Surface Electromyography Based Control of a Prosthetic Hand

An ideal prosthetic hand should provide individual finger actuation in various states of flexion to achieve improved dexterity and functionality, instead of either fully open or closed positions as seen in many conventional prosthetic hands. In order to control fingers, a suitable control input such as electromyography signal is needed. Electromyograms or electromyography signals are the measured electric potentials that are generated during skeletal muscle contraction. These electromyography signals have been used for the control of many prosthetic hands. Surface electromyography involves the placement of non-invasive adhesive electrodes on the surface of skin covering the targeted muscle, which in this case is the forearm. This technique is safer, simpler and also facilitates the use for prolonged periods of time when compared to the invasive methods. Electromyography signals are weak in nature and they require amplification and filtering. This thesis presents a fully-fledged integrated system to measure and process the electromyography signals, and then use these signals to control a unique prosthetic hand. The system also has flex sensors and processing boards for measuring the position of the fingers which provides feedback for the controller. A driver board is used for actuating the artificial muscles in the robotic hand, which receives power form a rechargeable battery. All the boards are controlled by NVIDIA Jetson TX2 Module. Important features of the prosthetic hand presented here are lightweight structure, low cost and silent actuation when compared with others. It uses the relatively new polymer artificial muscles, Twisted and Coiled polymer (TCP) muscles, based on silver-coated nylon. Prosthetic hands typically use electromechanical actuators or pneumatic actuators, which are heavy and bulky. TCP muscles have a high power to weight ratio and can be electrothermally-actuated by Joule heating effect. In this thesis, the performance of the TCP muscle-actuated prosthetic hand through the use of EMG signals is presented, mainly focusing on classical control systems such as proportional (P) controllers, and proportional and integral (PI ) controllers.