[HTML][HTML] Advancements in Parkinson's Disease Diagnosis: A Comprehensive Survey on Biomarker Integration and Machine Learning

R Pratihar, R Sankar - Computers, 2024 - mdpi.com
This comprehensive review explores the advancements in machine learning algorithms in
the diagnosis of Parkinson's disease (PD) utilizing different biomarkers. It addresses the …

Early detection of Parkinson's disease: Systematic analysis of the influence of the eyes on quantitative biomarkers in resting state electroencephalography

G Giménez-Aparisi, E Guijarro-Estelles… - Heliyon, 2023 - cell.com
While resting state electroencephalography (EEG) provides relevant information on
pathological changes in Parkinson's disease, most studies focus on the eyes-closed EEG …

Classification of Parkinson's disease EEG signals using 2D-MDAGTS model and multi-scale fuzzy entropy

J Li, X Li, Y Mao, J Yao, J Gao, X Liu - Biomedical Signal Processing and …, 2024 - Elsevier
Parkinson's disease (PD) is a neurodegenerative disorder that causes changes in neurons,
behavior, and physiological structures. However, these changes are very subtle in the early …

[HTML][HTML] ComBat models for harmonization of resting-state EEG features in multisite studies

A Jaramillo-Jimenez, DA Tovar-Rios… - Clinical …, 2024 - Elsevier
Objective Pooling multisite resting-state electroencephalography (rsEEG) datasets may
introduce bias due to batch effects (ie, cross-site differences in the rsEEG related to …

Clinical and neurophysiological effects of bilateral repetitive transcranial magnetic stimulation and EEG-guided neurofeedback in Parkinson's disease: a randomized …

JP Romero, M Moreno-Verdú, A Arroyo-Ferrer… - Journal of …, 2024 - Springer
Abstract Background Repetitive Transcranial Magnetic Stimulation (rTMS) and EEG-guided
neurofeedback techniques can reduce motor symptoms in Parkinson's disease (PD) …

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 …

Impact of sleep deprivation on aperiodic activity: a resting-state EEG study

D Bai, J Hu, S Jülich, X Lei - Journal of Neurophysiology, 2024 - journals.physiology.org
Sleep deprivation (SD) has been shown to have a negative impact on alertness, as
evidenced by behavioral and electroencephalographic studies. Nevertheless, in prior …

Analyzing Brain Signals Using Functional Geostatistics

NBQ Alonso - 2024 - search.proquest.com
Electroencephalography (EEG) signals represent the brain's electrical activity ob tained
through placing electrodes on the scalp. These recordings can be analyzed as curves …

[PDF][PDF] Declaration of Academic Integrity

NBQ Alonso - 2024 - run.unl.pt
Electroencephalography (EEG) signals represent the brain's electrical activity obtained
through placing electrodes on the scalp. These recordings can be analyzed as curves …

Efectos neuromoduladores, funcionales y estructurales de la estimulación theta-burst intermitente y su relación con la respuesta clínica en pacientes con enfermedad …

R Rashid Abdul Rahim Lopez - 2024 - rodin.uca.es
La estimulación theta-burst intermitente (iTBS) es un patrón de estimulación magnética
transcraneal repetitiva (rTMS) excitadora que ha puesto de manifiesto resultados …