Evaluation of an Electromyography (EMG)-driven Upper Extremity Model for Neurorehabilitation Applications

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dc.contributor.advisorFregly, Benjamin Jen_US
dc.creatorFord, Johnathan Williamen_US
dc.date.accessioned2022-09-26T15:26:27Zen_US
dc.date.available2022-09-26T15:26:27Zen_US
dc.date.created2022-05en_US
dc.date.issued2022-04-21en_US
dc.date.submittedMay 2022en_US
dc.date.updated2022-09-26T15:26:27Zen_US
dc.description.abstractUpper extremity EMG-driven models have the potential to inform the design of rehabilitation treatments. However, limitations exist when not all muscles have electromyographic (EMG) data available. Therefore, a synergy-based optimization approach was implemented to predict joint moments reliably despite missing EMG signals. Improvements are still needed, but progress is being made towards reliable prediction.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationFord, Johnathan William. "Evaluation of an Electromyography (EMG)-driven Upper Extremity Model for Neurorehabilitation Applications." (2022) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/113362">https://hdl.handle.net/1911/113362</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/113362en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectEMGen_US
dc.subjectelectromyographyen_US
dc.subjectsynergyen_US
dc.subjectupper extremityen_US
dc.titleEvaluation of an Electromyography (EMG)-driven Upper Extremity Model for Neurorehabilitation Applicationsen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentMechanical Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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