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Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

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Estimating body segment parameters from three-dimensional human body scans.

Pawel Kudzia^1,2, Erika Jackson², Genevieve Dumas²

¹Department of Engineering Science, Simon Fraser University, Burnaby, BC, Canada.

|January 5, 2022

Summary

This study introduces an affordable 3D scanning method for precise, participant-specific body segment parameter estimation. The system offers a low-cost, assumption-free alternative to existing techniques for biomechanical applications.

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Area of Science:

Biomechanics
Anthropometry
3D Imaging

Background:

Participant-specific body segment parameters reduce errors in biomechanical analyses.
Current estimation methods are often costly, assumption-laden, or population-specific.

Purpose of the Study:

Develop a low-cost, participant-specific 3D scanning and segmentation method for body segment parameters.
Eliminate assumptions regarding body geometry, ethnicity, and gender.

Main Methods:

Utilized a Microsoft Kinect v2 camera for 3D surface scanning.
Segmented scans into 16 body segments using open-source tools.
Developed custom software to calculate segment mass, center of mass, and moments of inertia.

Main Results:

Demonstrated consistency in total body volume estimation across repeated scans.
Accurate total body mass estimation comparable to medical scales.
Generated consistent and comparable body segment parameter estimates.

Conclusions:

The developed 3D scanning method provides an inexpensive and accessible approach for estimating participant-specific body segment parameters.
This method offers a viable alternative to expensive or assumption-based techniques.
The associated code is provided for wider adoption.