Human-Machine Interface Based on Electromyographic (EMG) Signals Aimed at Limb Rehabilitation for Diabetic Patients

Diabetes is a condition derived from high blood sugar levels for a prolonged period. Which triggers several complications such as anemia, blindness, erectile dysfunction, cardiovascular problems, high blood pressure, poor circulation, and a high probability of gangrene when there is a skin cut on an extremity where the most viable solution to risks is go septicemia or blood poisoning by pathogens generated by dead tissue is amputation of the limb. For such patients, where the limb amputation has already been carried out, tailored solutions are generated with the corresponding rehabilitation by learning to use this new tool to give them independence and inclusivity in their daily lives. Now, technology such as electromyographic sensors is required to read the electrical pulses generated by the muscles and then with artificial intelligence learn to interpret the electrical signals from the muscles of the patient's amputated limb. The main objective of this literature is to relate and obtain a prediction of the diabetes risk index of the general population, based on the incidence data of diabetic disease obtained by delegation in the United States, Mexico. -us through public health institutions. For the above, the prediction will be carried out by a multilayer perceptron neural network and an exploration of human-robot interface (HRI) solutions supported by electromyographic sensors will be carried out.