Related Experiment Video
Updated: Jul 26, 2026
Recording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping
Published on: June 26, 2012
[Training cortical signals by means of a BMI-EEG system, its evolution and intervention. A case report]
E Monge-Pereira1, I Casatorres Perez-Higueras2, P Fernandez-Gonzalez1
1Universidad Rey Juan Carlos, 28922 Alcorcon, Espana.
Introduction:
In the last years, new technologies such as the brain-machine interfaces (BMI) have been incorporated in the rehabilitation process of subjects with stroke. These systems are able to detect motion intention, analyzing the cortical signals using different techniques such as the electroencephalography (EEG). This information could guide different interfaces such as robotic devices, electrical stimulation or virtual reality.
Case Report:
A 40 years-old man with stroke with two months from the injury participated in this study. We used a BMI based on EEG. The subject's motion intention was analyzed calculating the event-related desynchronization. The upper limb motor function was evaluated with the Fugl-Meyer Assessment and the participant's satisfaction was evaluated using the QUEST 2.0. The intervention using a physical therapist as an interface was carried out without difficulty.
Conclusions:
The BMI systems detect cortical changes in a subacute stroke subject. These changes are coherent with the evolution observed using the Fugl-Meyer Assessment.
