Ray, Andreas M.Lopez-Larraz, EduardoFigueiredo, Thiago C.Birbaumer, NielsRamos-Murguialday, Ander2024-07-242024-07-242017-09-13Ray , A M , Lopez-Larraz , E , Figueiredo , T C , Birbaumer , N & Ramos-Murguialday , A 2017 , Movement-related brain oscillations vary with lesion location in severely paralyzed chronic stroke patients . in 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society : Smarter Technology for a Healthier World, EMBC 2017 - Proceedings . , 8037160 , Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS , Institute of Electrical and Electronics Engineers Inc. , pp. 1664-1667 , 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 , Jeju Island , Korea, Republic of , 11/07/17 . https://doi.org/10.1109/EMBC.2017.8037160conference97815090280921557-170Xhttps://hdl.handle.net/11556/1846Publisher Copyright: © 2017 IEEE.In the past few years, innovative upper-limb rehabilitation methods have been proposed for chronic stroke patients. These methods aim at functional motor rehabilitation using Brain-machine interfaces to constitute an alternate pathway from the brain to the muscles. Even in patients with absence of residual finger movements, recovery could be achieved. The extent to which these interventions are affected by individual lesion topology is yet to be understood. In this study EEG was measured in 30 chronic stroke patients during movement attempts of the paretic arm. We show that the magnitude of the event-related desynchronization was smaller in patients presenting lesions with involvement of the motor cortex. This could have important implications on the design of new rehabilitation schemes for these patients, which might benefit from carefully tailored interventions.4enginfo:eu-repo/semantics/restrictedAccessMovement-related brain oscillations vary with lesion location in severely paralyzed chronic stroke patientsconference output10.1109/EMBC.2017.8037160Signal ProcessingBiomedical EngineeringComputer Vision and Pattern RecognitionHealth InformaticsSDG 3 - Good Health and Well-beinghttp://www.scopus.com/inward/record.url?scp=85032221101&partnerID=8YFLogxK