File Exchange

image thumbnail

Digital Processing of Electromyographic Signals for Control

Live Script shows complex calculations of digital signal processing (DSP) perform to infer info from biological signals acquired by sensors

10 Downloads

Updated 18 Jul 2018

View License

Controlling biorobotic systems, such as prostheses, from physiological systems is possible as long as an adequate digital processing is carried out on physiological signals, which the user controls to some extent, as is the electromyographic signal, through this digital processing. The biosignal is aconditioned with filtering techniques, it is also possible to extract characteristics of the signal by means of suitable mathematical techniques such as the IAV, which allows achieving said objective and, in addition, allows the application of control methodologies such as the categorization of the magnitude of the biosignals, so that it provides a specific response to the biorobotic system.
It should be noted that the calculation of the envelope of the EMG signal is a vital process, since it is possible to set control thresholds, which allow to control electromechanical systems with greater ease and precision. Allowing in this way, make use of the electrophysiological signals of the body of living beings, to execute defined movements in a mechanical system that fulfills a function desired by the user.
This work shows that it is possible to use "unusable" biosignals, due to the amount of noise they contain when they are obtained. Once the proper processing is done, which results in optimal signals to be used in devices that are allowed to be controlled in the desired manner. In addition, this development is applicable to the daily life of an amputee, which allows enable lost functions, such as, for example, performing the movement of a robotic arm, which can accomplish specific tasks to achieve personal goals such as bringing food to the mouth or writing a letter. Submitted as part of the MATLAB Online Live Editor Challenge 2018.

Comments and Ratings (0)

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux