EEG artifact signals tracking and filtering in real time for command control application

Moghavvemi, M. and Attaran, A. and Moshrefpour Esfahani, M.H. (2011) EEG artifact signals tracking and filtering in real time for command control application. In: 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, 20-23 June 2011, Kuala Lumpur.

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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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISSN: 16800737 ISBN: 978-364221728-9 DOI: 10.1007/978-3-642-21729-6_127D
Uncontrolled 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
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Ms. Norhamizah Tamizi
Date Deposited: 25 Mar 2014 09:14
Last Modified: 23 Nov 2017 02:35

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