TY - GEN
T1 - A translational roadmap for a brain-machine-interface (BMI) system for rehabilitation
AU - Craik, Alexander
AU - Kilicarslan, Atilla
AU - Contreras-Vidal, Jose L.
N1 - Funding Information:
*This work is supported by NSF-PFI-RP award #1827769 Alexander Craik is with the IUCRC BRAIN Center, University of Houston, TX 77004 USA. (Phone: 713-743-0796; fax: 713-743-4444; email: arcraik@uh.edu) Atilla Kilicarslan is with the IUCRC BRAIN Center, University of Houston, TX 77004 USA. (Phone: 832-276-1789, email: akilica2@central.uh.edu) Jose L. Contreras-Vidal is with the IUCRC BRAIN Center, University of Houston, TX 77004 USA. (Phone: 713-743-4429, email: jlcontreras-vidal@uh.edu)
Funding Information:
The translational research and development of the BMI system, supported under a National Science Foundation Partnerships for Innovation (PFI) award, is comprised of three main components: 1) the BMI Module, 2) the Information and Control (IC) Module, and 3) a multifunctional single degree of freedom Upper Limb Rehabilitation Robot as the initial robotic platform. A schematic of this system is presented in Figure 1.While the system is shown as being operated with the actuator at the elbow, the BMI system is not limited to this setup and is also intended to be applicable for a variety of upper limb rehabilitation methods programs.
Funding Information:
The authors would like to acknowledge Youngmok Yun from Harmonic Bionics, Gerard E. Francisco from Memorial Hermann Hospital’s Institute for Rehabilitation and Research (TIRR), Igor Alvarado from National Instruments, and Shaheen Lokhandwala from the University of Houston's Office of Technology Transfer for their guidance and collaboration.
Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/10
Y1 - 2019/10
N2 - In this communication, a translational roadmap for a noninvasive Brain Machine Interface (BMI) system for rehabilitation is presented. This multi-faceted project addresses important engineering, clinical, end user and regulatory challenges. The goal is to improve the feasibility of at-home neurorehabilitation for patients with chronic stroke by providing a low-cost, portable, form fitting, reliable, and easy-to-use system. The proposed BMI system is also designed to enable direct communication between the end-user and clinician, allowing for continuous patient specific rehabilitation optimization.
AB - In this communication, a translational roadmap for a noninvasive Brain Machine Interface (BMI) system for rehabilitation is presented. This multi-faceted project addresses important engineering, clinical, end user and regulatory challenges. The goal is to improve the feasibility of at-home neurorehabilitation for patients with chronic stroke by providing a low-cost, portable, form fitting, reliable, and easy-to-use system. The proposed BMI system is also designed to enable direct communication between the end-user and clinician, allowing for continuous patient specific rehabilitation optimization.
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U2 - 10.1109/SMC.2019.8914210
DO - 10.1109/SMC.2019.8914210
M3 - Conference contribution
AN - SCOPUS:85076775907
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 3613
EP - 3618
BT - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
Y2 - 6 October 2019 through 9 October 2019
ER -