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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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. |
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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 |
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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. |
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/ |
_version_ |
1643688643097788416 |
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13.211869 |