Using the General Linear Model to Improve Performance in fNIRS Single Trial Analysis and Classification: A Perspective.

von Lühmann, Alexander; Ortega-Martinez, Antonio; Boas, David A; Yücel, Meryem Ayse

von Lühmann, Alexander; Ortega-Martinez, Antonio; Boas, David A; Yücel, Meryem Ayse.

Afiliación

von Lühmann A; Neurophotonics Center, Biomedical Engineering, Boston University, Boston, MA, United States.
Ortega-Martinez A; Machine Learning Department, Berlin Institute of Technology, Berlin, Germany.
Boas DA; Neurophotonics Center, Biomedical Engineering, Boston University, Boston, MA, United States.
Yücel MA; Neurophotonics Center, Biomedical Engineering, Boston University, Boston, MA, United States.

Front Hum Neurosci ; 14: 30, 2020.

Article en En | MEDLINE | ID: mdl-32132909

Palabras clave

BCI; GLM; HRF; classification; fNIRS; nuisance regression; preprocessing; short-separation

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Front Hum Neurosci Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

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