{"id":{"repo_id":"denver","oai_identifier":"oai:digitalcommons.du.edu:etd-1604"},"canonical_url":"https://search.dev.ndltd.org/etd/denver/oai:digitalcommons.du.edu:etd-1604","repository":{"repo_id":"denver","name":"University of Denver","base_url":"https://digitalcommons.du.edu/do/oai/"},"display":{"title":"Generalizable Methods for Modeling Lumbar Spine Kinematics","abstract":"<p>A more complete understanding of lumbar spine kinematics could improve diagnoses and treatment of low back pathologies and may advance the development of biomechanical models. Kinematics describes motion of the five lumbar vertebrae without consideration for the forces that cause the motion. Despite considerable attention from researchers and clinicians, lumbar spine kinematics are not fully understood because the anatomy is not accessible for direct observation and the complex governing biomechanics produce small magnitude, coupled intervertebral movements.</p> <p>The overall goal of this project was to develop a descriptive model of intervertebral lumbar spine kinematics that is applicable to a generalizable subject population with diverse anthropometry. To accomplish this, a method was developed for measuring three-dimensional vertebral configuration using positional magnetic resonance imaging (MRI). The method makes use of automated vertebral registration to address time limitations in current data processing techniques and improves the ability to power experimental investigations.</p> <p>Finally, a geometric model of lumbar vertebral kinematics was developed using principal component regression applied to <em>in vivo</em> vertebral measurement data across the range of flexion and extension joint motion. This principal component-based approach offers unique advantages for predicting and interpreting performance of complex systems such as lumbar joint biomechanics because no assumptions are made regarding the governing mechanisms. This provides an opportunity to infer mechanistic characteristics about intervertebral joint kinematics and to use <em>in vivo</em> data to validate musculoskeletal models.</p>","abstract_html":"&lt;p&gt;A more complete understanding of lumbar spine kinematics could improve diagnoses and treatment of low back pathologies and may advance the development of biomechanical models. Kinematics describes motion of the five lumbar vertebrae without consideration for the forces that cause the motion. Despite considerable attention from researchers and clinicians, lumbar spine kinematics are not fully understood because the anatomy is not accessible for direct observation and the complex governing biomechanics produce small magnitude, coupled intervertebral movements.&lt;/p&gt; &lt;p&gt;The overall goal of this project was to develop a descriptive model of intervertebral lumbar spine kinematics that is applicable to a generalizable subject population with diverse anthropometry. To accomplish this, a method was developed for measuring three-dimensional vertebral configuration using positional magnetic resonance imaging (MRI). The method makes use of automated vertebral registration to address time limitations in current data processing techniques and improves the ability to power experimental investigations.&lt;/p&gt; &lt;p&gt;Finally, a geometric model of lumbar vertebral kinematics was developed using principal component regression applied to &lt;em&gt;in vivo&lt;/em&gt; vertebral measurement data across the range of flexion and extension joint motion. This principal component-based approach offers unique advantages for predicting and interpreting performance of complex systems such as lumbar joint biomechanics because no assumptions are made regarding the governing mechanisms. This provides an opportunity to infer mechanistic characteristics about intervertebral joint kinematics and to use &lt;em&gt;in vivo&lt;/em&gt; data to validate musculoskeletal models.&lt;/p&gt;","abstract_has_math":false,"creators":["Simons, Craig Joseph"],"institution":null,"degree_name":"M.S.","degree_level":"Masters Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Bradley S. Davidson, Ph.D.","Loren Cobb","Peter Laz","Mohammad Mahoor","Nathan Sturtevant"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-01-01T08:00:00Z","date_published":"2013-01-01T08:00:00Z","updated_at":"2026-07-24T02:03:03Z","subjects":["Kinematics","Lumbar spine","Positional MRI","Mechanical Engineering","Other Mechanical Engineering"],"languages":["en"],"rights":["<p>Copyright is held by the author. User is responsible for all copyright compliance.</p>"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.du.edu/etd/605","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bradley S. 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Despite considerable attention from researchers and clinicians, lumbar spine kinematics are not fully understood because the anatomy is not accessible for direct observation and the complex governing biomechanics produce small magnitude, coupled intervertebral movements.</p> <p>The overall goal of this project was to develop a descriptive model of intervertebral lumbar spine kinematics that is applicable to a generalizable subject population with diverse anthropometry. To accomplish this, a method was developed for measuring three-dimensional vertebral configuration using positional magnetic resonance imaging (MRI). The method makes use of automated vertebral registration to address time limitations in current data processing techniques and improves the ability to power experimental investigations.</p> <p>Finally, a geometric model of lumbar vertebral kinematics was developed using principal component regression applied to <em>in vivo</em> vertebral measurement data across the range of flexion and extension joint motion. This principal component-based approach offers unique advantages for predicting and interpreting performance of complex systems such as lumbar joint biomechanics because no assumptions are made regarding the governing mechanisms. This provides an opportunity to infer mechanistic characteristics about intervertebral joint kinematics and to use <em>in vivo</em> data to validate musculoskeletal models.</p>"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Generalizable Methods for Modeling Lumbar Spine Kinematics"]}]}],"canonical_facts":{"dc:contributor":["Bradley S. Davidson, Ph.D.","Loren Cobb","Peter Laz","Mohammad Mahoor","Nathan Sturtevant"],"dc:creator":["Simons, Craig Joseph"],"dc:date.available":["2001-01-01T08:00:00Z"],"dc:description.abstract":["<p>A more complete understanding of lumbar spine kinematics could improve diagnoses and treatment of low back pathologies and may advance the development of biomechanical models. Kinematics describes motion of the five lumbar vertebrae without consideration for the forces that cause the motion. Despite considerable attention from researchers and clinicians, lumbar spine kinematics are not fully understood because the anatomy is not accessible for direct observation and the complex governing biomechanics produce small magnitude, coupled intervertebral movements.</p> <p>The overall goal of this project was to develop a descriptive model of intervertebral lumbar spine kinematics that is applicable to a generalizable subject population with diverse anthropometry. To accomplish this, a method was developed for measuring three-dimensional vertebral configuration using positional magnetic resonance imaging (MRI). The method makes use of automated vertebral registration to address time limitations in current data processing techniques and improves the ability to power experimental investigations.</p> <p>Finally, a geometric model of lumbar vertebral kinematics was developed using principal component regression applied to <em>in vivo</em> vertebral measurement data across the range of flexion and extension joint motion. This principal component-based approach offers unique advantages for predicting and interpreting performance of complex systems such as lumbar joint biomechanics because no assumptions are made regarding the governing mechanisms. This provides an opportunity to infer mechanistic characteristics about intervertebral joint kinematics and to use <em>in vivo</em> data to validate musculoskeletal models.</p>"],"dc:format":["application/pdf"],"dc:identifier":["https://digitalcommons.du.edu/etd/605"],"dc:language":["en"],"dc:rights":["<p>Copyright is held by the author. User is responsible for all copyright compliance.</p>"],"dc:subject":["Kinematics","Lumbar spine","Positional MRI","Mechanical Engineering","Other Mechanical Engineering"],"dc:title":["Generalizable Methods for Modeling Lumbar Spine Kinematics"],"thesis:degree_level":["Masters Thesis"],"thesis:degree_name":["M.S."]},"updated_at":"2026-07-24T02:03:03Z"}