Dynamic constraint combined human body inertia parameter identification method

Abstract

The invention discloses a dynamic constraint combined human body inertia parameter identification method. The human body is simplified into a multi-segment rigid model composed of multiple segments ofrigid bodies, and a dynamic equation of the multi-segment rigid model is established; and human body motion sampling data is collected via a motion capturing system and a ground counterforce detection system, a first-step identification human body inertia parameter is obtained via a first simplified mechanical equation, a second-step identification human body inertia parameter is obtained by introducing a basic physical constraint, and a third-step identification human body inertia parameter is obtained via a second simplified mechanical equation, and finally, the inertia parameter whose second-order norm is minimal is selected as a human body inertia parameter identification optimization result. Multiple constraints are introduced, so that a calculation process of human body inertia parameter identification is clear and can be programmed easily; the dynamic equation is simplified to measure the joint moment directly, a joint moment estimated value constraint is introduced for optimization, and the accuracy of an inertia parameter identification result is improved.

Description

technical field [0001] The invention relates to a human body parameter measurement technology, in particular to a human body inertial parameter identification method combined with dynamic constraint conditions. Background technique [0002] Human body inertial parameters directly affect human body motion and gait characteristics, and there are a large number of personalized identification requirements for human body inertial parameters in the fields of medical rehabilitation and sports. The inertial parameters of the human body include the mass of the limbs, the position of the center of mass, and the tensor of inertia. [0003] In the early research, a statistical database of standard human inertial parameters was established through the measurement of human anatomy with a certain number of samples, and a regression fitting equation was established. However, due to the existence of individual differences, the fitting equation is difficult to apply to individual estimation. ...

AI Technical Summary

Problems solved by technology

Considering that it is difficult to directly measure the joint moments of the human body, this method simplifies the human dynamics equations, resulting in the loss of some constraints, which makes it difficult for the inertial parameter identification results to approach the real values.

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