{"id":{"repo_id":"umkc","oai_identifier":"oai:mospace.umsystem.edu:10355/60574"},"canonical_url":"https://search.dev.ndltd.org/etd/umkc/oai:mospace.umsystem.edu:10355/60574","repository":{"repo_id":"umkc","name":"University of Missouri - Kansas City","base_url":"https://mospace.umsystem.edu/oai/request"},"display":{"title":"Musculoskeletal Modeling of The Human Elbow Joint","abstract":"Comprehensive knowledge of the in vivo loading of elbow structures is essential in understanding the biomechanical causes associated with elbow diseases and injuries, and to find appropriate treatment. Currently, in vivo measurements of ligament, and muscle forces, and cartilage contact pressures during elbow activities is not possible. Therefore, computational models needs to be employed for prediction. A dynamic computational model in which muscle, ligament and articular surface contact forces are predicted concurrently would be the ideal tool for patient specific pre-operative planning, computer aided surgery and rehabilitation. Computational models of the elbow have been developed to study joint behavior, but all of these models have limited applicability because the joint structure was modeled as an idealized joint (e.g. hinge joint) rather than a true anatomical joint. Three dimensional studies of elbow passive motion showed that the elbow does not function as a simple hinge joint. An accurate elbow model should reflect the intrinsic laxity of the elbow especially for clinical applications. Presented here are methods for developing an anatomically based computational model of the human elbow joint that replicates the mechanical behavior of the joint and is capable of concurrent prediction of articular contact, ligament, and muscle forces under dynamic conditions. The model performance was evaluated in both a cadaveric study and a living human subject experiment. The validated models were then used to investigate the effects of medial and lateral collateral ligament deficiency on elbow joint kinematics, ligament loads, and articular contact pressure distribution.","abstract_html":"Comprehensive knowledge of the in vivo loading of elbow structures is essential in understanding the biomechanical causes associated with elbow diseases and injuries, and to find appropriate treatment. Currently, in vivo measurements of ligament, and muscle forces, and cartilage contact pressures during elbow activities is not possible. Therefore, computational models needs to be employed for prediction. A dynamic computational model in which muscle, ligament and articular surface contact forces are predicted concurrently would be the ideal tool for patient specific pre-operative planning, computer aided surgery and rehabilitation. Computational models of the elbow have been developed to study joint behavior, but all of these models have limited applicability because the joint structure was modeled as an idealized joint (e.g. hinge joint) rather than a true anatomical joint. Three dimensional studies of elbow passive motion showed that the elbow does not function as a simple hinge joint. An accurate elbow model should reflect the intrinsic laxity of the elbow especially for clinical applications. Presented here are methods for developing an anatomically based computational model of the human elbow joint that replicates the mechanical behavior of the joint and is capable of concurrent prediction of articular contact, ligament, and muscle forces under dynamic conditions. The model performance was evaluated in both a cadaveric study and a living human subject experiment. The validated models were then used to investigate the effects of medial and lateral collateral ligament deficiency on elbow joint kinematics, ligament loads, and articular contact pressure distribution.","abstract_has_math":false,"creators":["Rahman, Munsur"],"institution":"University of Missouri--Kansas City","degree_name":"Ph.D.","degree_level":"Doctoral","degree_discipline":"Engineering (UMKC)","degree_department":null,"school":null,"contributors":[],"advisors":["Stylianou, Antonis P.","Bani-Yaghoub, Majid"],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017","date_published":"2017","updated_at":"2026-07-24T05:19:40Z","subjects":[],"languages":["en_US"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10355/60574","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Stylianou, Antonis P.","Bani-Yaghoub, Majid"]},{"key":"dc:creator","label":"Author","values":["Rahman, Munsur"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-06-05T13:51:03Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-06-05T13:51:03Z"]},{"key":"dc:date.issued","label":"Date","values":["2017"]},{"key":"dc:publisher","label":"Institution","values":["University of Missouri--Kansas City"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering (UMKC)","Mathematics (UMKC)"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri-Kansas City"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10355/60574"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Title from PDF of title page viewed June 8, 2017","Dissertation advisor: Antonis P. 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Computational models of the elbow have been developed to study joint behavior, but all of these models have limited applicability because the joint structure was modeled as an idealized joint (e.g. hinge joint) rather than a true anatomical joint. Three dimensional studies of elbow passive motion showed that the elbow does not function as a simple hinge joint. An accurate elbow model should reflect the intrinsic laxity of the elbow especially for clinical applications. Presented here are methods for developing an anatomically based computational model of the human elbow joint that replicates the mechanical behavior of the joint and is capable of concurrent prediction of articular contact, ligament, and muscle forces under dynamic conditions. The model performance was evaluated in both a cadaveric study and a living human subject experiment. The validated models were then used to investigate the effects of medial and lateral collateral ligament deficiency on elbow joint kinematics, ligament loads, and articular contact pressure distribution."]},{"key":"dc:title","label":"Title","values":["Musculoskeletal Modeling of The Human Elbow Joint"]}]}],"canonical_facts":{"dc:contributor.advisor":["Stylianou, Antonis P.","Bani-Yaghoub, Majid"],"dc:creator":["Rahman, Munsur"],"dc:date.accessioned":["2017-06-05T13:51:03Z"],"dc:date.available":["2017-06-05T13:51:03Z"],"dc:date.issued":["2017"],"dc:description":["Title from PDF of title page viewed June 8, 2017","Dissertation advisor: Antonis P. Stylianou and Majid Bani-Yaghoub","Vita","Includes bibliographical references (pages 130-139)","Thesis (Ph.D.)--School of Computing and Engineering and Department of Mathematics and Statistics. University of Missouri--Kansas City, 2017"],"dc:description.abstract":["Comprehensive knowledge of the in vivo loading of elbow structures is essential in understanding the biomechanical causes associated with elbow diseases and injuries, and to find appropriate treatment. Currently, in vivo measurements of ligament, and muscle forces, and cartilage contact pressures during elbow activities is not possible. Therefore, computational models needs to be employed for prediction. A dynamic computational model in which muscle, ligament and articular surface contact forces are predicted concurrently would be the ideal tool for patient specific pre-operative planning, computer aided surgery and rehabilitation. Computational models of the elbow have been developed to study joint behavior, but all of these models have limited applicability because the joint structure was modeled as an idealized joint (e.g. hinge joint) rather than a true anatomical joint. Three dimensional studies of elbow passive motion showed that the elbow does not function as a simple hinge joint. An accurate elbow model should reflect the intrinsic laxity of the elbow especially for clinical applications. Presented here are methods for developing an anatomically based computational model of the human elbow joint that replicates the mechanical behavior of the joint and is capable of concurrent prediction of articular contact, ligament, and muscle forces under dynamic conditions. The model performance was evaluated in both a cadaveric study and a living human subject experiment. The validated models were then used to investigate the effects of medial and lateral collateral ligament deficiency on elbow joint kinematics, ligament loads, and articular contact pressure distribution."],"dc:identifier.uri":["https://hdl.handle.net/10355/60574"],"dc:language.iso":["en_US"],"dc:publisher":["University of Missouri--Kansas City"],"dc:title":["Musculoskeletal Modeling of The Human Elbow Joint"],"dc:type":["Thesis"],"thesis:degree_discipline":["Engineering (UMKC)","Mathematics (UMKC)"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Missouri-Kansas City"]},"updated_at":"2026-07-24T05:19:40Z"}