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dc.contributor.advisorPatton, James L.en_US
dc.contributor.authorLancaster, Joseph R.en_US
dc.date.accessioned2016-02-17T17:32:20Z
dc.date.available2018-02-18T10:30:10Z
dc.date.created2015-12en_US
dc.date.issued2016-02-17
dc.date.submitted2015-12en_US
dc.identifier.urihttp://hdl.handle.net/10027/20239
dc.description.abstractThe identification of motor impairments in human neuropathologies is daunting and often restricted to using isometric tests, identifying a single impairment, or investigating a single joint. Here, we present and evaluate our preliminary work in employing a novel, model-based framework for identification and quantification of multiple simultaneous impairments from multijoint upper extremity movement data in the form of a kinematic distribution. We use multiple synthetic models of idealized motor impairments to understand if and how it might be possible to differentiate between them based on the changes they induce in these movement distributions. We simulate these models in a variety of combinations and severities and use standard regression techniques to attempt to recover the “pathoparameters” defining them. We show that, given a well-chosen set of example distributions in a lookup table, one has the ability to identify pathoparameters and differentiate between impairment types without confusion.en_US
dc.language.isoenen_US
dc.rightsen_US
dc.rightsCopyright 2015 Joseph R. Lancasteren_US
dc.subjectmotor impairmenten_US
dc.subjectstrokeen_US
dc.subjectsystem identificationen_US
dc.subjectpathoparameteren_US
dc.subjectcomputational modelingen_US
dc.titleIdentification of Motor Impairments Using Movement Distributionsen_US
thesis.degree.departmentBioengineeringen_US
thesis.degree.disciplineBioengineeringen_US
thesis.degree.grantorUniversity of Illinois at Chicagoen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMS, Master of Scienceen_US
dc.type.genrethesisen_US
dc.contributor.committeeMemberBerniker, Maxen_US
dc.contributor.committeeMemberHuang, Felixen_US
dc.type.materialtexten_US


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