Duk Shin, Yasuhiko Nakanishi, Chao Chen, Hiroyuki Kambara, Natsue Yoshimura and Yasuharu Koike
Brain-machine interface techniques have been applied in a number of studies to control neuromotor prostheses and for neuro-rehabilitation in the hopes of providing a means to restore lost motor function. Electrocorticography has seen recent use in this regard because it offers a higher spatiotemporal resolution than non-invasive electroencephalography and is less invasive than intracortical microelectrodes. Despite lots of successful studies; none of study has dealt with the importance of both kinematic and kinetic information for the purpose of realizing an ECoG-based neuroprosthesis. Here, we review the decoding kinetic and kinematic information from electrocorticograms. First, we introduce our preprocessing method for decoding of muscle activities, hand trajectories, and joint angles with our previous works. Second, we review and discuss about three questions: which locations are most effective area for decoding, how different numbers of effective electrocorticography signals affect decoding performance, and which frequency band is most effective? We foresee the proposed method contributing to future advancements in neuro-prosthesis and neurorehabilitation technology.
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International Journal of Neurorehabilitation received 1078 citations as per Google Scholar report
