• 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