(untitled) (INGE@UAN - TENDENCIAS EN LA INGENIERÍA, 2013)
Traditionally, human-machine interfaces have been a widely studied research topic in the rehabilitation field. In order to empower the physical rehabilitation processes of motor disabled people, there are growing efforts within the scientific community aimed at developing new robotic devices such as exoskeletons. Myoelectric control is an advanced technique concerning with detection, processing, classification and application of electromyography signals to control external rehabilitation systems and devices. In physical therapies using robotic systems it is fundamental an effective identification of the human motion to command these systems. In literature, surface EMG signals have been widely used, taking into account that they can reflect the movement intention. This work provides a revision of the computational techniques and methods that have been used in literature, based on features extraction and pattern recognition techniques aimed at myoelectric control of robotic exoskeletons. It is considered researches that have used these methods to control robotic devices, and it is presented future trends in this research field.