Multi-subject classification of Motor Imagery EEG signals using transfer learning in neural networks

Carlos Emiliano Solorzano-Espindola, Erik Zamora, Humberto Sossa

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

Brain-Computer Interfaces are new technologies with a fast development due to their possible usages, which still require overcoming some challenges to be readily usable. The paradigm of motor imagery is among the ones in these types of systems where the pipeline is tuned to work with only one person as it fails to classify the signals of a different person. Deep Learning methods have been gaining attention for tasks involving high-dimensional unstructured data, like EEG signals, but fail to generalize when trained on small datasets. In this work, to acquire a benchmark, we evaluate the performance of several classifiers while decoding signals from a new subject using a leave-one-out approach. Then we test the classifiers on the previous experiment and a method based on transfer learning in neural networks to classify the signals of multiple persons at a time. The resulting neural network classifier achieves a classification accuracy of 73% on the evaluation sessions of four subjects at a time and 74% on three at a time on the BCI competition IV 2a dataset.

Idioma originalInglés
Título de la publicación alojada43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas1006-1009
Número de páginas4
ISBN (versión digital)9781728111797
DOI
EstadoPublicada - 2021
Evento43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, México
Duración: 1 nov 20215 nov 2021

Serie de la publicación

NombreProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (versión impresa)1557-170X

Conferencia

Conferencia43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
País/TerritorioMéxico
CiudadVirtual, Online
Período1/11/215/11/21

Huella

Profundice en los temas de investigación de 'Multi-subject classification of Motor Imagery EEG signals using transfer learning in neural networks'. En conjunto forman una huella única.

Citar esto