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Determining and Controlling External Power Output During Regular Handrim Wheelchair Propulsion

Determining and Controlling External Power Output During Regular Handrim Wheelchair Propulsion

Published on: February 5, 2020

Determination of inertial parameters using a dynamometer.

Jongsang Son¹, Jeseong Ryu¹, Jungyoon Kim¹

¹Department of Biomedical Engineering and Institute for Convergence Study of Bio-Medical Wellness, Yonsei University (Wonju Campus), Maeji-ri, Heungeop-myeon, Wonju-si, Gangwon-do 220-710, Republic of Korea.

Bio-Medical Materials and Engineering

|September 18, 2014

Summary

This summary is machine-generated.

A new method determines moment of inertia using a dynamometer and optimization, accurately estimating human body segment inertial parameters. This technique enhances the reliability of human dynamics studies.

Keywords:

Inertial parameters center of mass mass moment of inertia radius of gyration

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Area of Science:

Biomechanics
Human Dynamics
Inertial Parameter Estimation

Background:

Accurate estimation of inertial parameters is crucial for biomechanical analysis.
Existing methods may lack precision or require complex setups.

Purpose of the Study:

To introduce a simple method for determining the moment of inertia using a commercial dynamometer.
To estimate inertial parameters (mass, center of mass, moment of inertia) via an optimization technique.
To validate the method by comparing estimated parameters with theoretical values.

Main Methods:

Utilized the dynamic equation of motion to determine the moment of inertia.
Employed an optimization technique for inertial parameter estimation.
Tested the method at various passive angular speeds (240, 270, 300°/s) using an elbow attachment and a 3 kg weight.

Main Results:

Moment of inertia values for the elbow attachment were consistent across different speeds (e.g., 0.216 ± 0.017 kg·m² at 240°/s).
Moment of inertia values for the 3 kg weight were also consistent across speeds (e.g., 0.821 ± 0.054 kg·m² at 240°/s).
Estimated inertial parameters closely matched theoretical values for both the attachment and the weight.

Conclusions:

The developed method provides accurate and reliable estimation of inertial parameters.
The technique is effective irrespective of angular speed, demonstrating robustness.
This method holds potential for improving human body segment analysis in biomechanics and human dynamics research.