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TECHNICAL PAPERS: Joint/Whole Body

Using Mass Distribution Information to Model the Human Thigh for Body Segment Parameter Estimation

[+] Author and Article Information
Jennifer L. Durkin

Department of Kinesiology, University of Waterloodurkinjl@healthy.uwaterloo.ca

James J. Dowling

Department of Kinesiology,  McMaster University, Hamilton, ON, Canadadowlingj@mcmaster.ca

Laura Scholtes

Department of Kinesiology,  McMaster University, Hamilton, ON, Canada

J Biomech Eng 127(3), 455-464 (Jan 31, 2005) (10 pages) doi:10.1115/1.1894367 History: Received October 17, 2002; Revised December 01, 2004; Accepted January 31, 2005

Accurate estimations of body segment inertial parameters (BSPs) are required to calculate the kinetics of motion. The purpose of this study was to develop a geometric model of the human thigh segment based on mass distribution properties determined from dual energy x ray absorptiometry (DEXA). One hundred subjects from four populations underwent a DEXA scan and anthropometric measurements were taken. The mass distribution properties of the thigh segment were determined for 20 subjects, a geometric model was developed, and the model was applied to the remaining 80 subjects. The model was validated by comparing to benchmark DEXA measurements. Four other popular models in the literature were also evaluated in the same manner. No one set of predictors performed best for a particular group or BSP, however modeling the mass distribution properties of the segment allows the assumption of constant density while still accurately representing the inertial properties of the segment and provides promise for future development of BSP models.

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Copyright © 2005 by American Society of Mechanical Engineers
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Figures

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Figure 1

Density image of a young female volunteer produced from DEXA scan information to display bony landmarks. Dashed line represents an example of the digitization method for the thigh segment.

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Figure 2

Mass image of a young female volunteer produced from DEXA scan information to display all soft tissue mass, ensuring that all relevant thigh mass is contained within the digitized area (dashed line). Image is produced using raw data dimensions of 1.32×0.53cm.

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Figure 3

Example of interpolated data points fitting raw DEXA data with very little smoothing. Mass cross section is through midthigh region.

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Figure 4

Ensemble averages of the mass distribution characteristics of the thigh segment for four population groups. The plots represent the amount of mass present every 1% segment length from proximal to distal ends. The area between the curves represents 100% of the segment mass. Positive y axis represents lateral thigh mass. Negative y axis represents medial thigh mass. Inside curve represents the mean mass distribution, outside curve represents +1 SD. The negative standard deviation has been omitted.

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Figure 5

Diagram of the geometric model used to represent the mass distribution characteristics of the thigh segment for four groups of humans. Points P and D represent the proximal and distal segment endpoints, respectively.

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Figure 6

Diagram of the proximal segment of the geometric model illustrating the three slopes of the oblique plane and the elements used to integrate for segment volume

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Figure 7

Scatterplots of model estimations vs. DEXA measurements of (a) mass and (b) ICM for the female (19–30 years) group. Solid line represents the unity line between the model predictions and DEXA measurements.

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Figure 8

Ensemble averages of the (a) mass distribution properties and (b) ICM distribution properties estimated by the developed model and measured by DEXA. Mean model estimates are displayed as a percent of DEXA mass to show where the model failed to estimate the desired parameter. The curves represent the mean ensemble averages from the male (19–30 years) group.

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