{'fraction_non_alphanumeric': 0.02072141212586339, 'fraction_numerical': 0.0, 'mean_word_length': 5.037037037037037, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Development of an adaptive framework for the control of upper limb myoelectric prosthesis

This work presents the development of a sensor for detecting human muscle contraction, which captures myoelectric signals (EMG), in order to control a myoelectric prosthesis of superior limb. The analysis of the signal is carried out through software running in a microcontroller that decides how to open or close the artificial hand. The facilities in changing the acting form by software makes its use attractive for the patient. New state functions (for example, if the hand is open, closed, semi-closed, etc.) can be easily added to the prosthesis with a simple alteration in the microcontroller program, without any hardware alteration. The authors propose a strategy for controlling the artificial hand, based on the myoelectric signal, and using a servomotor that drives the prosthesis mechanisms. This way, the patient has a more accurate and easier control of the movement of the prosthetic device, thus leading to a faster adaptation. Through a proposed control strategy, a method to analyze the pattern of the myoelectric signal can be defined. Thus, several kinds of actuating of the artificial hand can be obtained by a simple binary signal or through the analysis of the myoelectric signal pattern.