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Deep Brain Stimulation therapies: a control-engineering perspective
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.ORCID iD: 0000-0002-6608-250x
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2017 (English)In: Proc. American Control Conference: ACC 2017, IEEE, 2017, p. 104-109Conference paper, Published paper (Refereed)
Abstract [en]

Deep Brain Stimulation (DBS) is an established therapy for treating e.g. Parkinson's disease, essential tremor, as well as epilepsy. In DBS, chronic pulsatile electrical stimulation is administered to a certain target area of the brain through a surgically implanted lead. The stimuli parameters have to be properly tuned in order to achieve therapeutical effect that in most cases is alleviation of motor symptoms. Tuning of DBS currently is a tedious task since it is performed manually by medical personnel in a trial-and-error manner. It can be dramatically improved and expedited by means of recently developed mathematical models together with control and estimation technology. This paper presents a control engineering perspective on DBS, viewing it as a control system for minimizing the severity of the symptoms through coordinated manipulation of the stimuli parameters. The DBS model structure comprises a stimuli model, an activation model, and a symptoms model. Each of those is individualized from patient data obtained through medical imaging, electrical measurements, and objective symptom quantification. The proposed approach is illustrated by simulation and clinical data from an individualized DBS model being developed by the authors.

Place, publisher, year, edition, pages
IEEE, 2017. p. 104-109
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:uu:diva-305221DOI: 10.23919/ACC.2017.7962938ISI: 000427033300016ISBN: 978-1-5090-5992-8 (electronic)ISBN: 978-1-5090-4583-9 (print)ISBN: 978-1-5090-5994-2 OAI: oai:DiVA.org:uu-305221DiVA, id: diva2:1034753
Conference
ACC 2017, May 24–26, Seattle, WA
Available from: 2017-07-03 Created: 2016-10-13 Last updated: 2018-07-27Bibliographically approved

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Cubo, RubénMedvedev, AlexanderAndersson, Helena

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