Abstract:
Dependable and efficient utilization of a multigrasp prosthetic hand requires an effective control interface. This interface should be intuitive and direct, offering continuous and proportional control of motion with negligible latency. Realization of such a controller is a challenging problem in upper extremity prosthetics research although several significant strides have been made. Prevalent approaches to multigrasp control thus far include pattern recognition and hierarchical control.
This paper presents the design and preliminary experimental validation of a myoelectric controller that is intended to control the continuous motion of a multigrasp prosthetic hand between nine characteristic postures (reposition, point, hook, lateral pinch, opposition, tip, cylindrical, spherical and tripod). The controller, referred to as multigrasp myoelectric control (MMC) is based on an EMG supervised event-driven finite state machine. The EMG component provides user intent, and consists of a single bipolar signal acquired through two EMG electrodes, similar to EMG interfaces commonly found in commercial myoelectric prostheses. The state machine acts in conjunction with a low-level coordination controller to
activate different actuator subsets (connected to digits via tendons in the prosthesis) based on the present state. The controller incorporates object detection and force estimation algorithms to allow force based state transitions and the estimation of digit forces.
To test the functionality of the controller, experiments were conducted on a healthy subject using an able bodied adapter with a multigrasp prosthetic hand. Experimental results are presented that demonstrate the ability of the MMC to provide effective movement and grasp control of
the multigrasp prosthesis.
