Implementation of sEMG-based real-time embedded adaptive finger force control for a prosthetic hand

This paper presents surface electromyographic (sEMG)-based, real-time Model Reference Adaptive Control (MRAC) strategy for a prosthetic hand prototype. The proposed design is capable of decoding the prerecorded sEMG signal as well as the sensory force feedback from the sensors to control the force of the prosthetic hand prototype using a PIC 32MX360F512L microcontroller. The input sEMG signal is preprocessed using a Half-Gaussian filter and fed to a fusion based Multiple Input Single Output (MISO) skeletal muscle force model. This MISO system provides the estimated finger forces to be produced as input to the prosthetic hand prototype. A simple MRAC method along with a two stage embedded design is used for the force control of the prosthetic hand. The sensed force at the fingertip is fed back to the controller for real-time operation. The data is transmitted to the computer through an universal asynchronous receiver/transmitter (UART) interface of the proposed embedded design. Results show good performance in controlling the finger force as well as shortcomings of the mechanical design of the prosthetic hand prototype to be addressed in future.