Human Body Inertia Properties

2013 ◽  
pp. 271-302
Keyword(s):  
Human Body ◽  
Inertia Properties ◽  
Body Inertia

Rigid Body Inertia Properties

2021 ◽  
Vol 63 (9) ◽  
pp. 1483-1489
Author(s):  
T. B. Goldvarg ◽  
V. N. Shapovalov
Keyword(s):  
Rigid Body ◽  
Inertia Properties ◽  
Body Inertia

Indirect Measurement of the Inertia Properties of a Knee Prosthesis Through a Simple Frequency-Domain Technique

2009 ◽  
Vol 3 (4) ◽  
Author(s):  
Emiliano Mucchi ◽  
Giuliamarta Bottoni ◽  
Raffaele Di Gregorio
Keyword(s):  
Medical Devices ◽  
Frequency Response Function ◽  
Knee Prosthesis ◽  
Indirect Measurement ◽  
Measurement Sensitivity ◽  
Fast Evaluation ◽  
Transfemoral Amputees ◽  
Inertia Properties ◽  
Inertia Forces ◽  
Body Inertia

The dynamic study of humans carrying prostheses requires the rigid-body inertia properties of the prostheses. Since such properties are difficult to evaluate, in general, roughly estimated values of these quantities are used. These approximations may yield significant errors in the evaluation of some dynamic quantities (i.e., the inertia forces due to the prosthesis). This work is addressed to assess an experimental technique, based on frequency response function measurements, that indirectly measures the inertia properties of prostheses for transfemoral amputees. First, a specifically designed specimen and, then, a real prosthesis are tested for assessing the proposed technique. The results are that the measurement sensitivity is 0.002 kg m2 for inertia-tensor entries and 3 mm for center-of-gravity coordinates. Thus, the proposed technique is effective for a precise and fast evaluation of the inertia properties of medical devices such as prostheses.

Finite Element Incremental Approach and Exact Rigid Body Inertia

1996 ◽  
Vol 118 (2) ◽  
pp. 171-178 ◽  
Author(s):  
A. A. Shabana
Keyword(s):  
Finite Element ◽  
Rigid Body ◽  
Rigid Bodies ◽  
Simple Expression ◽  
Shape Functions ◽  
Large Rotation ◽  
Nodal Coordinates ◽  
Inertia Properties ◽  
Element Shape ◽  
Body Inertia

In the dynamics of multibody systems that consist of interconnected rigid and deformable bodies, it is desirable to have a formulation that preserves the exactness of the rigid body inertia. As demonstrated in this paper, the incremental finite element approach, which is often used to solve large rotation problems, does not lead to the exact inertia of simple structures when they rotate as rigid bodies. Nonetheless, the exact inertia properties, such as the mass moments of inertia and the moments of mass, of the rigid bodies can be obtained using the finite element shape functions that describe large rigid body translations by introducing an intermediate element coordinate system. The results of application of the parallel axis theorem can be obtained using the finite element shape functions by simply changing the element nodal coordinates. As demonstrated in this investigation, the exact rigid body inertia properties in case of rigid body rotations can be obtained using the shape function if the nodal coordinates are defined using trigonometric functions. The analysis presented in this paper also demonstrates that a simple expression for the kinetic energy can be obtained for flexible bodies that undergo large displacements without the need for interpolation of large rotation coordinates.

Identification of Human Inertia Properties Using a Momentum-Based Approach

2012 ◽  
Vol 134 (10) ◽  
Author(s):  
Qi Lu ◽  
Ou Ma
Keyword(s):  
Human Body ◽  
Measurement Errors ◽  
Least Square Method ◽  
Least Square ◽  
Identification Procedure ◽  
Lagrangian Equations ◽  
Internal Forces ◽  
Inertia Properties ◽  
Dynamics Simulations ◽  
Tree Type

This paper presents a momentum-based approach for identifying the barycentric parameters of a human body. The human body is modeled as a multiple rigid-body dynamical system with a tree-type topology using the principle of impulse and momentum. Since the resulting impulse-momentum equations are linear in terms of the unknown barycentric parameters, these parameters can be easily solved using the least-square method or other well-understood solution techniques. The approach does not require measuring or estimating accelerations and internal forces because they do not appear in the impulse-momentum equations and, thus, the resulting identification procedure is less demanding on the measurement and also less sensitive to measurement errors in comparison with other existing methods derived based on Newton-Euler or Lagrangian equations. The momentum-based approach has been studied by dynamics simulations with the consideration of possible measurement errors. The study showed good results.

Trajectory Estimation of Human Mass Center Based on an Inertia Identification Approach

2012 ◽  
Author(s):  
Wenwu Xiu ◽  
Qi Lu ◽  
Ou Ma
Keyword(s):  
Human Body ◽  
Experimental Testing ◽  
Time Estimation ◽  
Mass Center ◽  
Primary Input ◽  
Trajectory Estimation ◽  
Body Segments ◽  
Real Time Estimation ◽  
Identification Approach ◽  
Inertia Properties

Mass center of a human body is not a fixed point on the human body because the inertia distribution of the human body changes with body posture. Real-time estimation of the location of human mass center is often required for many biomechanical or biomedical applications. This is not an easy task if the inertia properties of the human’s body segments are unknown. This paper presents a technique for estimating the trajectory of the human mass center based on a recently developed inertia properties identification technology which was derived based on the impulse-momentum principle. The proposed technique assumes a human body as a general treelike multibody system, such that the mass center of the human is predictable with the knowledge of the barycentric parameters of the human. The latter can be identified using inertia identification method. This technique is advantageous because it requires only the 3D motion capture data as its primary input and does not need to know the inertia and geometric parameters of individual body segments of the human. The paper presents a dynamic simulation based study of the proposed estimation technique and also describes an ongoing experimental testing.

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