Nota Clínica

Training cortical signals by means of a BMI-EEG system, its evolution and intervention. A case report

E. Monge-Pereira, I. Casatorres Pérez-Higueras, P. Fernández-González, J. Ibáñez-Pereda, J.I. Serrano, F. Molina-Rueda [REV NEUROL 2017;64:362-366] PMID: 28368083 DOI: https://doi.org/10.33588/rn.6408.2016443

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Volumen 64 | Number 08 | Nº of views of the article 6.279 | Nº of PDF downloads 126 | Article publication date 16/04/2017

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ABSTRACT

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 subjects motion intention was analyzed calculating the event-related desynchronization. The upper limb motor function was evaluated with the Fügl-Meyer Assessment and the participants 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 Fügl-Meyer Assessment. KeywordsBrain-machine interface Electroencephalography Physiotherapist Rehabilitation Stroke Upper limb CategoriesMareos, vértigos y acufenos Patología vascular

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Nota Clínica

Training cortical signals by means of a BMI-EEG system, its evolution and intervention. A case report

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