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A sensitivity analysis method for the body segment inertial parameters based on ground reaction and joint moment
Sumire Futamure1, Vincent Bonnet2, Raphael Dumas3
1Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology, Japan.
Journal of Biomechanics
|September 27, 2017
Summary
A new method simplifies sensitivity analysis for human body dynamics. Segment masses are crucial, while most moments of inertia are not, for accurate gait analysis.
Area of Science:
- Biomechanics
- Human Motion Analysis
- Robotics System Identification
Background:
- Accurate human whole-body dynamic models are essential for biomechanical analysis.
- System identification in robotics offers tools for parameter estimation.
- Sensitivity analysis is crucial for understanding parameter influence in complex models.
Purpose of the Study:
- To develop a simple and efficient method for sensitivity analysis of dynamics parameters in complex whole-body human models.
- To identify which inertial parameters significantly influence gait dynamics and joint moments.
- To assess the feasibility of estimating joint moments from limited data.
Main Methods:
- Utilized regressor matrices from robotics system identification theory.
- Linearized equations of motion with respect to segment inertial parameters.
- Applied sensitivity analysis to gait dynamics and kinematics data from nine subjects using a 15-segment 3D model.
- Calculated sensitivity indices to determine parameter influence.
Main Results:
- Identified 76 out of 150 segment inertial parameters as non-influential for gait.
- Segment masses were found to be influential parameters.
- Moments of inertia, except for the trunk, were generally not influential for ground reaction forces, moments, and joint moments.
- Demonstrated that over 90% of lower-limb joint moments during stance can be estimated using only force-plate and kinematics data.
Conclusions:
- The proposed sensitivity analysis method is effective for complex human body models.
- Segment masses are critical, whereas most moments of inertia have minimal impact on gait dynamics.
- Accurate estimation of lower-limb joint moments is achievable with reduced inertial parameter knowledge.
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