A Robust, Practical Upper Limb Electromyography Interface Using Dry 3D Printed Electrodes

This study aims to develop a practical, robust and reliable human-machine interface using gesture recognition based on surface electromyography (sEMG) signals from the forearm. This technology is developed to be employed medically in stroke rehabilitation or prosthetic control. So far, studies have been conducted that improved the accuracy of such systems, but little has been done to avoid using wet (gelled) electrodes and hence improve their reliability and robustness for long-term use. Through this study, a comfortable and wearable bio- signal acquisition device is designed and developed that uses dry EMG electrodes. 3D printed electrodes are compared with ready-made dry ones to choose the better option, and an interface is established that allows control of any mechatronic system such as a prosthetic arm.