Results 51 to 60 of about 49,854 (168)
MethodsXElectroencephalography (EEG) data recorded during full-body movement is prone to artifacts that compromise signal quality. We introduce EEG-cleanse, a modular and fully automated preprocessing pipeline for cleaning EEG signals collected in dynamic, real ...
Carolina Rico-Olarte +2 more
doaj +1 more source
Robust artifactual independent component classification for BCI practitioners [PDF]
, 2014 Objective. EEG artifacts of non-neural origin can be separated from neural signals by independent component analysis (ICA). It is unclear (1) how robustly recently proposed artifact classifiers transfer to novel users, novel paradigms or changed ...
Allefeld, Carsten +5 more
core +1 more source
, 2014 Energy consumption is an important issue in continuous wireless telemonitoring of physiological signals. Compressed sensing (CS) is a promising framework to address it, due to its energy-efficient data compression procedure.
Jung, Tzyy-Ping +4 more
core +1 more source
Towards predicting posttraumatic stress symptom severity using portable EEG-derived biomarkers
Scientific ReportsPosttraumatic Stress Disorder (PTSD) is a heterogeneous mental health disorder that can develop following a traumatic experience. Understanding its neurobiological basis is crucial to advance early diagnosis and treatment.
Ashritha Peddi +8 more
doaj +1 more source
A large-scale evaluation framework for EEG deep learning architectures
, 2018 EEG is the most common signal source for noninvasive BCI applications. For such applications, the EEG signal needs to be decoded and translated into appropriate actions.
Ball, Tonio +5 more
core +1 more source
Automatic sleep staging using ear-EEG
BioMedical Engineering OnLine, 2017 Background Sleep and sleep quality assessment by means of sleep stage analysis is important for both scientific and clinical applications. Unfortunately, the presently preferred method, polysomnography (PSG), requires considerable expert assistance and ...
Kaare B. Mikkelsen +3 more
doaj +1 more source
A method for classifying mental tasks in the space of EEG transforms [PDF]
, 2009 In this article we describe a new method for supervised classification of EEG signals. This method applies to the power spectrum density data and assigns class-dependent information weights to individual pixels, so that the decision is defined by the ...
Amorim, R, Gan, JQ, Mirkin, B
core
Privacy for Personal Neuroinformatics
, 2014 Human brain activity collected in the form of Electroencephalography (EEG), even with low number of sensors, is an extremely rich signal. Traces collected from multiple channels and with high sampling rates capture many important aspects of participants'
Greenwood, Dazza +3 more
core +1 more source
Development of an algorithm for detecting slow peak-wave activity in non-convulsive forms of epilepsy [PDF]
Известия высших учебных заведений: Прикладная нелинейная динамикаThe purpose of this study is to develop a classifier capable of detecting typical absence seizures in real-time using electroencephalogram (EEG) data and a Support Vector Machine (SVM) model. Methods.
Belokopytov, Anton Сергеевич +3 more
doaj +1 more source
Non-invasive surface electroencephalography for broilers
MethodsXOur research aimed to develop a non-invasive EEG method for broiler chickens that can be utilized in basic research and practical applications. We evaluated the success of 1) the application and attachment of the EEG electrodes to the head of broiler and
Yukari Togami +4 more
doaj +1 more source