Classification of hand movement direction based on EEG high-gamma activity

Carlos A. Loza, Gavin R. Philips, Mehrnaz Kh Hazrati, Janis J. Daly, Jose C. Principe

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

7 Citas (Scopus)

Resumen

The Electroencephalogram (EEG) is a non-invasive technique used in the medical field to record and analyze brain activity. In particular, Brain Machine Interfaces (BMI) create this bridge between brain signals and the external world through prosthesis, visual interfaces and other physical devices. This paper investigates the relation between particular hand movement directions while using a BMI and the EEG recordings during such movement. The Common Spatial Pattern method (CSP) over the high-γ frequency band is utilized in order to discriminate opposite hand movement directions. The experiment is performed with three subjects and the average classification accuracy is obtained for two different cases.

Idioma originalInglés
Título de la publicación alojada2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas6509-6512
Número de páginas4
ISBN (versión digital)9781424479290
DOI
EstadoPublicada - 2 nov. 2014
Publicado de forma externa
Evento2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, Estados Unidos
Duración: 26 ago. 201430 ago. 2014

Serie de la publicación

Nombre2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Conferencia

Conferencia2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
País/TerritorioEstados Unidos
CiudadChicago
Período26/08/1430/08/14

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