Prosthesis control using undersampled surface electromyographic signals

Amputations can result in disability, permanent physical injury, and even posttraumatic stress disorder. Upper extremity amputations are mostly work-related, and such injuries include about 7% of the total burden of disease. High-functional artificial limbs are not available to most amputees because of their high price and the lack of public health coverage. Thus, there has been a significant interest in the design and fabrication of low-cost active upper-limb prostheses. Such devices are usually controlled by surface electromyographic (sEMG) signals. Recently, portable, low-cost recording devices such as Thalmic Labs Myo Gesture Control Armband have been used in the movement detection. Such devices use undersampled sEMG signals. In this chapter, we discuss upper-limb prostheses and their control. We further provide the results of some experiments showing that such undersampled signals could be used for various applications required in advanced prosthesis control, e.g., force prediction, elbow angle prediction, movement detection, and time and frequency parameter extraction using undersampled sEMG signals. Finally, a low-cost controller for BRUNEL HAND 2.0 from Open Bionics is designed to link low-cost recording and prosthesis.This work was supported by the Ministry of Economy and Competitiveness (MINECO), Spain, under contract DPI2017-83989-R and the Ministry of Science and Innovation (MICINN), Spain, under contract PRE2018-085387. CIBER-BBN is an initiative of the Instituto de Salud Carlos III, Spain. JF Alonso is a Serra Hunter Fellow. The research leading to this results has also received funding from the European's Union Horizon 2020 research and innovation program under the Marie Slodowska-Curie Grant Agreement No 712349 (TECNIOspring PLUS) and from the Agency for Business Competitiveness of the Government of Catalonia.Postprint (published version