Intracerebral EEG Artifact Identification Using Convolutional Neural Networks

Manual and semi-automatic identification of artifacts and unwanted physiological signals in large intracerebral electroencephalographic (iEEG) recordings is time consuming and inaccurate. To date, unsupervised methods to accurately detect iEEG artifacts are not available. This study introduces a nov...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Argitaratua izan da:Neuroinformatics
Egile Nagusiak: Nejedly, Petr, Cimbalnik, Jan, Klimes, Petr, Plesinger, Filip, Halamek, Josef, Kremen, Vaclav, Viscor, Ivo, Brinkmann, Benjamin H., Pail, Martin, Brazdil, Milan, Worrell, Gregory, Jurak, Pavel
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: Springer US 2018
Gaiak:
Original Article
Sarrera elektronikoa:https://ncbi.nlm.nih.gov/pmc/articles/PMC6459786/
https://ncbi.nlm.nih.gov/pubmed/30105544
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s12021-018-9397-6
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