Myoelectric control of prosthetics and robotics

Prosthetic limbs improve mobility and give people the power to perform tasks that would otherwise be arduous to undertake. In our research, we have developed a functional, 3D printed prosthetic hand. This hand detects and interprets the myoelectric signal from healthy muscles to control motors that move the prosthetic fingers and wrist, mimicking the functionality of a true hand. In order to detect a myoelectric signal, we use two electrodes placed across the muscle of interest. The signal from these two electrodes is measured differentially using an instrumentation amplifier. The signal from the instrumentation amplifier is then sent into a twin t-notch filter to remove the parasitic 60 Hz noise; this filtering increases the signal to noise ratio to approximately 10:1. We also send the signal through a high pass RC filter to remove any DC offset. Finally, the signal is sent to an additional amplification stage before being interpreted by a microcontroller. The microcontroller uses a simple threshold algorithm to decide if the hand should be opened or closed. In conclusion, we were able to create a functional 3D printed prosthetic hand controlled via myoelectric sensing and interpretation.