Biomedical signal filtering for noisy environments
Contribuinte(s) |
Nahavandi Saeid |
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Data(s) |
01/12/2014
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Resumo |
Luke's work addresses issue of robustly attenuating multi-source noise from surface EEG signals using a novel Adaptive-Multiple-Reference Least-Means-Squares filter (AMR-LMS). In practice, the filter successfully removes electrical interference and muscle noise generated during movement which contaminates EEG, allowing subjects to maintain maximum mobility throughout signal acquisition and during the use of a Brain Computer Interface. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Deakin Univeristy, Strategic Research Centre, Centre for Intelligence Systems Research |
Relação |
http://dro.deakin.edu.au/eserv/DU:30079016/nyhof-agreement-2015.pdf http://dro.deakin.edu.au/eserv/DU:30079016/nyhof-biomedicalsignal-2015A.pdf |
Direitos |
The Author. All Rights Reserved |
Palavras-Chave | #medical imaging #electroencephalograph (EEG) #multi-source noise #noise filter |
Tipo |
Thesis |