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Motor prediction in brain-computer interfaces for controlling mobile robots

Geng, T and Gan, JQ (2008) Motor prediction in brain-computer interfaces for controlling mobile robots. In: UNSPECIFIED, ? - ?.

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Abstract

EEG-based Brain-Computer Interface (BCI) can be regarded as a new channel tor motor control except that it does not involve muscles. Normal neuromuseular motor control has two fundamental components: (1) to control the body, and (2) to predict the consequences of the control command, which is called motor prediction. In this study, after training with a specially designed BCI paradigm based on motor imagery, two subjects learnt to predict the time course of some features of the EEG signals. It is shown that, with this newly-obtained motor prediction skill, subjects can use motor imagery of feet to directly control a mobile robot to avoid obstacles and reach a small target in a time-critical scenario. © 2008 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 14 Dec 2012 10:10
Last Modified: 23 Jan 2019 00:15
URI: http://repository.essex.ac.uk/id/eprint/4156

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