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Body segment inertial parameters of children derived from a large database of 3D body scans
Bhrigu K Lahkar1, Thomas Robert2, Fermín Basso3
1Kinesiology for Assessment of Sports, Health and Injury (KASHI) Lab, School of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, India.
Insights
This study developed regression models for child body segment inertial parameters (BSIPs) using 3D scans. These models provide accurate estimations crucial for pediatric biomechanical analysis and movement studies.
Area of Science:
- Biomechanics
- Human Movement Analysis
- Pediatric Physiology
Background:
- Accurate body segment inertial parameters (BSIPs) are essential for human movement analysis.
- Existing BSIP data for children is limited, hindering pediatric biomechanical research.
Purpose of the Study:
- To develop regression models for estimating pediatric BSIPs (mass, center of mass position, moments of inertia).
- To utilize 3D body scan data from a large cohort of children for personalized BSIP calculations.
- To provide a comprehensive dataset and models for child-specific biomechanical analysis.
Main Methods:
- Acquired 3D body scans from 688 children (ages 2.9-12.7 years).
- Processed scans to create personalized volumetric body meshes and compute 3D BSIPs.
- Developed normalized regression models for BSIPs, stratified by sex.
Main Results:
- Regression models showed high accuracy for normalized mass and moderate-to-good accuracy for normalized center of mass and radii of gyration.
- Observed age-related changes in normalized mass, center of mass position, and radii of gyration across various body segments.
- Identified specific trends such as posterior shifts in abdominal CoM and anterior shifts in thigh CoM.
Conclusions:
- This study presents the first comprehensive BSIP regression models for a large, gender-balanced pediatric cohort.
- The automated approach and detailed regressions address significant limitations in prior pediatric biomechanics research.
- These findings are expected to significantly advance pediatric biomechanical modeling and movement analysis.
Abstract:
Body segment inertial parameters (BSIPs) are critical for human movement analysis. However, child-specific BSIPs remains limited. This study aimed to develop regression models for BSIPs (mass, CoM-position, and moments of inertia) using 3D body scans from 688 children aged 2.9-12.7 years. A 3D scanning system was used to capture body surfaces as point clouds, which were automatically processed to generate segmented, personalized volumetric body meshes with embedded segment coordinate systems. These meshes were then used to compute 3D BSIPs, which were normalized (relative to body mass and corresponding segment length) and fitted by regression models separately for males and females. The regression models demonstrated high predictive accuracy for normalized mass and moderate-to-good accuracy for normalized CoM-positions and radii of gyration. Age-related changes were observed as reductions in normalized mass for the head-neck and abdomen, alongside increases for the thigh. Normalized CoM-positions shifted posteriorly for the abdomen, anteriorly for the thigh, and proximally for the forearm. Normalized radii of gyration declined across all directions, particularly for the hand and thigh. This work provides the first comprehensive BSIP regressions for a large, gender-balanced cohort of children up to 12 years old, addressing limitations in prior research with a fully automated approach. These regressions are expected to advance biomechanical modeling and enhance movement analysis in pediatric populations.
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