A collaborative BCI approach to autonomous control of a prosthetic limb system
- Resource Type
- Conference
- Authors
- Katyal, Kapil D.; Johannes, Matthew S.; Kellis, Spencer; Aflalo, Tyson; Klaes, Christian; McGee, Timothy G.; Para, Matthew P.; Shi, Ying; Lee, Brian; Pejsa, Kelsie; Liu, Charles; Wester, Brock A.; Tenore, Francesco; Beaty, James D.; Ravitz, Alan D.; Andersen, Richard A.; McLoughlin, Michael P.
- Source
- 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on. :1479-1482 Oct, 2014
- Subject
- General Topics for Engineers
Robots
Three-dimensional displays
Training
Trajectory
Prosthetic limbs
prosthetics
neural prosthetic system
brain-machine interface
brain-computer interface
semi-autonomous
robotic limb
computer vision
intelligent robotics
hybrid BCI/BMI
modular prosthetic limb
- Language
- ISSN
- 1062-922X
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.