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Closed-loop deep brain stimulation based on a stream-clustering system

dc.contributor.authorCámara Núñez, Carmen
dc.contributor.authorWarwick, Kevin
dc.contributor.authorBruña Fernández, Ricardo
dc.contributor.authorAziz, Tipu
dc.contributor.authorPereda, Ernesto
dc.date.accessioned2024-02-08T09:33:22Z
dc.date.available2024-02-08T09:33:22Z
dc.date.issued2019
dc.description.abstractIdiopathic Parkinsons disease (PD) is currently the second most important neurodegenerative disease in incidence. Deep brain stimulation (DBS) constitutes a successful and necessary therapy; however, the continuous stimulation it provides can be associated with multiple side effects. DBS uses an implanted pulse generator that delivers, through a set of electrodes, electrical stimulation to the target area, normally the Sub Thalamic Nucleus. Recently, Closed-loop DBS has emerged as a promising new strategy, where the device stimulates only when necessary, thereby reducing any adverse effects. Here, we present a Closed-loop DBS system for PD, which is able to recognize, with 100% accuracy, when the patient is going to enter into the tremor phase, thus allowing the device to stimulate only in such cases. The expert system has been designed and implemented within the data stream mining paradigm, suitable for our scenario since it can cope with continuous data of a theoretical infinite length and with a certain variability, which uses the synchronization among the neural population within the Sub Thalamic Nucleus as the continuous data stream input to the system.
dc.description.departmentDepto. de Psicología Experimental, Procesos Cognitivos y Logopedia
dc.description.departmentDepto. de Medicina
dc.description.facultyFac. de Psicología
dc.description.facultyFac. de Medicina
dc.description.refereedTRUE
dc.description.statuspub
dc.identifier.citationPlease cite this article as: C. Camara, K. Warwick, R. Bruna, ˜ T. Aziz, E. Pereda, Closed-loop deep brain stimulation based on a stream-clustering system, Expert Systems With Applications (2019), doi: https://doi.org/10.1016/j.eswa.2019.02.024
dc.identifier.doi10.1016/j.eswa.2019.02.024
dc.identifier.essn1873-6793
dc.identifier.issn0957-4174
dc.identifier.officialurlhttps://doi.org/10.1016/j.eswa.2019.02.024
dc.identifier.urihttps://hdl.handle.net/20.500.14352/100250
dc.journal.titleExpert Systems With Applications
dc.language.isoeng
dc.page.final199
dc.page.initial187
dc.publisherElsevier
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.cdu612.8
dc.subject.keywordClustering
dc.subject.keywordData stream mining (DSM)
dc.subject.keywordExpert system
dc.subject.keywordDeep brain stimulation (DBS)
dc.subject.keywordParkinson’s disease (PD)
dc.subject.keywordNeural engineering
dc.subject.ucmNeurociencias (Medicina)
dc.subject.unesco2490 Neurociencias
dc.subject.unesco3207.11 Neuropatología
dc.titleClosed-loop deep brain stimulation based on a stream-clustering system
dc.typejournal article
dc.type.hasVersionAM
dc.volume.number126
dspace.entity.typePublication
relation.isAuthorOfPublication47811cb6-7768-4f47-b356-c91b49efc7a2
relation.isAuthorOfPublicationef335315-bb52-49b1-8703-63c7caae45f8
relation.isAuthorOfPublication.latestForDiscoveryef335315-bb52-49b1-8703-63c7caae45f8

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