A virtual reality and brain computer interface system for upper limb rehabilitation of post stroke patients

• Autores: Achanccaray D., Acuña K., Carranza E., Andreu-Perez J.
• Formato: objeto de conferencia
• Fecha de Publicación: 2017
• Institución: Consejo Nacional de Ciencia Tecnología e Innovación
• Repositorio: CONCYTEC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.concytec.gob.pe:20.500.12390/504
• Enlace del recurso: https://hdl.handle.net/20.500.12390/504; https://doi.org/10.1109/FUZZ-IEEE.2017.8015726
• Nivel de acceso: acceso abierto
• Materia: Neuromuscular rehabilitation; Brain; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Interfaces (computer); Medical computing; https://purl.org/pe-repo/ocde/ford#3.04.02

This work presents a brain computer interface (BCI) framework for upper limb rehabilitation of post stroke patients, combining BCI and virtual reality (VR) technology; a VR feedback is shown to the participants to achieve a greater activation of certain brain regions involved with the performing of upper limb motor task. This system uses an adaptive neuro-fuzzy inference system (ANFIS) classifier to discriminate between a motor task and rest condition, the first one classifies between extension and rest conditions; and the second one classifies between flexion and rest conditions. In the training stage, eight healthy subjects participated in the sessions, the best accuracies are 99.3% and 88.9%, as a result of cross-validation. Meanwhile, the best accuracy in online test is 89%. The methodology here presented can be straightforwardly employed as a rehabilitation system for brain repair in individuals with neurological diseases or brain injury.