EEG artifact signals tracking and filtering in real time for command control application
Document Type
Conference Item
Publication Date
6-1-2011
Abstract
Brain machine interface (BMI) is a direct communication pathway between human's brain and an external device. In some researches it is also called Brain-Computer interface (BCI). There are two types of motor BMIs: invasive and non-invasive. Research on non-invasive BMIs started in the 1980s by measuring brain electrical activity over the scalp electroencephalogram (EEG). In this paper, an attempt in made to present initial steps on a non-invasive BMI design based on pattern recognition algorithm method on EEG signals. These artifact signals are converted to command signals to control and steer an external object. The EEG signal is contaminated with numerous artifact signals which make the assembly of usable artifact signal very difficult. With help of MATLAB program, tracking and filtering of artifact signals in real time application is presented as well.
Keywords
Artifact, BCI, BMI, EEG, Artifact, Artifact signals, BCI, BMI, Brain electrical activity, Brain machine interface, Command control, Command signal, Direct communications, EEG signals, MATLAB program, Non-invasive, Pattern recognition algorithms, Real time, Real-time application
Divisions
fac_eng
Publication Title
IFMBE Proceedings
Publisher
Springer-Verlag
Event Title
5th Kuala Lumpur International Conference on Biomedical Engineering, BIOMED 2011, Held in Conjunction with the 8th Asian Pacific Conference on Medical and Biological Engineering, APCMBE 2011
Event Location
Kuala Lumpur
Event Dates
20-23 June 2011
Event Type
conference
Additional Information
ISSN: 16800737 ISBN: 978-364221728-9 DOI: 10.1007/978-3-642-21729-6_127D