Parkinson's disease: Cause factors, measurable indicators, and early diagnosis

S Bhat, UR Acharya, Y Hagiwara, N Dadmehr… - Computers in biology …, 2018 - Elsevier
Parkinson's disease (PD) is a neurodegenerative disease of the central nervous system
caused due to the loss of dopaminergic neurons. It is classified under movement disorder as …

A review of automated sleep stage scoring based on physiological signals for the new millennia

O Faust, H Razaghi, R Barika, EJ Ciaccio… - Computer methods and …, 2019 - Elsevier
Abstract Background and Objective Sleep is an important part of our life. That importance is
highlighted by the multitude of health problems which result from sleep disorders. Detecting …

Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals

N Michielli, UR Acharya, F Molinari - Computers in biology and medicine, 2019 - Elsevier
Automated evaluation of a subject's neurocognitive performance (NCP) is a relevant topic in
neurological and clinical studies. NCP represents the mental/cognitive human capacity in …

A deep learning model for automated sleep stages classification using PSG signals

O Yildirim, UB Baloglu, UR Acharya - International journal of …, 2019 - mdpi.com
Sleep disorder is a symptom of many neurological diseases that may significantly affect the
quality of daily life. Traditional methods are time-consuming and involve the manual scoring …

Automatic sleep stage classification using time–frequency images of CWT and transfer learning using convolution neural network

P Jadhav, G Rajguru, D Datta… - Biocybernetics and …, 2020 - Elsevier
For automatic sleep stage classification, the existing methods mostly rely on hand-crafted
features selected from polysomnographic records. In this paper, the goal is to develop a …

Convolution-and attention-based neural network for automated sleep stage classification

T Zhu, W Luo, F Yu - … Journal of Environmental Research and Public …, 2020 - mdpi.com
Analyzing polysomnography (PSG) is an effective method for evaluating sleep health;
however, the sleep stage scoring required for PSG analysis is a time-consuming effort for an …

Automated detection of abnormal EEG signals using localized wavelet filter banks

M Sharma, S Patel, UR Acharya - Pattern Recognition Letters, 2020 - Elsevier
Epilepsy is a neural disorder that is associated with the central nervous system (CNS) in
which the brain activity sometimes becomes abnormal, which may lead to seizures, loss of …

An automated diagnosis of depression using three-channel bandwidth-duration localized wavelet filter bank with EEG signals

M Sharma, PV Achuth, D Deb, SD Puthankattil… - Cognitive Systems …, 2018 - Elsevier
Depression is a mental illness. If not diagnosed and treated quickly, it can affect one's mood
and quality of life. Modern life is stressful and fast paced, owing to which depression has …

Use of features from RR-time series and EEG signals for automated classification of sleep stages in deep neural network framework

RK Tripathy, UR Acharya - Biocybernetics and Biomedical Engineering, 2018 - Elsevier
Sleep is a physiological activity and human body restores itself from various diseases during
sleep. It is necessary to get sufficient amount of sleep to have sound physiological and …

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 …