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dc.contributor.authorPino, Lou Joseph
dc.date.accessioned2009-01-21 21:14:47 (GMT)
dc.date.available2009-01-21 21:14:47 (GMT)
dc.date.issued2009-01-21T21:14:47Z
dc.date.submitted2008
dc.identifier.urihttp://hdl.handle.net/10012/4214
dc.description.abstractObjectives: Based on the analysis of electromyographic (EMG) data muscles are often characterized as normal or affected by a neuromuscular disease process. A clinical decision support system (CDSS) for the electrophysiological characterization of muscles by analyzing motor unit potentials (MUPs) was developed to assist physicians and researchers with the diagnosis, treatment & management of neuromuscular disorders and analyzed against criteria for use in a clinical setting. Methods: Quantitative MUP data extracted from various muscles from control subjects and patients from a number of clinics was used to compare the sensitivity, specificity, and accuracy of a number of different clinical decision support methods. The CDSS developed in this work known as AMC-PD has three components: MUP characterization using Pattern Discovery (PD), muscle characterization by taking the average of MUP characterizations and calibrated muscle characterizations. Results: The results demonstrated that AMC-PD achieved higher accuracy than conventional means and outlier analysis. Duration, thickness and number of turns were the most discriminative MUP features for characterizing the muscles studied in this work. Conclusions: AMC-PD achieved higher accuracy than conventional means and outlier analysis. Muscle characterization performed using AMC-PD can facilitate the determination of “possible”, “probable”, or “definite” levels of disease whereas the conventional means and outlier methods can only provide a dichotomous “normal” or “abnormal” decision. Therefore, AMC-PD can be directly used to support clinical decisions related to initial diagnosis as well as treatment and management over time. Decisions are based on facts and not impressions giving electromyography a more reliable role in the diagnosis, management, and treatment of neuromuscular disorders. AMC-PD based calibrated muscle characterization can help make electrophysiological examinations more accurate and objective.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectdecision supporten
dc.subjectpattern recognitionen
dc.subjectquantitative electromyographyen
dc.subjectmotor unit potentialsen
dc.titleNeuromuscular Clinical Decision Support using Motor Unit Potentials Characterized by 'Pattern Discovery'en
dc.typeDoctoral Thesisen
dc.pendingfalseen
dc.subject.programSystem Design Engineeringen
uws-etd.degree.departmentSystems Design Engineeringen
uws-etd.degreeDoctor of Philosophyen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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