An EMG-Controlled Hand Exoskeleton for Natural Pinching
Lenny Lucas*, Matthew DiCicco*, and Yoky Matsuoka*,**
*Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA
**Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 5000 Forbes Ave. NSH3207, Pittsburgh, PA 15213
Spinal cord and other local injuries often lead to partial paralysis while the brain stays fully functional. When this partial paralysis occurs in the hand, these individuals are not able to execute daily activities on their own even if their arms are functional. To remedy this problem, a lightweight, low-profile orthotic exoskeleton has been designed to restore dexterity to paralyzed hands. The exoskeleton’s movements are controlled by the user’s available electromyography (EMG) signals. The device has two actuators controlling the index finger flexion that can be used to perform a pinching motion against a fixed thumb. Using this orthotic device, a new control technique was developed to allow for a natural reaching and pinching sequence by utilizing the natural residual muscle activation patterns. To design this controller, two actuator control algorithms were explored with a quadriplegic (C5/C6) subject and it was determined that a simple binary control algorithm allowed for faster interaction with objects over a variable control algorithm. The binary algorithm was then used as an enabling algorithm to activate the exoskeleton movements when the natural sequence of muscle activities found a pattern related to a pinch. This natural pinching technique has shown significant promise toward realistic neural control of wearable robotic devices to assist paralyzed individuals.
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