Stroke lesion location influences the decoding of movement intention from EEG

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dc.contributor.authorLopez-Larraz, Eduardo
dc.contributor.authorRay, Andreas M.
dc.contributor.authorFigueiredo, Thiago C.
dc.contributor.authorBibian, Carlos
dc.contributor.authorBirbaumer, Niels
dc.contributor.authorRamos-Murguialday, Ander
dc.contributor.institutionMedical Technologies
dc.date.accessioned2024-07-24T11:53:08Z
dc.date.available2024-07-24T11:53:08Z
dc.date.issued2017-09-13
dc.descriptionPublisher Copyright: © 2017 IEEE.
dc.description.abstractRecent studies have demonstrated the efficacy of brain-machine interfaces (BMI) for motor rehabilitation after stroke, especially for those patients with severe paralysis. However, a cerebro-vascular accident can affect the brain in many different manners, and lesions in diverse areas, even from significantly different volumes, can lead to similar or equal motor deficits. The location of the insult influences the way the brain activates when moving or attempting to move a paralyzed limb. Since the essence of a rehabilitative BMI is to precisely decode motor commands from the brain, it is crucial to characterize how lesion location affects the measured signals and if and how it influences BMI performance. This paper compares the performances of an electroencephalography (EEG)-based movement intention decoder in two groups of severely paralyzed chronic stroke patients: 14 with subcortical lesions and 14 with mixed (i.e., cortical and subcortical) lesions. We show that the lesion location influences the performance of the BMI when decoding the movement attempts of the paretic arm. The obtained results underline the need for further developments for a better individualization of BMI-based rehabilitative therapies for stroke patients.en
dc.description.sponsorshipThis study was funded by the Baden-Württemberg Stiftung (GRUENS ROB-1), the Deutsche Forschungsgemeinschaft (DFG, Koselleck), the Fortüne-Program of the University of Tübingen (2422-0-0), and the Bundesministerium für Bil-dung und Forschung BMBF MOTORBIC (FKZ 13GW0053) and AMORSA (FKZ 16SV7754).
dc.description.statusPeer reviewed
dc.format.extent4
dc.identifier.citationLopez-Larraz , E , Ray , A M , Figueiredo , T C , Bibian , C , Birbaumer , N & Ramos-Murguialday , A 2017 , Stroke lesion location influences the decoding of movement intention from EEG . in 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society : Smarter Technology for a Healthier World, EMBC 2017 - Proceedings . , 8037504 , Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS , Institute of Electrical and Electronics Engineers Inc. , pp. 3065-3068 , 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.2017.8037504
dc.identifier.citationconference
dc.identifier.doi10.1109/EMBC.2017.8037504
dc.identifier.isbn9781509028092
dc.identifier.issn1557-170X
dc.identifier.urihttps://hdl.handle.net/11556/2264
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85032191848&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
dc.relation.ispartofseriesProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
dc.relation.projectIDBaden-Württemberg Stiftung
dc.relation.projectIDDeutsche Forschungsgemeinschaft, DFG
dc.relation.projectIDEberhard Karls Universität Tübingen, 2422-0-0
dc.relation.projectIDBundesministerium für Bildung, Wissenschaft, Forschung und Technologie, BMBWF, FKZ 13GW0053-FKZ 16SV7754
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsSignal Processing
dc.subject.keywordsBiomedical Engineering
dc.subject.keywordsComputer Vision and Pattern Recognition
dc.subject.keywordsHealth Informatics
dc.subject.keywordsSDG 3 - Good Health and Well-being
dc.titleStroke lesion location influences the decoding of movement intention from EEGen
dc.typeconference output
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