New actigraph for long-term tremor recording.
Identifieur interne : 002C76 ( PubMed/Curation ); précédent : 002C75; suivant : 002C77New actigraph for long-term tremor recording.
Auteurs : Eus J W. Van Someren [Pays-Bas] ; Myrthe D. Pticek ; Johannes D. Speelman ; Peter R. Schuurman ; Rianne Esselink ; Dick F. SwaabSource :
- Movement disorders : official journal of the Movement Disorder Society [ 0885-3185 ] ; 2006.
English descriptors
- KwdEn :
- MESH :
- methods : Electrophysiology, Environmental Monitoring.
- physiopathology : Parkinson Disease, Tremor.
- Aged, Algorithms, Female, Hand, Humans, Male, Middle Aged, Reference Values, Reproducibility of Results.
Abstract
A new method of movement analysis is validated, allowing an actigraph to discriminate tremor from other movements and store duration and intensity measures of both movement types. For algorithm optimization, wrist acceleration was recorded in nine controls and nine Parkinson's disease patients, while simultaneously rating their observed tremor minute by minute on item 20 of the Unified Parkinson's Disease Rating Scale. An optimization procedure to minimize false positives in controls while maximizing tremor detection in patients resulted in false positive tremor classification in 2.4% +/- 2.5% of the movement time of control subjects (range, 0%-7%), while providing tremor classification in 82.1% +/- 15.4% of the movement time in patients (range, 55%-100%), correlating r = 0.93 with their averaged observed tremor score. A second, generalizability study showed that application of the optimized algorithm resulted in accurate classification of 71% +/- 14% of the observed tremor time (range, 46%-90%) in another 9 patients and in a false positive classification in only 0.5% +/- 0.8% of the time in another 10 controls (range, 0%-2.4%). The commercial availability of this actigraph now for the first time makes it possible to investigate tremor fluctuations over several weeks. An example is given of how long-term monitoring can be of use in evaluation of symptom management.
DOI: 10.1002/mds.20900
PubMed: 16639727
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<front><div type="abstract" xml:lang="en">A new method of movement analysis is validated, allowing an actigraph to discriminate tremor from other movements and store duration and intensity measures of both movement types. For algorithm optimization, wrist acceleration was recorded in nine controls and nine Parkinson's disease patients, while simultaneously rating their observed tremor minute by minute on item 20 of the Unified Parkinson's Disease Rating Scale. An optimization procedure to minimize false positives in controls while maximizing tremor detection in patients resulted in false positive tremor classification in 2.4% +/- 2.5% of the movement time of control subjects (range, 0%-7%), while providing tremor classification in 82.1% +/- 15.4% of the movement time in patients (range, 55%-100%), correlating r = 0.93 with their averaged observed tremor score. A second, generalizability study showed that application of the optimized algorithm resulted in accurate classification of 71% +/- 14% of the observed tremor time (range, 46%-90%) in another 9 patients and in a false positive classification in only 0.5% +/- 0.8% of the time in another 10 controls (range, 0%-2.4%). The commercial availability of this actigraph now for the first time makes it possible to investigate tremor fluctuations over several weeks. An example is given of how long-term monitoring can be of use in evaluation of symptom management.</div>
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<Abstract><AbstractText>A new method of movement analysis is validated, allowing an actigraph to discriminate tremor from other movements and store duration and intensity measures of both movement types. For algorithm optimization, wrist acceleration was recorded in nine controls and nine Parkinson's disease patients, while simultaneously rating their observed tremor minute by minute on item 20 of the Unified Parkinson's Disease Rating Scale. An optimization procedure to minimize false positives in controls while maximizing tremor detection in patients resulted in false positive tremor classification in 2.4% +/- 2.5% of the movement time of control subjects (range, 0%-7%), while providing tremor classification in 82.1% +/- 15.4% of the movement time in patients (range, 55%-100%), correlating r = 0.93 with their averaged observed tremor score. A second, generalizability study showed that application of the optimized algorithm resulted in accurate classification of 71% +/- 14% of the observed tremor time (range, 46%-90%) in another 9 patients and in a false positive classification in only 0.5% +/- 0.8% of the time in another 10 controls (range, 0%-2.4%). The commercial availability of this actigraph now for the first time makes it possible to investigate tremor fluctuations over several weeks. An example is given of how long-term monitoring can be of use in evaluation of symptom management.</AbstractText>
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