A two-bit binary control system for an orthotic, hand-assistive exoskeleton

A combined 450,000 Americans suffer from multiple sclerosis, chronic carpal tunnel syndrome, and muscular dystrophy; debilitative disorders that result in a loss of muscle strength and dexterity within the afflicted individual. A controlled orthotic exoskeleton presents a solution by amplifying a user's residual strength to restore precision pinch and/or power grasp motions. In order to optimize system response time and control accuracy, a two-bit binary state control algorithm was designed using LabVIEW v8.5. The states of the control system were refined using positional and object-sensing information supplied via negative feedback from Hall effect angular sensors and force sensing resistors. Forearm EMG was recorded and used to characterize hand strength with and without the mechanical assistance generated from the hand-assistive exoskeleton. The control system was tested using simulated sensor feedback data and has proven to be a robust design. The controller will be integrated with a glove-like, hand-based exoskeleton. The complete system was designed to restore hand functionality through the amplification of precision pinch and/or power grasp.