Subject-specific channel selection for classification of motor imagery electroencephalographic dataReportar como inadecuado




Subject-specific channel selection for classification of motor imagery electroencephalographic data - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

* Corresponding author 1 LTCI - Laboratoire Traitement et Communication de l-Information 2 Orange Labs Issy les Moulineaux

Abstract : Brain-computer interfaces BCIs are systems that record brain signals and then classify them to generate computer commands. Keeping a minimal number of channels electrodes is essential for developing portable BCIs. Unlike existing methods choosing channels without optimization of time segment for classification, this work proposes a novel subject-specific channel selection method based on a criterion derived from Fisher-s discriminant analysis to realize the parametrization of both time segment and channel positions. The experimental results show that the method can efficiently reduce the number of channels from 118 channels to no more than 11, and shorten the training time, without a significant decrease of classification accuracy on a standard dataset.

Keywords : Brain computer interfaces electroencephalography biomedical signal processing machine learning





Autor: Yuan Yang - Olexiy Kyrgzov - Joe Wiart - Isabelle Bloch -

Fuente: https://hal.archives-ouvertes.fr/



DESCARGAR PDF




Documentos relacionados