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Analysis and classification of EEG signals [PDF]
, 2012 Electroencephalography (EEG) is one of the most clinically and scientifically exploited signals recorded from humans. Hence, its measurement plays a prominent role in brain studies. In particular, the examination of EEG signals has been recognized as the
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
Data selection in EEG signals classification
, 2016 The alcoholism can be detected by analyzing electroencephalogram (EEG) signals. However, analyzing multi-channel EEG signals is a challenging task, which often requires complicated calculations and long execution time.
Wen, Peng +3 more
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Brain SciencesThe generation of images from electroencephalography (EEG) signals has become a popular research topic in recent research because it can bridge the gap between brain signals and visual stimuli and has wide application prospects in neuroscience and ...
Guangyu Yang, Jinguo Liu
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To characterize the demographic, clinical, and laboratory features of the Chinese patients of genetic Creutzfeldt‐Jakob disease with T188K variant (T188K‐gCJD), the most common subtype of genetic prion diseases (gPrDs) in China. Methods In this nationwide retrospective study, data from 98 genetically confirmed T188K‐gCJD patients ...
Chun‐Jie Li +11 more
wiley +1 more source
Basic and Clinical Neuroscience, 2014 The objective of this study is development of driver’s sleepiness using Visually Evoked Potentials (VEP). VEP computed from EEG signals from the visual cortex.
Amjad Hashemi +2 more
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Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 more
wiley +1 more source
Seizure characterisation using frequency-dependent multivariate dynamics [PDF]
, 2009 The characterisation of epileptic seizures assists in the design of targeted pharmaceutical seizure prevention techniques and pre-surgical evaluations.
Crane, Martin +5 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Variants in SLC6A1, encoding the GABA transporter 1 (GAT‐1), cause epilepsy, autism spectrum disorder, and developmental delay via loss of GABA uptake, impaired trafficking, and ER retention. We previously found that 4‐Phenylbutyrate (PBA), an FDA‐approved drug, restores GABA uptake and reduces seizures in SLC6A1‐related disorders ...
Melissa B. DeLeeuw +5 more
wiley +1 more source
Developing new techniques to analyse and classify EEG signals [PDF]
, 2018 A massive amount of biomedical time series data such as Electroencephalograph (EEG), electrocardiography (ECG), Electromyography (EMG) signals are recorded daily to monitor human performance and diagnose different brain diseases.
Diykh, Mohammed Abdalhadi
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