Electronic acquisition of the electromyographic signal - Phase 1

This document evidences the research proposal, focused on the electronic design for the acquisition and conditioning of the electromyographic signal, from non-invasive methods for subsequent analysis in amplitude and time, variables that will allow evaluating the electrical activity of nerves and muscles. Nowadays in the area of biomedicine, the obtaining and conditioning of electrophysiological data of individuals is of great importance. Firstly, the adequate processing and visualization of the expected signal pattern can provide the specialist with optimal reading of data by providing correct diagnoses, and second, the favorable incidence over time through optimal medical treatment to the patient that improves their conditions of life. On the other hand, due to the post-conflict in our country, there are individuals who have marks caused by violence that involve physical treatments, some of them, rehabilitations that compromise the evaluation over time of the muscular response of some parts of the body. This is the social justification of the investigation, whose initial phase includes the conditioning under electronic components of the electromyographic signal for its subsequent analysis over time. In order to comply with the proposed phase, a sequential methodology has been carried out which includes the review of the state of the art related to the design, implementation and analysis of circuits, to condition the basic pattern electromyographic signal by means of non-invasive methods, followed by the simulation and visualization of the signal in free software, then the identification of changes in the amplitude and frequency and disturbances in the signal, which can be mitigated by the design of filters. The initial results indicate that the type of sensor, the contact with the skin and the movement of the patient cause the disturbance of the result of the signal conditioned by electronic methods. Likewise, the correct digital reading of the signal pattern in the appropriate format would provide, in later phases, the storage and remote access of different muscle responses of patients over time to consult the specialist remotely, decreasing patient transfer costs when performing followups On-line.