4.6 Article

Optimal Sensor Set for Decoding Motor Imagery from EEG

Journal

APPLIED SCIENCES-BASEL
Volume 13, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/app13074438

Keywords

brain-computer interface; motor imagery; feature reduction; electroencephalogram; machine learning

Ask authors/readers for more resources

Brain-computer interfaces (BCIs) can enable individuals to interact with devices based on their brain activity. However, the high costs associated with research-grade electroencephalogram (EEG) acquisition devices make them impractical for everyday use. This study demonstrates that decoding movement intention from a limited number of sensors is feasible, opening up the possibility of using commercial sensor devices for BCI control.
Brain-computer interfaces (BCIs) have the potential to enable individuals to interact with devices by detecting their intention from brain activity. A common approach to BCI is to decode movement intention from motor imagery (MI), the mental representation of an overt action. However, research-grade electroencephalogram (EEG) acquisition devices with a high number of sensors are typically necessary to achieve the spatial resolution required for reliable analysis. This entails high monetary and computational costs that make these approaches impractical for everyday use. This study investigates the trade-off between accuracy and complexity when decoding MI from fewer EEG sensors. Data were acquired from 15 healthy participants performing MI with a 64-channel research-grade EEG device. After performing a quality assessment by identifying visually evoked potentials, several decoding pipelines were trained on these data using different subsets of electrode locations. No significant differences (p = [0.18-0.91]) in the average decoding accuracy were found when using a reduced number of sensors. Therefore, decoding MI from a limited number of sensors is feasible. Hence, using commercial sensor devices for this purpose should be attainable, reducing both monetary and computational costs for BCI control.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available