NRI: Small: EEG and EMG Human Model-Based Adaptive Control of a Dexterous Artificial Hand

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The research goal of this award is to explore different methods for upper limb amputees to control dexterous artificial hands with brain waves. Biomedical signal processing techniques will be developed to enable this with a single, small recording electrode placed noninvasively on the amputees' heads. The recorded brain waves will be wirelessly transmitted to the hand in real time. A top-level controller will be developed to interpret the intent of the amputees while a low-level controller will be used to synchronize the dexterous grasp motions of the artificial hand. Algorithms will also be developed using tactile feedback from the fingertips to automatically prevent grasped objects from being accidentally dropped when they are transported or disturbed. Amputees will participate in a study to compare the newly developed artificial hand control techniques with brain waves to conventional control techniques with muscle signals during common tasks of daily life.If successful, this research will result in a noninvasive and economic method for amputees to control a dexterous artificial hand with brain waves. This could substantially improve the functionality of prosthetic hands for many amputees. The use of minimal hardware will facilitate the clinical adoption of this technique and the autonomous low-level control algorithms will produce a brain machine interface that places a low cognitive burden on the operator. This research can also be readily applied to benefit many disabled people including stroke victims and quadriplegics and can positively impact other areas of robotics such as improvised explosive disarmament, underwater and space exploration, and rescue robotics. Underrepresented engineering students will benefit from being included in this research plan. Additionally, undergraduate and graduate engineering students will benefit from newly developed classes and laboratory exercises resulting from this research.