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contributor authorNorman-Gerum, Valerie
contributor authorMcPhee, John
date accessioned2019-02-28T11:11:09Z
date available2019-02-28T11:11:09Z
date copyright10/23/2018 12:00:00 AM
date issued2018
identifier issn0148-0731
identifier otherbio_140_12_121011.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4253585
description abstractThe purpose of this work is twofold: first, to synthesize a motion pattern imitating sit-to-stand (STS) and second, to compare the kinematics and dynamics of the resulting motion to healthy STS. Predicting STS in simulation inspired the creation of three models: a biomechanical model, a motion model, and performance criteria as a model of preference. First, the human is represented as three rigid links in the sagittal plane. This model captures aspects of joint, foot, and buttocks physiology, which makes it the most comprehensive planar model for predicting STS to date. Second, candidate STS trajectories are described geometrically by a set of Bézier curves which seem well suited to predictive biomechanical simulations. Third, with the assumption that healthy people naturally prioritize mechanical efficiency, disinclination to a motion is described as a cost function of joint torques, and for the first time, physical infeasibility including slipping and falling. This new dynamic optimization routine allows for motions of gradually increasing complexity while the model's performance is improving. Using these models and optimal control strategy together has produced gross motion patterns characteristic of healthy STS when compared with normative data from the literature.
publisherThe American Society of Mechanical Engineers (ASME)
titleConstrained Dynamic Optimization of Sit-to-Stand Motion Driven by Bézier Curves
typeJournal Paper
journal volume140
journal issue12
journal titleJournal of Biomechanical Engineering
identifier doi10.1115/1.4041527
journal fristpage121011
journal lastpage121011-7
treeJournal of Biomechanical Engineering:;2018:;volume( 140 ):;issue: 012
contenttypeFulltext


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