Determination of lower extremity anthropometric parameters using dual energy X-ray absorptiometry: the influence on net joint moments during gait

Ganley, Kathleen J.; Powers, Christopher M.

doi:10.1016/j.clinbiomech.2003.08.002

Cited by 83 publications

(66 citation statements)

References 16 publications

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“…Of those that have, only able-bodied gait has been evaluated and not all possible reference frames have been considered. In contrast, the effect of different inertial parameter sets on lower limb joint moment calculations has been well investigated [15][16][17][18][19]. This is surprising given that, for relatively slow speed movements such as gait, lower limb joint moments are far more likely to be sensitive to a change in reference frame than they are to a change in the magnitude of an inertial parameter set.…”

Section: Introductionmentioning

confidence: 89%

On the expression of joint moments during gait

Schache¹,

Baker²

2007

Gait & Posture

142

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Section: Introductionmentioning

confidence: 89%

On the expression of joint moments during gait

Schache¹,

Baker²

2007

Gait & Posture

142

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“…[44,45,70,71]). Errors in model dimensions and inertial parameters can affect joint angle and moment calculations [72][73][74], which will result in errors in estimated muscle forces. If performing a dynamic analysis, we recommend comparing the whole-body COM acceleration computed from kinematic data to the acceleration generated by measured ground reaction forces.…”

Section: Verifying Musculoskeletal Geometrymentioning

confidence: 99%

Is My Model Good Enough? Best Practices for Verification and Validation of Musculoskeletal Models and Simulations of Movement

Hicks

Uchida

Seth

et al. 2015

Journal of Biomechanical Engineering

560

455

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Computational modeling and simulation of neuromusculoskeletal (NMS) systems enables researchers and clinicians to study the complex dynamics underlying human and animal movement. NMS models use equations derived from physical laws and biology to help solve challenging real-world problems, from designing prosthetics that maximize running speed to developing exoskeletal devices that enable walking after a stroke. NMS modeling and simulation has proliferated in the biomechanics research community over the past 25 years, but the lack of verification and validation standards remains a major barrier to wider adoption and impact. The goal of this paper is to establish practical guidelines for verification and validation of NMS models and simulations that researchers, clinicians, reviewers, and others can adopt to evaluate the accuracy and credibility of modeling studies. In particular, we review a general process for verification and validation applied to NMS models and simulations, including careful formulation of a research question and methods, traditional verification and validation steps, and documentation and sharing of results for use and testing by other researchers. Modeling the NMS system and simulating its motion involves methods to represent neural control, musculoskeletal geometry, muscle-tendon dynamics, contact forces, and multibody dynamics. For each of these components, we review modeling choices and software verification guidelines; discuss variability, errors, uncertainty, and sensitivity relationships; and provide recommendations for verification and validation by comparing experimental data and testing robustness. We present a series of case studies to illustrate key principles. In closing, we discuss challenges the community must overcome to ensure that modeling and simulation are successfully used to solve the broad spectrum of problems that limit human mobility.

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“…The researcher is faced with the choice of directly measuring the BSP for each subject or to use pre-existing models. Direct measurement may involve using mass scanning techniques for each subject (Dumas et al, 2004;Ganley and Powers, 2004), though for simple gait analysis the potential harmful effects of exposing subjects to radiation usually outweighs the advantages of this approach. In choosing a pre-existing model, the researcher must make an appropriate choice from the large selection found in the literature .…”

Section: Estimation Of Body Segment Parametersmentioning

confidence: 99%

Gait Dynamics on a Cross-Slope Walking Surface

Dixon

Pearsall

2010

Journal of Applied Biomechanics

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The purpose of this study was to determine the effect of cross-slope on gait dynamics. Ten young adult males walked barefoot along an inclinable walkway. Ground reaction forces (GRFs), lower-limb joint kinematics, global pelvis orientation, functional leg-length, and joint reaction moments (JRMs) were measured. Statistical analyses revealed differences across limbs (up-slope [US] and down-slope [DS]) and inclinations (level; 0°; and cross-sloped, 6°). Adaptations included increases of nearly 300% in mediolateral GRFs (p < .001), functional shortening the US-limb and elongation of the DS-limb (p < .001), reduced step width (p = .024), asymmetrical changes in sagittal kinematics and JRM, and numerous pronounced coronal plane differences including increased US-hip adduction (and adductor moment) and decreased DS-hip adduction (and adductor moment). Data suggests that modest cross-slopes can induce substantial asymmetrical changes in gait dynamics and may represent a physical obstacle to populations with restricted mobility.

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Determination of lower extremity anthropometric parameters using dual energy X-ray absorptiometry: the influence on net joint moments during gait

Cited by 83 publications

References 16 publications

On the expression of joint moments during gait

On the expression of joint moments during gait

Is My Model Good Enough? Best Practices for Verification and Validation of Musculoskeletal Models and Simulations of Movement

Gait Dynamics on a Cross-Slope Walking Surface

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