: a mobile-health solution for integrated nudge-neurofeedback training for senior citizens
As the worldwide population gets increasingly aged, in-home telemedicine and mobile-
health solutions represent promising services to promote active and independent aging and …
health solutions represent promising services to promote active and independent aging and …