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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/5888
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dc.contributor.advisorBruin, H. deen_US
dc.contributor.authorStashuk, William Danielen_US
dc.date.accessioned2014-06-18T16:33:22Z-
dc.date.available2014-06-18T16:33:22Z-
dc.date.created2010-05-06en_US
dc.date.issued1985-07en_US
dc.identifier.otheropendissertations/1232en_US
dc.identifier.other2467en_US
dc.identifier.other1301163en_US
dc.identifier.urihttp://hdl.handle.net/11375/5888-
dc.description.abstract<p>A procedure for the recording and storing or EMG signals for the automatic extraction of individual motor unit rate coding and morphological information was developed. The extraction of the fate coding information is performed by the analysis of individual motor unit action potential trains (MUAPT'S), obtained by decomposing the composite EMG signal, recorded from a selective surface of a needle electrode. The morphological information is derived from the analysis of macro motor unit potentials (MUP'S). The macro MUP'S are the result of ensemble averaging the cannula recorded signal, using the individual MUAPT'S as sources of synchronizing triggers for the averaging process. A standard single fibre or macro EMG needle electrode can be used.</p> <p>Signals recorded during isometric, constant or slow force varying contractions, up to 50% of the maximum voluntary contraction level, can be successfully analyzed. The number of motor units simultaneously studied, usually ranges from 3 to 5. The processing of the data, for each second of muscle contraction, can be performed by a PDP 11/34 computer in approximately one minute, with 95% accurate, rate coding information obtained. This speed and accuracy may increase the clinical use of rate coding information. The procedure also provides individual motor unit rate coding and morphological information simultaneously, allowing correlation of motor unit sizes with firing rates and identification of macro MUP'S for high threshold motor units.</p>en_US
dc.subjectElectrical and Electronicsen_US
dc.subjectElectrical and Electronicsen_US
dc.titleAutomatic Quantitative Analysis of Needle Recorded EMG Signalsen_US
dc.typethesisen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
Appears in Collections:Open Access Dissertations and Theses

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