Results 31 to 40 of about 1,230,009 (250)

Brain–Computer Interface: The HOL–SSA Decomposition and Two-Phase Classification on the HGD EEG Data

Diagnostics, 2023
An efficient processing approach is essential for increasing identification accuracy since the electroencephalogram (EEG) signals produced by the Brain–Computer Interface (BCI) apparatus are nonlinear, nonstationary, and time-varying.
Mary Judith Antony, Baghavathi Priya Sankaralingam, Shakir Khan, Abrar Almjally, Nouf Abdullah Almujally, Rakesh Kumar Mahendran   +5 more
doaj   +1 more source

Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson's disease [PDF]

, 2014
In addition to classic motor signs and symptoms, individuals with Parkinson's disease (PD) are characterized by emotional deficits. Ongoing brain activity can be recorded by electroencephalograph (EEG) to discover the links between emotional states and ...
Mohamad, Khairiyah, Yuvaraj, Rajamanickam, Ibrahim, Norlinah Mohamed, Omar, Mohd Iqbal, Murugappan, Murugappan, Sundaraj, Kenneth, Palaniappan, Ramaswamy   +6 more
core   +1 more source

A Novel Method Based on Combination of Independent Component Analysis and Ensemble Empirical Mode Decomposition for Removing Electrooculogram Artifacts From Multichannel Electroencephalogram Signals

Frontiers in Neuroscience, 2021
Electrooculogram (EOG) is one of common artifacts in recorded electroencephalogram (EEG) signals. Many existing methods including independent component analysis (ICA) and wavelet transform were applied to eliminate EOG artifacts but ignored the possible ...
Chao-Lin Teng, Chao-Lin Teng, Chao-Lin Teng, Yi-Yang Zhang, Yi-Yang Zhang, Yi-Yang Zhang, Wei Wang, Yuan-Yuan Luo, Gang Wang, Gang Wang, Gang Wang, Jin Xu, Jin Xu, Jin Xu   +13 more
doaj   +1 more source

Clinical Outcomes of SEEG‐Guided Radiofrequency Thermocoagulation in Children With Focal Drug‐Resistant Epilepsy: A Multicenter Real‐World Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Stereoelectroencephalography‐guided radiofrequency thermocoagulation (SEEG‐RFTC) has emerged as a safe and effective minimally invasive treatment for children with drug‐resistant focal epilepsy. Although evidence from real‐world studies remains limited, numerous pediatric cases have demonstrated promising outcomes. This retrospective
Weitao Chen, Stéphane Jean, Weihong Liu, Yihai Dai, Xinrong Fang, Xiaoqiang Wei, Shan Chen, Shiwei Song   +7 more
wiley   +1 more source

Development of electroencephalogram (EEG) signals classification techniques

, 2019
Electroencephalography (EEG) is one of the most important signals recorded from humans. It can assist scientists and experts to understand the most complex part of the human body, the brain. Thus, analysing EEG signals is the most preponderant process to
Al Ghayab, Hadi Ratham Ghayab
core   +1 more source

Two Different Approaches of Feature Extraction for Classifying the EEG Signals [PDF]

, 2011
The electroencephalograph (EEG) signal is one of the most widely used signals in the biomedicine field due to its rich information about human tasks.
Caraça-Valente Hernández, Juan Pedro, Lara Torralbo, Juan Alfonso, Lara, Juan,, Valente, Juan, P., Pérez Pérez, Aurora, Valente, Juan,, Juan A. Lara, Pari Jahankhani, Jahankhani, Pari, Lara, Juan, A., Pérez, Aurora, Juan P. Valente, Aurora Pérez   +12 more
core   +1 more source

Advances in classification of EEG signals via evolving fuzzy classifiers and dependant multiple HMMs. [PDF]

, 2006
Two novel approaches to the problem of brain signals (electroencephalogram (EEG)) classification are introduced in the paper. The first method is based on a modular probabilistic network architecture that employs multiple dependant hidden Markov models ...
Angelov, Plamen, Chiao, Shih-Yang, Reoullas, Michalis, Xydeas, Costas   +3 more
core   +4 more sources

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

The Use of EEG Signals For Biometric Person Recognition [PDF]

, 2015
This work is devoted to investigating EEG-based biometric recognition systems. One potential advantage of using EEG signals for person recognition is the difficulty in generating artificial signals with biometric characteristics, thus making the spoofing
Yang, Su
core  

Added Prognostic Value of EEG Reactivity in Comatose Patients Following Cardiac Arrest

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives To evaluate the added prognostic value of EEG reactivity for favorable outcome compared with background analysis during and after targeted temperature management (TTM). Methods Prospective observational cohort study of comatose post–cardiac arrest patients admitted to a single academic center between 2017 and 2022, all undergoing ...
Sarah Caroyer, Marie Obrecht, Charlotte de Maeseneire, Charlotte Damien, Chantal Depondt, Lorenzo Ferlini, Estelle Rikir, Filippo Annoni, Fabio Silvio Taccone, Nicolas Mavroudakis, Benjamin Legros, Nicolas Gaspard   +11 more
wiley   +1 more source