A rule-based expert system for real-time feedback-control in deep brain stimulation

Programming in deep brain stimulation (DBS) is often a labour-intensive process. Although automatic closed-loop stimulation has recently been receiving considerable attention, it is still far from clinical settings. Testing in-loop stimulation in a clinical setting is extremely challenging due to ma...

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Autores principales:	Bremm Rene Peter, Koch Klaus Peter, Krüger Rejko, Hertel Frank, Gonçalves Jorge
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2020
Materias:	movement disorders essential tremor wearable motion sensors rule-based expert systems deep brain stimulation Medicine R
Acceso en línea:	https://doaj.org/article/0bf074921daa449384059f7be6185c68
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id	oai:doaj.org-article:0bf074921daa449384059f7be6185c68
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spelling	oai:doaj.org-article:0bf074921daa449384059f7be6185c682021-12-05T14:10:42ZA rule-based expert system for real-time feedback-control in deep brain stimulation2364-550410.1515/cdbme-2020-3027https://doaj.org/article/0bf074921daa449384059f7be6185c682020-09-01T00:00:00Zhttps://doi.org/10.1515/cdbme-2020-3027https://doaj.org/toc/2364-5504Programming in deep brain stimulation (DBS) is often a labour-intensive process. Although automatic closed-loop stimulation has recently been receiving considerable attention, it is still far from clinical settings. Testing in-loop stimulation in a clinical setting is extremely challenging due to manual programming and the lack of synchronisation between stimulation and monitoring devices. In this work, we present a simple rulebased expert system to test feedback-controlled DBS in a clinical setting. The new application operates in closed-loop with the physician as acting person and real-time feedback from an accelerometer. Patients with movement disorders such as in essential tremor announce an individually acceptable level of tremor as a boundary condition for control. As a proof-of-concept, the expert system provides continuous recommendations of stimulation parameters and guides the physician to increase or decrease DBS amplitude by capturing tremor acceleration power on the patients’ forearms. The introduced application considers the technical and practical aspects in a clinical setting. Data obtained from test subjects provide insight into tremor dynamics. We demonstrate the clinical applicability of the rule-based control system for future research focusing on tremor dynamics and inloop stimulation. Finally, a telemetry streaming system could provide the interface for the application of automatic tremor control without the physician as acting person.Bremm Rene PeterKoch Klaus PeterKrüger RejkoHertel FrankGonçalves JorgeDe Gruyterarticlemovement disordersessential tremorwearable motion sensorsrule-based expert systemsdeep brain stimulationMedicineRENCurrent Directions in Biomedical Engineering, Vol 6, Iss 3, Pp 103-106 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	movement disorders essential tremor wearable motion sensors rule-based expert systems deep brain stimulation Medicine R
spellingShingle	movement disorders essential tremor wearable motion sensors rule-based expert systems deep brain stimulation Medicine R Bremm Rene Peter Koch Klaus Peter Krüger Rejko Hertel Frank Gonçalves Jorge A rule-based expert system for real-time feedback-control in deep brain stimulation
description	Programming in deep brain stimulation (DBS) is often a labour-intensive process. Although automatic closed-loop stimulation has recently been receiving considerable attention, it is still far from clinical settings. Testing in-loop stimulation in a clinical setting is extremely challenging due to manual programming and the lack of synchronisation between stimulation and monitoring devices. In this work, we present a simple rulebased expert system to test feedback-controlled DBS in a clinical setting. The new application operates in closed-loop with the physician as acting person and real-time feedback from an accelerometer. Patients with movement disorders such as in essential tremor announce an individually acceptable level of tremor as a boundary condition for control. As a proof-of-concept, the expert system provides continuous recommendations of stimulation parameters and guides the physician to increase or decrease DBS amplitude by capturing tremor acceleration power on the patients’ forearms. The introduced application considers the technical and practical aspects in a clinical setting. Data obtained from test subjects provide insight into tremor dynamics. We demonstrate the clinical applicability of the rule-based control system for future research focusing on tremor dynamics and inloop stimulation. Finally, a telemetry streaming system could provide the interface for the application of automatic tremor control without the physician as acting person.
format	article
author	Bremm Rene Peter Koch Klaus Peter Krüger Rejko Hertel Frank Gonçalves Jorge
author_facet	Bremm Rene Peter Koch Klaus Peter Krüger Rejko Hertel Frank Gonçalves Jorge
author_sort	Bremm Rene Peter
title	A rule-based expert system for real-time feedback-control in deep brain stimulation
title_short	A rule-based expert system for real-time feedback-control in deep brain stimulation
title_full	A rule-based expert system for real-time feedback-control in deep brain stimulation
title_fullStr	A rule-based expert system for real-time feedback-control in deep brain stimulation
title_full_unstemmed	A rule-based expert system for real-time feedback-control in deep brain stimulation
title_sort	rule-based expert system for real-time feedback-control in deep brain stimulation
publisher	De Gruyter
publishDate	2020
url	https://doaj.org/article/0bf074921daa449384059f7be6185c68
work_keys_str_mv	AT bremmrenepeter arulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT kochklauspeter arulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT krugerrejko arulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT hertelfrank arulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT goncalvesjorge arulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT bremmrenepeter rulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT kochklauspeter rulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT krugerrejko rulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT hertelfrank rulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation AT goncalvesjorge rulebasedexpertsystemforrealtimefeedbackcontrolindeepbrainstimulation
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A rule-based expert system for real-time feedback-control in deep brain stimulation

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