AR2, a novel automatic muscle artifact reduction software method for ictal EEG interpretation: Validation and comparison of performance with commercially available software

Objective: To develop a novel software method (AR2) for reducing muscle contamination of ictal scalp electroencephalogram (EEG), and validate this method on the basis of its performance in comparison to a commercially available software method (AR1) to accurately depict seizure-onset location. Metho...

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Detalles Bibliográficos
Autores principales: Weiss, Shennan Aibel, Asadi-Pooya, Ali A, Vangala, Sitaram, Moy, Stephanie, Wyeth, Dale H, Orosz, Iren, Gibbs, Michael, Schrader, Lara, Lerner, Jason, Cheng, Christopher K, Chang, Edward, Rajaraman, Rajsekar, Keselman, Inna, Churchman, Perdro, Bower-Baca, Christine, Numis, Adam L, Ho, Michael G, Rao, Lekha, Bhat, Annapoorna, Suski, Joanna, Asadollahi, Marjan, Ambrose, Timothy, Fernandez, Andres, Nei, Maromi, Skidmore, Christopher, Mintzer, Scott, Eliashiv, Dawn S, Mathern, Gary W, Nuwer, Marc R, Sperling, Michael, Engel Jr, Jerome, Stern, John M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2017
Materias:
Software Tool Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5399961/
https://www.ncbi.nlm.nih.gov/pubmed/28491280
http://dx.doi.org/10.12688/f1000research.10569.2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5399961/
https://www.ncbi.nlm.nih.gov/pubmed/28491280
http://dx.doi.org/10.12688/f1000research.10569.2

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