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ASME Press Select Proceedings
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)Available to Purchase
Editor
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859896
No. of Pages:
906
Publisher:
ASME Press
Publication date:
2011

Brain signals via scalp Electroencephalography (EEG) can be used by patients with severe motor impairments to communicate with their environment. This can be done by brain—computer interface (BCI) system. This work is based upon utilizing the brain signals of a human-being for the extraction of rhythmic activity from one or two channel noninvasively recorded signal using IEEE standard 1057 algorithm and the classification (using SVM ) of important information which can be used to get the control of a robot's navigation without physical strain. The procedure includes acquisition and analysis of brain signals via EEG equipment, development of a classification system using SVM techniques.

Abstract
Keywords
Introduction
Feature Extraction
Classification of Signals
Results
Conclusions
References
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