Assistive technology design and preliminary testing of a robot platform based on movement intention using low-cost brain computer interface

"The process through which children learn about the world and develop perceptual, cognitive and motor skills relies heavily on object exploration in their physical world. New types of assistive technology that enable children with impairments to interact with their environment have emerged in r...

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Detalles Bibliográficos
Autores Principales: Sakamaki I., Del Campo C.E.P., Wiebe S.A., Tavakoli M., Adams K.
Formato: Objeto de conferencia (Conference Object)
Lenguaje:Inglés (English)
Publicado: Institute of Electrical and Electronics Engineers Inc. 2017
Materias:
Acceso en línea:https://repository.urosario.edu.co/handle/10336/24029
https://doi.org/10.1109/SMC.2017.8122954
Descripción
Sumario:"The process through which children learn about the world and develop perceptual, cognitive and motor skills relies heavily on object exploration in their physical world. New types of assistive technology that enable children with impairments to interact with their environment have emerged in recent years, and they could be beneficial for children's cognitive and perceptual skills development. Many studies have reported on brain computer interface (BCI) research. However, a conventional electroencephalography (EEG) system is generally bulky and expensive. It also requires special equipment and technical expertise to operate successfully. In this study, a compact low-cost EEG system was used to detect signals related to movement intention and control a mobile robot control. EEG signals of three non-disabled adults were acquired by the BCI system and the movement intention was classified during physical movement and motor imagery. The average classification accuracies achieved during testing were 56.4% for the motor imagery and 72.7% for the physical movement. The results show moderate classification accuracy for the motor imagery; however, the classification accuracy for the physical movement was high for all the subjects. Even though further improvement of the system is still needed, the experimental results demonstrated the feasibility of a BCI-based robotic system that is affordable and accessible for many people including children with disabilities. © 2017 IEEE."