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Brain-Computer Interfaces for Control of Upper Extremity Neuroprostheses in Individuals with High Spinal Cord Injury
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Author(s): Rüdiger Rupp (Heidelberg University Hospital, Spinal Cord Injury Center, Germany), Martin Rohm (Heidelberg University Hospital, Spinal Cord Injury Center, Germany)and Matthias Schneiders (Heidelberg University Hospital, Spinal Cord Injury Center, Germany)
Copyright: 2014
Pages: 28
Source title:
Emerging Theory and Practice in Neuroprosthetics
Source Author(s)/Editor(s): Ganesh R. Naik (University of Technology Sydney (UTS), Australia)and Yina Guo (Taiyuan University of Science and Technology, China)
DOI: 10.4018/978-1-4666-6094-6.ch012
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Abstract
For individuals with tetraplegia, restoring limited or missing grasping function is the highest priority. In patients with high Spinal Cord Injury (SCI) and a lack of surgical options, restricted upper extremity function can be improved with the use of neuroprostheses based on Functional Electrical Stimulation (FES). Grasp neuroprostheses with different degrees of complexity and invasiveness exist, although few models are available for routine clinical application. Hybrid systems combining FES with orthoses hold promise for restoring completely lost upper extremity function. Novel user interfaces integrating biosignals from several sources are needed to make full use of the many degrees of freedom of hybrid neuroprostheses. Motor Imagery (MI)-based Brain-Computer Interfaces (BCIs) are an emerging technology that may serve as a valuable adjunct to traditional control interfaces. This chapter provides an overview of the current state of the art of BCI-controlled upper-extremity neuroprostheses and describes the challenges and promises for the future.
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