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Predictive Simulations of Gait and Their Application in Prosthesis Design

Koelewijn, Anne D
http://rave.ohiolink.edu/etdc/view?acc_num=csu1533901459119777

Abstract Details

2018, Doctor of Engineering, Cleveland State University, Washkewicz College of Engineering.
Predictive simulations predict human gait by solving a trajectory optimization problem by minimizing energy expenditure. These simulations could predict the effect of a prosthesis on gait before its use. This dissertation has four aims, to show the application of predictive simulations in prosthesis design and to improve the quality of predictive simulations. Aim 1 was to explain joint moment asymmetry in the knee and hip in gait of persons with a transtibial amputation (TTA gait). Predictive simulations showed that an asymmetric gait required less effort. However, a small effort increase yielded a gait with increased joint moment symmetry and reduced joint reaction forces. This suggests that gait training could reduce the risk of developing osteoarthritis in persons with a transtibial amputation. Aim 2 was to compare the effect of different prosthesis alignments on TTA gait. Predictive simulations were solved using a three-dimensional musculoskeletal model with different prosthetic alignments. A flexion alignment of the prosthesis might be favored over a neutral alignment, since the metabolic cost and joint reaction forces were lower, though the differences were small. Also, predictions indicated that a lateral translation or an external rotation could alleviate skin problems by reducing skin-to-socket stresses. Aim 3 was to compare the gait objective of minimizing metabolic energy to minimizing muscular effort. Four metabolic energy expenditure models were selected after an experiment to compare metabolic cost calculated with seven metabolic energy models to metabolic cost from pulmonary gas exchange measurements. The minimum energy solution was more similar to normal gait in joint angles, while the minimum effort solution was more similar in joint moments, especially at the knee. However, neither solution could entirely explain human gait. Aim 4 was to propose an approach to optimize in a stochastic environment and implement it to explain antagonistic muscle co-contraction in human movement. In a stochastic environment, muscle co-contraction was energy optimal for certain tasks and nonzero foot clearance was energy efficient. The approach was then applied to TTA gait to explain co-contraction of the upper-leg muscles on the prosthesis side. The results suggested that antagonistic co-contraction is energy optimal for human gait.
Antonie van den Bogert (Advisor)
Ann Rheinthal (Committee Member)
Hanz Richter (Committee Member)
Eric Schearer (Committee Member)
Daniel Simon (Committee Member)
279 p.
Biomechanics; Mechanical Engineering; Rehabilitation
Gait, Biomechanics, Predictive Simulation, Trajectory Optimization, Transtibial amputee, Prosthesis

Recommended Citations

Citations

  • Koelewijn, A. D. (2018). Predictive Simulations of Gait and Their Application in Prosthesis Design [Doctoral dissertation, Cleveland State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=csu1533901459119777

    APA Style (7th edition)

  • Koelewijn, Anne. Predictive Simulations of Gait and Their Application in Prosthesis Design. 2018. Cleveland State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=csu1533901459119777.

    MLA Style (8th edition)

  • Koelewijn, Anne. "Predictive Simulations of Gait and Their Application in Prosthesis Design." Doctoral dissertation, Cleveland State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=csu1533901459119777

    Chicago Manual of Style (17th edition)

csu1533901459119777
891
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This open access ETD is published by Cleveland State University and OhioLINK.