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

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...

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Main Authors: Moghavvemi, M., Attaran, A., Moshrefpour Esfahani, M.H.
Format: Conference or Workshop Item
Published: Springer-Verlag 2011
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Online Access:http://eprints.um.edu.my/9741/
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spelling my.um.eprints.97412017-11-23T02:35:50Z http://eprints.um.edu.my/9741/ EEG artifact signals tracking and filtering in real time for command control application Moghavvemi, M. Attaran, A. Moshrefpour Esfahani, M.H. TA Engineering (General). Civil engineering (General) 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. Springer-Verlag 2011-06 Conference or Workshop Item PeerReviewed 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.
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Moghavvemi, M.
Attaran, A.
Moshrefpour Esfahani, M.H.
EEG artifact signals tracking and filtering in real time for command control application
description 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.
format Conference or Workshop Item
author Moghavvemi, M.
Attaran, A.
Moshrefpour Esfahani, M.H.
author_facet Moghavvemi, M.
Attaran, A.
Moshrefpour Esfahani, M.H.
author_sort Moghavvemi, M.
title EEG artifact signals tracking and filtering in real time for command control application
title_short EEG artifact signals tracking and filtering in real time for command control application
title_full EEG artifact signals tracking and filtering in real time for command control application
title_fullStr EEG artifact signals tracking and filtering in real time for command control application
title_full_unstemmed EEG artifact signals tracking and filtering in real time for command control application
title_sort eeg artifact signals tracking and filtering in real time for command control application
publisher Springer-Verlag
publishDate 2011
url http://eprints.um.edu.my/9741/
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score 13.211869