Results 61 to 70 of about 874,261 (376)

AR-PCA-HMM approach for sensorimotor task classification in EEG-based brain-computer interfaces [PDF]

open access: yes, 2010
We propose an approach based on Hidden Markov models (HMMs) combined with principal component analysis (PCA) for classification of four-class single trial motor imagery EEG data for brain computer interfacing (BCI) purposes. We extract autoregressive (AR)
Argunsah, Ali Ozgur   +3 more
core   +1 more source

Accelerated Progression of Gait Impairment in Parkinson's Disease and REM Sleep Without Atonia

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective People with Parkinson's disease (PD) and rapid eye movement (REM) sleep without atonia (RSWA) often have more severe gait disturbances compared to PD without RSWA. The association between the presence and expression of RSWA and the rate of progression of gait impairment in PD is unknown.
Sommer L. Amundsen‐Huffmaster   +11 more
wiley   +1 more source

Detection of intention level in response to task difficulty from EEG signals [PDF]

open access: yes, 2013
We present an approach that enables detecting intention levels of subjects in response to task difficulty utilizing an electroencephalogram (EEG) based brain-computer interface (BCI).
Cetin, Mujdat   +7 more
core   +1 more source

Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug‐Resistant Epilepsy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To develop a novel deep‐learning model of clinical DWI tractography that can accurately predict the general assessment of epilepsy severity (GASE) in pediatric drug‐resistant epilepsy (DRE) and test if it can screen diverse neurocognitive impairments identified through neuropsychological assessments.
Jeong‐Won Jeong   +7 more
wiley   +1 more source

EEG is better left alone

open access: yesbioRxiv, 2022
Automated preprocessing methods are critically needed to process the large publicly-available EEG databases, but the optimal approach remains unknown because we lack data quality metrics to compare them.
A. Delorme
semanticscholar   +1 more source

Transfer Learning for EEG-Based Brain–Computer Interfaces: A Review of Progress Made Since 2016 [PDF]

open access: yesIEEE Transactions on Cognitive and Developmental Systems, 2020
A brain–computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common noninvasive BCI modality, electroencephalogram (EEG), is sensitive to noise/artifact and suffers between-subject/within-subject ...
Dongrui Wu, Yifan Xu, Baoliang Lu
semanticscholar   +1 more source

A Comprehensive Overview of the Clinical, Electrophysiological, and Neuroimaging Features of BPAN: Insights From a New Case Series

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Neurodegeneration with brain iron accumulation (NBIA) comprises a genetically and clinically heterogeneous group of rare neurological disorders characterized particularly by iron accumulation in the basal ganglia. To date, 15 genes have been associated with NBIA.
Seda Susgun   +95 more
wiley   +1 more source

Forventninger og helserett ved Ila fengsel og forvaringsanstalt

open access: yesKritisk Juss, 2023
Soningsforholdene ved Ila fengsel og forvaringsanstalt har vært kritisert gjennom flere år, særlig med henblikk på isolasjon. Forventningene om forbedring er delvis utformet som forventninger til helsevesenet.
Øyvind Holst, Hanne Eeg-Henriksen
doaj   +1 more source

Non-factorizable effects in B-anti-B mixing

open access: yes, 2003
We study the B-parameter (``bag factor'') for B-anti-B mixing within a recently developed heavy-light chiral quark model. Non-factorizable contributions in terms of gluon condensates and chiral corrections are calculated.
Eeg, J. O., Hiorth, A.
core   +1 more source

Effects of force load, muscle fatigue and extremely low frequency magnetic stimulation on EEG signals during side arm lateral raise task [PDF]

open access: yes, 2017
Objective: This study was to quantitatively investigate the effects of force load, muscle fatigue and extremely low frequency (ELF) magnetic stimulation on electroencephalography (EEG) signal features during side arm lateral raise task.
Biller S   +14 more
core   +2 more sources

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