DocumentCode
27580
Title
EEG Activity During Movement Planning Encodes Upcoming Peak Speed and Acceleration and Improves the Accuracy in Predicting Hand Kinematics
Author
Lingling Yang ; Leung, Henry ; Plank, Markus ; Snider, Joseph ; Poizner, Howard
Author_Institution
Dept. of Comput. Sci., City Univ. of Hong Kong, Kowloon, China
Volume
19
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
22
Lastpage
28
Abstract
The relationship between movement kinematics and human brain activity is an important and fundamental question for the development of neural prosthesis. The peak velocity and the peak acceleration could best reflect the feedforward-type movement; thus, it is worthwhile to investigate them further. Most related studies focused on the correlation between kinematics and brain activity during the movement execution or imagery. However, human movement is the result of the motor planning phase as well as the execution phase and researchers have demonstrated that statistical correlations exist between EEG activity during the motor planning and the peak velocity and the peak acceleration using grand-average analysis. In this paper, we examined whether the correlations were concealed in trial-to-trial decoding from the low signal-to-noise ratio of EEG activity. The alpha and beta powers from the movement planning phase were combined with the alpha and beta powers from the movement execution phase to predict the peak tangential speed and acceleration. The results showed that EEG activity from the motor planning phase could also predict the peak speed and the peak acceleration with a reasonable accuracy. Furthermore, the decoding accuracy of the peak speed and the peak acceleration could both be improved by combining band powers from the motor planning phase with the band powers from the movement execution.
Keywords
acceleration; biomechanics; decoding; electroencephalography; feedforward; medical signal processing; statistical analysis; EEG activity; alpha powers; band powers; beta powers; feedforward-type movement; grand-average analysis; hand kinematics; human brain activity; human movement; motor planning phase; movement execution; movement kinematics; movement planning encoding; neural prosthesis; peak acceleration; peak speed; peak velocity; signal-to-noise ratio; statistical correlations; trial-to-trial decoding; Acceleration; Accuracy; Decoding; Electrodes; Electroencephalography; Kinematics; Planning; Alpha and beta band powers; EEG; movement execution; movement planning; peak speed and acceleration;
fLanguage
English
Journal_Title
Biomedical and Health Informatics, IEEE Journal of
Publisher
ieee
ISSN
2168-2194
Type
jour
DOI
10.1109/JBHI.2014.2327635
Filename
6823644
Link To Document