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research-article

The effects of prosthesis inertial parameters on inverse dynamics: A probabilistic analysis

[+] Author and Article Information
Brecca Gaffney

Department of Mechanical & Materials Engineering Human Dynamics Laboratory University of Denver
brecca.gaffney@gmail.com

Cory L. Christiansen

Department of Physical Medicine & Rehabilitation University of Colorado Denver Geriatric Research Education and Clinical Center VA Eastern Colorado Health Care System
cory.christiansen@ucdenver.edu

Amanda M. Murray

Department of Physical Medicine & Rehabilitation University of Colorado Denver Geriatric Research Education and Clinical Center VA Eastern Colorado Health Care System
Amanda.Murray2@utoledo.edu

Casey A. Myers

Department of Mechanical & Materials Engineering Center for Orthopaedic Biomechanics University of Denver
casey.myers1@gmail.com

Peter J. Laz

Department of Mechanical & Materials Engineering Center for Orthopaedic Biomechanics University of Denver
peter.laz@du.edu

Bradley S. Davidson

Department of Mechanical & Materials Engineering Human Dynamics Laboratory University of Denver 2155 E Wesley Ave. ECS 443 Denver, CO 80208
Bradley.davidson@du.edu

1Corresponding author.

ASME doi:10.1115/1.4038175 History: Received June 07, 2017; Revised September 19, 2017

Abstract

Joint kinetic measurement is a fundamental tool used to quantify compensatory movement patterns in participants with transtibial amputation (TTA). Joint kinetics are calculated through inverse dynamics (ID) and depend on segment kinematics, external forces, and both segment and prosthetic inertial parameters (PIPS); yet the individual influence of PIPs on ID is unknown. The objective of this investigation was to assess the importance of parameterizing PIPs when calculating ID using a probabilistic analysis. A series of Monte Carlo simulations were performed to assess the influence of uncertainty in PIPs on ID. Multivariate input distributions were generated from experimentally measured PIPs (foot/shank: mass, center of mass, moment of inertia) of 10 prostheses and output distributions were hip and knee joint kinetics. Confidence bounds (2.5-97.5%) and sensitivity of outputs to model input parameters were calculated throughout one gait cycle. Results demonstrated that PIPs had a larger influence on joint kinetics during the swing period than the stance period (e.g. maximum hip flexion/extension moment confidence bound size: stance = 5.6 N-m, swing: 11.4 N-m). Joint kinetics were most sensitive to shank mass during both the stance and swing periods. Accurate measurement of prosthesis shank mass is necessary to calculate joint kinetics with ID in participants with TTA with passive prostheses consisting of total contact carbon fiber sockets and dynamic elastic response feet during walking.

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