Review and classification of emotion recognition based on EEG brain-computer interface system research: a systematic review

A Al-Nafjan, M Hosny, Y Al-Ohali, A Al-Wabil - Applied Sciences, 2017 - mdpi.com
Recent developments and studies in brain-computer interface (BCI) technologies have
facilitated emotion detection and classification. Many BCI studies have sought to investigate …

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 …

EEG-based emotion charting for Parkinson's disease patients using Convolutional Recurrent Neural Networks and cross dataset learning

MN Dar, MU Akram, R Yuvaraj, SG Khawaja… - Computers in biology …, 2022 - Elsevier
Electroencephalogram (EEG) based emotion classification reflects the actual and intrinsic
emotional state, resulting in more reliable, natural, and meaningful human-computer …

[HTML][HTML] The role of quantitative EEG in the diagnosis of neuropsychiatric disorders

LL Popa, H Dragos, C Pantelemon… - Journal of medicine …, 2020 - ncbi.nlm.nih.gov
Quantitative electroencephalography (QEEG) is a modern type of electroencephalography
(EEG) analysis that involves recording digital EEG signals which are processed …

Performance evaluation of multi-channel electroencephalogram signal (EEG) based time frequency analysis for human emotion recognition

KP Wagh, K Vasanth - Biomedical Signal Processing and Control, 2022 - Elsevier
The automated detection of a human's emotional state by acquiring physiological or non-
physiological cues is referred to as Emotion Recognition. The EEG-based approach is an …

Functional changes in brain oscillations in dementia: a review

A Giustiniani, L Danesin, B Bozzetto… - Reviews in the …, 2023 - degruyter.com
A growing body of evidence indicates that several characteristics of electroencephalography
(EEG) and magnetoencephalography (MEG) play a functional role in cognition and could be …

Tunable Q wavelet transform based emotion classification in Parkinson's disease using Electroencephalography

M Murugappan, W Alshuaib, AK Bourisly, SK Khare… - Plos one, 2020 - journals.plos.org
Parkinson's disease (PD) is a severe incurable neurological disorder. It is mostly
characterized by non-motor symptoms like fatigue, dementia, anxiety, speech and …

[BOOK][B] The clinical neuroscience of lateralization

A Mundorf, S Ocklenburg - 2021 - taylorfrancis.com
The Clinical Neuroscience of Lateralization gives the first comprehensive transdiagnostic
overview of the evidence for changes in hemispheric asymmetries in different psychiatric …

An artificial intelligence based effective diagnosis of parkinson disease using EEG signal

MA Al-Khasawneh, A Alzahrani, A Alarood - Data Analysis for …, 2023 - Springer
This study focuses on the use of human bio-signals for the early diagnosis of PD
(Parkinson's disease). EEG (Electroencephalography) and EMG have been used to …

Analysis of thermal comfort, energy consumption, and CO2 reduction of indoor space according to the type of local heating under winter rest conditions

M Lee, J Ham, JW Lee, H Cho - Energy, 2023 - Elsevier
In this study, the thermal comfort of indoor spaces while resting under winter indoor
conditions was evaluated by analyzing the bio-signals of the human body according to the …