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Title of Journal: J Neurol

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Abbravation: Journal of Neurology

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Steinkopff-Verlag

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DOI

10.1016/0029-554x(67)90639-8

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1432-1459

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Longterm EMG recordings differentiate between par

Authors: S Breit S Spieker J B Schulz T Gasser
Publish Date: 2008/01/22
Volume: 255, Issue: 1, Pages: 103-111
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Abstract

The differential diagnosis of tremor is mainly based on clinical criteriaNevertheless these criteria are in some cases not sufficient to differentiate between different tremor forms Longterm EMG has proven to be a valid and reliable method for the quantification of pathological tremorsThe aim of the study was to develop a longterm EMGbased automated analysis procedure that separates parkinsonian tremor from essential tremor Using longterm EMG tremor was recorded in 45 consecutive patients 26 with Parkinsons disease PD and 19 with essential tremor ET Eight tremor parameters were generated automatically By stepwise backward regression a subset of these criteria was extracted to achieve an automated classification of the tremor by a mathematical model The obtained model was then tested on a new group of 13 patients in early stages of the diseaseSignificant differences between groups were found for tremor occurrence tremor asymmetry mean tremor frequency and standard deviation of phase of antagonistic muscles Due to data overlap a classification of the two tremor forms was not possible based on a single tremor parameter Using logistic regression a linear formula based on the three parameters tremor occurrence mean tremor frequency and standard deviation of phase was established and predicted the correct diagnosis in 93 of patients The validation of the model on the new group of patients in early stages of the tremor disease yielded a correct diagnosis in 100 of cases

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