نتایج جستجو برای: eeg classification

تعداد نتایج: 521471  

2015
Reinhold Scherer Josef Faller Elisabeth V. C. Friedrich Eloy Opisso Ursula Costa Andrea Kübler Gernot R. Müller-Putz

Brain-computer interfaces (BCIs) translate oscillatory electroencephalogram (EEG) patterns into action. Different mental activities modulate spontaneous EEG rhythms in various ways. Non-stationarity and inherent variability of EEG signals, however, make reliable recognition of modulated EEG patterns challenging. Able-bodied individuals who use a BCI for the first time achieve - on average - bin...

Journal: :International Journal of Computer Applications 2015

Journal: :Balkan Journal of Electrical and Computer Engineering 2020

Journal: :International Journal of Research in Advent Technology 2019

Journal: :International Journal of Computer Applications 2016

Journal: :Computational Intelligence and Neuroscience 2023

Neuromarketing is a modern marketing research technique whereby consumers’ behavior analyzed using neuroscientific approaches. In this work, an EEG database of responses to image advertisements was created, processed, and studied with the goal building predictive models that can classify preference based on their data. Several types analysis were performed three classifier algorithms, namely, S...

2016
Sean J. Colloby Ruth A. Cromarty Luis R. Peraza Kristinn Johnsen Gísli Jóhannesson Laura Bonanni Marco Onofrj Robert Barber John T. O'Brien John-Paul Taylor

Differential diagnosis of Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) remains challenging; currently the best discriminator is striatal dopaminergic imaging. However this modality fails to identify 15-20% of DLB cases and thus other biomarkers may be useful. It is recognised electroencephalography (EEG) slowing and relative medial temporal lobe preservation are supportive featu...

Journal: :Neurocomputing 2014
Xiao-Wei Wang Dan Nie Bao-Liang Lu

Recently, emotion classification from EEG data has attracted much attention with the rapid development of dry electrode techniques, machine learning algorithms, and various real-world applications of brain– computer interface for normal people. Until now, however, researchers had little understanding of the details of relationship between different emotional states and various EEG features. To ...

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