DocumentCode :
139388
Title :
Electrocorticogram encoding of upper extremity movement duration
Author :
Wang, Po T. ; King, Christine E. ; McCrimmon, Colin M. ; Shaw, Susan J. ; Millett, David E. ; Liu, Charles Y. ; Chui, Luis A. ; Nenadic, Zoran ; Do, An H.
Author_Institution :
Dept. of Biomed. Eng., Univ. of California, Irvine, Irvine, CA, USA
fYear :
2014
fDate :
26-30 Aug. 2014
Firstpage :
1243
Lastpage :
1246
Abstract :
Electrocorticogram (ECoG) is a promising long-term signal acquisition platform for brain-computer interface (BCI) systems such as upper extremity prostheses. Several studies have demonstrated decoding of arm and finger trajectories from ECoG high-gamma band (80-160 Hz) signals. In this study, we systematically vary the velocity of three elementary movement types (pincer grasp, elbow and shoulder flexion/extension) to test whether the high-gamma band encodes for the entirety of the movements, or merely the movement onset. To this end, linear regression models were created for the durations and amplitudes of high-gamma power bursts and velocity deflections. One subject with 8×8 high-density ECoG grid (4 mm center-to-center electrode spacing) participated in the experiment. The results of the regression models indicated that the power burst durations varied directly with the movement durations (e.g. R2=0.71 and slope=1.0 s/s for elbow). The persistence of power bursts for the duration of the movement suggests that the primary motor cortex (M1) is likely active for the entire duration of a movement, instead of providing a marker for the movement onset. On the other hand, the amplitudes were less co-varied. Furthermore, the electrodes of maximum R2 conformed to somatotopic arrangement of the brain. Also, electrodes responsible for flexion and extension movements could be resolved on the high-density grid. In summary, these findings suggest that M1 may be directly responsible for activating the individual muscle motor units, and future BCI may be able to utilize them for better control of prostheses.
Keywords :
biomechanics; biomedical electrodes; electroencephalography; encoding; medical signal processing; regression analysis; ECoG high-gamma band signals; arm trajectories; brain-computer interface systems; center-to-center electrode spacing; distance 4 mm; elbow flexion-extension; electrocorticogram encoding; extension movements; finger trajectories; flexion movements; frequency 80 Hz to 160 Hz; high-density ECoG grid; high-gamma band encoding; high-gamma power burst amplitudes; high-gamma power burst durations; individual muscle motor units; linear regression models; long-term signal acquisition platform; movement onset; pincer grasp; primary motor cortex; shoulder flexion-extension; somatotopic arrangement; upper extremity movement duration; upper extremity prostheses; velocity deflections; Biological system modeling; Decoding; Elbow; Electrodes; Joints; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2014.6943822
Filename :
6943822
Link To Document :
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