Automatic Muscle Artifacts Identification and Removal from Single-Channel EEG Using Wavelet Transform with Meta-Heuristically Optimized Non-Local Means Filter

Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts, which may lead to wrong interpretation in the brain–computer interface (BCI) system as well as in various medical diagnoses. The main objective of this paper is to remove muscle artifacts without distorting the infor...

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Detalles Bibliográficos
Autores principales: Phadikar, Souvik, Sinha, Nidul, Ghosh, Rajdeep, Ghaderpour, Ebrahim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030243/
https://www.ncbi.nlm.nih.gov/pubmed/35458940
http://dx.doi.org/10.3390/s22082948

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030243/
https://www.ncbi.nlm.nih.gov/pubmed/35458940
http://dx.doi.org/10.3390/s22082948

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