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Published October 2014 | public
Book Section - Chapter

A collaborative BCI approach to autonomous control of a prosthetic limb system


Existing brain-computer interface (BCI) control of highly dexterous robotic manipulators and prosthetic devices typically rely solely on neural decode algorithms to determine the user's intended motion. Although these approaches have made significant progress in the ability to control high degree of freedom (DOF) manipulators, the ability to perform activities of daily living (ADL) is still an ongoing research endeavor. In this paper, we describe a hybrid system that combines elements of autonomous robotic manipulation with neural decode algorithms to maneuver a highly dexterous robotic manipulator for a reach and grasp task. This system was demonstrated using a human patient with cortical micro-electrode arrays allowing the user to manipulate an object on a table and place it at a desired location. The preliminary results for this system are promising in that it demonstrates the potential to blend robotic control to perform lower level manipulation tasks with neural control that allows the user to focus on higher level tasks thereby reducing the cognitive load and increasing the success rate of performing ADL type activities.

Additional Information

© 2014 IEEE. The authors would like to thank John Helder and John Roycroft for their help with configuring the MPL systems for experimentation and data acquisition. The authors would like to say special thanks to EGS for participating in the study. This work was supported by the Space and Naval Warfare Systems Command under Contract N66001-10-C-4056 20100630. Any opinions, findings and conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the Defense Advanced Research Projects Agency or Space and Naval Warfare Systems Command.

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August 20, 2023
October 20, 2023