TY - GEN
T1 - Beamformer Source Estimation Improves Accuracy of Motor-Imagery-based Brain Computer Interface
AU - Chan, Hui Ling
AU - Wang, Jung Wei
AU - Chen, Yong Sheng
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Motor-imagery-based brain computer interface has advantages in high information transition rate and has potential to achieve high portability without using a display for visual stimulation. However, electroencephalographic data is a mixture of neural activity from various brain locations and also external artifacts. This paper presents a novel method utilizing source-level features computed based on maximum contrast beamformer. The estimated source activity has the maximum contrast between the power during the reference period and the period that event-related synchronization or desynchronization emerges. Moreover, this method utilizes the classification structure based on divide-and-conquer concept to identify four classes of motor imageries, including left hand, right hand, tongue, and foot. The experimental results demonstrate the improvement in classification accuracy by using the proposed method.
AB - Motor-imagery-based brain computer interface has advantages in high information transition rate and has potential to achieve high portability without using a display for visual stimulation. However, electroencephalographic data is a mixture of neural activity from various brain locations and also external artifacts. This paper presents a novel method utilizing source-level features computed based on maximum contrast beamformer. The estimated source activity has the maximum contrast between the power during the reference period and the period that event-related synchronization or desynchronization emerges. Moreover, this method utilizes the classification structure based on divide-and-conquer concept to identify four classes of motor imageries, including left hand, right hand, tongue, and foot. The experimental results demonstrate the improvement in classification accuracy by using the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=85062793358&partnerID=8YFLogxK
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U2 - 10.1109/ICDSP.2018.8631798
DO - 10.1109/ICDSP.2018.8631798
M3 - Conference contribution
AN - SCOPUS:85062793358
T3 - International Conference on Digital Signal Processing, DSP
BT - 2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on Digital Signal Processing, DSP 2018
Y2 - 19 November 2018 through 21 November 2018
ER -