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Single channel electroencephalogram feature extraction based on probability density function for synchronous brain computer interface
Muhammad Shaufil Adha Shawkany Hazim1, Norlaili Mat Safri2, Mohd Afzan Othman3.
Over recent years, there has been an explosive growth of interest in
Electroencephalogram (EEG) based-Brain Computer Interface (BCI). Technically any
architecture of a BCI is designed to have the ability of extracting out a set of features from
brain signal. This paper demonstrated the extraction process based on Probability Density
Function (PDF).A shared control scheme was developed between a mobile robot and
subject. In general, subjects were required to synchronously imagine a star rotating and
mind relaxation at specific time and direction. The imagination of a star would trigger a
mobile robot suggesting that there is an object at certain direction. The mobile robot was
then looking for a target based on probability value assigned to it. The result shows that
95% of theta activity was concentrated at target’s direction (during star imagination) and
reduced when there is no target (during mind relaxation).
Affiliation:
- Universiti Teknologi Malaysia, Malaysia
- Universiti Teknologi Malaysia, Malaysia
- Universiti Teknologi Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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