José M. Azorín

TL;DR: It is concluded that lower-body powered exoskeletons with automated gait intention detection based on BMIs open new possibilities in the assistance and rehabilitation fields, although the current performance, clinical benefits and several key challenging issues indicate that additional research and development is required to deploy these systems in the clinic and at home.

TL;DR: A non-invasive spontaneous Brain–Machine Interface has been designed to control a robot arm through the mental activity of the users through the classification of four mental tasks in order to manage the movements of the robot.

TL;DR: A brain-computer interface based on electroencephalography (EEG) that has been developed to assist disabled people using the evoked potentials paradigm, which allows severe disabled people to interact with other people using basic commands related to emotions and needs.

TL;DR: A Brain Computer Interface (BCI) based on electroencephalography (EEG) that allows control of a robot arm will enable people with severe disabilities to control a robot arms to assist them in a variety of tasks in their daily lives.

TL;DR: A new portable and wireless interface based on electrooculography (EOG) aimed at people with severe motor disorders that allows the movement of the eyes measuring the potential between the cornea and the retina to be detected.