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dc.contributor.authorCaruntu, Dumitru I.;Moreno, Ricardo
dc.date.accessioned2023-04-06T13:03:35Z
dc.date.available2023-04-06T13:03:35Z
dc.date.copyright12/19/2022 12:00:00 AM
dc.date.issued2022
dc.identifier.issn15551415
dc.identifier.othercnd_018_02_021003.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289002
dc.description.abstractThis work investigates the kinematics and ligament, muscle, and contact forces of droplanding exercise. A twodimensional sagittal inverse dynamics knee model is developed to predict internal forces experienced during this exercise. Experimental data is gathered using a vicon motion analysis system and AMTI force plates. This experimental data is then used as input to the inverse dynamics model. The forces produced during the droplanding exercise are computed using an optimization approach. The tibiofemoral contact point was predicted to move anteriorly as the most significant muscle, ligament, and contact forces increased reaching their peaks. Next, the contact point moves posteriorly as the most significant internal forces decrease, and then moves again anteriorly until the end of the exercise (end of the ascent phase) as the internal forces decrease to zero. Posterior cruciate ligament (PCL) is predicted to be the only significant ligament during droplanding. The largest force values experienced during droplanding are gluteus muscle and tibiofemoral contact forces with a peak of 17 body weight (BW), quadriceps muscle force with a peak of 14 BW, and hip contact force along femoral longitudinal direction with a peak of 7 BW. A comparison with data available in the literature is conducted.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleDropLanding Inverse Dynamics Model of Human Knee
dc.typeJournal Paper
dc.journal.volume18
dc.journal.issue2
dc.journal.titleJournal of Computational and Nonlinear Dynamics
dc.identifier.doi10.1115/1.4056356
dc.journal.fristpage21003
dc.journal.lastpage210039
dc.page9
dc.treeJournal of Computational and Nonlinear Dynamics:;2022:;volume( 018 ):;issue: 002
dc.contenttypeFulltext


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