Modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.

This paper discusses modeling and automatic feedback control of (postural and rest) tremor for adaptive-control-methodology-based estimation of deep brain stimulation (DBS) parameters. The simplest linear oscillator-based tremor model, between stimulation amplitude and tremor, is investigated by uti...

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Autores principales:	Muhammad Rehan, Keum-Shik Hong
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/78af699fb1884d14ade22757940e45c4
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spelling	oai:doaj.org-article:78af699fb1884d14ade22757940e45c42021-11-18T07:47:55ZModeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.1932-620310.1371/journal.pone.0062888https://doaj.org/article/78af699fb1884d14ade22757940e45c42013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23638163/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203This paper discusses modeling and automatic feedback control of (postural and rest) tremor for adaptive-control-methodology-based estimation of deep brain stimulation (DBS) parameters. The simplest linear oscillator-based tremor model, between stimulation amplitude and tremor, is investigated by utilizing input-output knowledge. Further, a nonlinear generalization of the oscillator-based tremor model, useful for derivation of a control strategy involving incorporation of parametric-bound knowledge, is provided. Using the Lyapunov method, a robust adaptive output feedback control law, based on measurement of the tremor signal from the fingers of a patient, is formulated to estimate the stimulation amplitude required to control the tremor. By means of the proposed control strategy, an algorithm is developed for estimation of DBS parameters such as amplitude, frequency and pulse width, which provides a framework for development of an automatic clinical device for control of motor symptoms. The DBS parameter estimation results for the proposed control scheme are verified through numerical simulations.Muhammad RehanKeum-Shik HongPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 4, p e62888 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Muhammad Rehan Keum-Shik Hong Modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.
description	This paper discusses modeling and automatic feedback control of (postural and rest) tremor for adaptive-control-methodology-based estimation of deep brain stimulation (DBS) parameters. The simplest linear oscillator-based tremor model, between stimulation amplitude and tremor, is investigated by utilizing input-output knowledge. Further, a nonlinear generalization of the oscillator-based tremor model, useful for derivation of a control strategy involving incorporation of parametric-bound knowledge, is provided. Using the Lyapunov method, a robust adaptive output feedback control law, based on measurement of the tremor signal from the fingers of a patient, is formulated to estimate the stimulation amplitude required to control the tremor. By means of the proposed control strategy, an algorithm is developed for estimation of DBS parameters such as amplitude, frequency and pulse width, which provides a framework for development of an automatic clinical device for control of motor symptoms. The DBS parameter estimation results for the proposed control scheme are verified through numerical simulations.
format	article
author	Muhammad Rehan Keum-Shik Hong
author_facet	Muhammad Rehan Keum-Shik Hong
author_sort	Muhammad Rehan
title	Modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.
title_short	Modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.
title_full	Modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.
title_fullStr	Modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.
title_full_unstemmed	Modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.
title_sort	modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/78af699fb1884d14ade22757940e45c4
work_keys_str_mv	AT muhammadrehan modelingandautomaticfeedbackcontroloftremoradaptiveestimationofdeepbrainstimulation AT keumshikhong modelingandautomaticfeedbackcontroloftremoradaptiveestimationofdeepbrainstimulation
_version_	1718422919207452672

Modeling and automatic feedback control of tremor: adaptive estimation of deep brain stimulation.

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