MovDisordV3, PubMed, Corpus, bibRecord, 001E70

Clinically deployable Kinesia technology for automated tremor assessment.

Identifieur interne : 001E70 ( PubMed/Corpus ); précédent : 001E69; suivant : 001E71

Clinically deployable Kinesia technology for automated tremor assessment.

Auteurs : Joseph P. Giuffrida ; David E. Riley ; Brian N. Maddux ; Dustin A. Heldman

Source :

Movement disorders : official journal of the Movement Disorder Society [ 1531-8257 ] ; 2009.

RBID : pubmed:19133661

English descriptors

KwdEn :
- Algorithms, Automatic Data Processing (methods), Humans, Kinesics, Parkinson Disease (complications), Severity of Illness Index, Tremor (diagnosis), Tremor (etiology).
MESH :
- complications : Parkinson Disease.
- diagnosis : Tremor.
- etiology : Tremor.
- methods : Automatic Data Processing.
- Algorithms, Humans, Kinesics, Severity of Illness Index.

Abstract

The objective was to design, build, and assess Kinesia, a wireless system for automated assessment of Parkinson's disease (PD) tremor. The current standard in evaluating PD is the Unified Parkinson's Disease Rating Scale (UPDRS), a qualitative ranking system typically completed during an office visit. Kinesia integrates accelerometers and gyroscopes in a compact patient-worn unit to capture kinematic movement disorder features. Objectively quantifying PD manifestations with increased time resolution should aid in evaluating efficacy of treatment protocols and improve patient management. In this study, PD subjects performed the tremor subset of the UPDRS motor section while wearing Kinesia. Quantitative kinematic features were processed and highly correlated to clinician scores for rest tremor (r(2) = 0.89), postural tremor (r(2) = 0.90), and kinetic tremor (r(2) = 0.69). The quantitative features were used to develop a mathematical model that predicted tremor severity scores for new data with low errors. Finally, PD subjects indicated high clinical acceptance.

DOI: 10.1002/mds.22445
PubMed: 19133661

Links to Exploration step

pubmed:19133661

Le document en format XML

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<author><name sortKey="Giuffrida, Joseph P" sort="Giuffrida, Joseph P" uniqKey="Giuffrida J" first="Joseph P" last="Giuffrida">Joseph P. Giuffrida</name>
<affiliation><nlm:affiliation>Division of Movement Disorders, Cleveland Medical Devices Inc., Cleveland, Ohio 44103, USA. jgiuffrida@clevemed.com</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Riley, David E" sort="Riley, David E" uniqKey="Riley D" first="David E" last="Riley">David E. Riley</name>
</author>
<author><name sortKey="Maddux, Brian N" sort="Maddux, Brian N" uniqKey="Maddux B" first="Brian N" last="Maddux">Brian N. Maddux</name>
</author>
<author><name sortKey="Heldman, Dustin A" sort="Heldman, Dustin A" uniqKey="Heldman D" first="Dustin A" last="Heldman">Dustin A. Heldman</name>
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<author><name sortKey="Heldman, Dustin A" sort="Heldman, Dustin A" uniqKey="Heldman D" first="Dustin A" last="Heldman">Dustin A. Heldman</name>
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<series><title level="j">Movement disorders : official journal of the Movement Disorder Society</title>
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<term>Parkinson Disease (complications)</term>
<term>Severity of Illness Index</term>
<term>Tremor (diagnosis)</term>
<term>Tremor (etiology)</term>
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<keywords scheme="MESH" qualifier="complications" xml:lang="en"><term>Parkinson Disease</term>
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<keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Tremor</term>
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<front><div type="abstract" xml:lang="en">The objective was to design, build, and assess Kinesia, a wireless system for automated assessment of Parkinson's disease (PD) tremor. The current standard in evaluating PD is the Unified Parkinson's Disease Rating Scale (UPDRS), a qualitative ranking system typically completed during an office visit. Kinesia integrates accelerometers and gyroscopes in a compact patient-worn unit to capture kinematic movement disorder features. Objectively quantifying PD manifestations with increased time resolution should aid in evaluating efficacy of treatment protocols and improve patient management. In this study, PD subjects performed the tremor subset of the UPDRS motor section while wearing Kinesia. Quantitative kinematic features were processed and highly correlated to clinician scores for rest tremor (r(2) = 0.89), postural tremor (r(2) = 0.90), and kinetic tremor (r(2) = 0.69). The quantitative features were used to develop a mathematical model that predicted tremor severity scores for new data with low errors. Finally, PD subjects indicated high clinical acceptance.</div>
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<Title>Movement disorders : official journal of the Movement Disorder Society</Title>
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<Abstract><AbstractText>The objective was to design, build, and assess Kinesia, a wireless system for automated assessment of Parkinson's disease (PD) tremor. The current standard in evaluating PD is the Unified Parkinson's Disease Rating Scale (UPDRS), a qualitative ranking system typically completed during an office visit. Kinesia integrates accelerometers and gyroscopes in a compact patient-worn unit to capture kinematic movement disorder features. Objectively quantifying PD manifestations with increased time resolution should aid in evaluating efficacy of treatment protocols and improve patient management. In this study, PD subjects performed the tremor subset of the UPDRS motor section while wearing Kinesia. Quantitative kinematic features were processed and highly correlated to clinician scores for rest tremor (r(2) = 0.89), postural tremor (r(2) = 0.90), and kinetic tremor (r(2) = 0.69). The quantitative features were used to develop a mathematical model that predicted tremor severity scores for new data with low errors. Finally, PD subjects indicated high clinical acceptance.</AbstractText>
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	Movement Disorders (revue)
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Movement Disorders (revue)

Clinically deployable Kinesia technology for automated tremor assessment.

Clinically deployable Kinesia technology for automated tremor assessment.

Source :

English descriptors

Abstract

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki