ABSTRACT
Currently, many upper limb prosthesis solutions are being presented, which are activated through the recording and processing of muscle activity, for which electromyography signal acquisition circuits are developed, where they are processed to find a level of activation necessary to activate various 360mechanisms that belong to the prosthesis. In the present work, we use a wearable device that performs the simultaneous recording of eight muscles, because it has integrated eight acquisition channels, and the device allows the recording and wireless sending of signals to various devices. As a result, we present an acquisition protocol where the registration of the arm muscles is performed, where we separate each of the signals that correspond to a particular muscle. The proposed method can be used in various applications where it is required to characterize the work of certain muscles in certain activities, which can create a database of the behavior of each muscle for certain activities, in order to improve the design of prostheses. As conclusion, we present how these signals can be used to recognize characteristic patterns using artificial intelligence techniques.
