Home automation system for the disabled using electromyographic signals

Summary form only given, as follows. Patients in disability status have difficulty coping and control their environment, this limits their autonomy and performing everyday tasks. We present in this paper an electronic system that acquiring and using EMG superficial signal (sEMG) of two groups of muscles, masseter and flexor carpi radialis, processes and generates an encoding that is used as a set of commands for automa-te some elements inside a housing that ensure comfort and safety for the user. The developed system implements pro-cessing techniques and characterization based on temporal approach, FFT and Wavelets where using neural networks are recognized movement patterns. The different charac-teristics of the EMG signal of the same muscle and movement in different subjects, shows that the developed system is adaptable to each user through a phase of training un-der a protocol of movements. This work not only focuses on the development of a biomedical device for the descri-bed patients, but also it improves their quality of life, pro-motes social inclusion and helps to solve some self-esteem issues that are presented in these people, and gives them the possibility of being independent in their daily lives.