Analysis and identification of the movements of a human arm using an electromyographic signal acquisition and processing system

Abstract

Using MATLAB for the development of an EMG signal acquisition and processing system, to identify the different movements generated by a human arm such as flexion, extension, pronation and supination.Previously, information of the aforementioned movements is obtained to determine the best method of processing these signals generated by the movements. We proceed to program in Matlab to acquire and process these signals in real time. The acquisition system is made up of an EMG sensor implemented with an accelerometer sensor that helps determine the position and the set is connected to an Arduino Promicro that is configured as an interface for data acquisition with Matlab. These signals that are processed by Matlab will be shown by a graph.The sample to validate the equipment obtained a population of 94 people, where 96% of success was evidenced, this plus the statistical analysis of chi-square to evaluate and validate the hypothesis. According to the responses obtained in real time it was necessary to modify the position of the EMG device in the test arm, power source and have enough information to avoid errors.La muestra para validar el equipo se obtiene una población de 94 personas, en donde se evidencio el 96% de éxito, esto más el análisis estadístico de chi-cuadrado para evaluar y validar la hipótesis. Según las respuestas obtenidas en tiempo real se vio necesario modificar la posición del dispositivo EMG en el brazo de pruebas, fuente de alimentación y tener la suficiente información para evitar errores.