A mathematical model for the computational determination of parameter values of anthropomorphic segments

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305

A mathematical inertia model which permits the determination of personalized segmental inertia parameter values from anthropometric measurements is described. The human body is modelled using 40 geometric solids which are specified by 95 anthropometric measurements. A 'stadium' solid is introduced for modelling the torso segments using perimeter and width measurements. This procedure is more accurate than the use of elliptical discs of given width and depth and permits a smaller number of such solids to be used. Inertia parameter values may be obtained for body models of up to 20 segments. Errors in total body mass estimates from this and other models are discussed with reference to the unknown lung volumes.

Section: Discussionsupporting

confidence: 76%

Section: Geometrical Representationmentioning

confidence: 99%

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The simulation of aerial movement—II. A mathematical inertia model of the human body

Yeadon

1990

313

305

“…Determination of subject-specific strength parameters has been achieved using isovelocity dynamometer measurements . Various methods have been used to determine personalised inertia parameters including geometric models of body segments (Hatze, 1980, Jensen, 1978, Yeadon, 1990b. During an impact such as heel strike in running the skeletal structures of the body experience high accelerations whereas the soft tissue acceleration is delayed (Nigg et al, 1995).…”

Section: Introductionmentioning

confidence: 99%

Determination of subject-specific model parameters for visco-elastic elements

Wilson

King

Yeadon

2006

The determination of subject-specific model parameter values is necessary in order for a computer simulation model of human motion to be evaluated quantitatively. This study used an optimisation procedure along with a kinematically-driven simulation model of the contact phase in running jumps to determine the elastic parameters of segmental wobbling masses and the foot-ground interface. Kinetic and kinematic data were obtained on a running jump for height and a running jump for distance performed by an elite male high jumper. Stiffness and damping coefficients of the visco-elastic elements in the model were varied until the difference between simulation and performance was minimised. Percentage differences of 6% and 9% between the simulated and recorded performances were obtained in the jumps for height and distance respectively. When the parameters obtained from the jump for height were used in a simulation of the jump for distance (and vice versa) there was poor agreement with the recorded jump. On the other hand a common set of visco-elastic parameters were obtained using the data from both recorded jumps resulting in a mean difference of only 8% (made up of 7% and 10%) between simulation and performance that was almost as good as the individual matches. Simulations were not overly sensitive to perturbations of the common set of visco-elastic parameters. It is concluded that subject-specific elastic parameters should be calculated from more than a single jump in order to provide a robust set of values that can be used in different simulations.

“…To our knowledge, in previous approaches to forearm dynamics a single rigid segment was used that rotated around two axes through the elbow joint (Hatze, 1980;Winter, 1990;Nigg and Herzog, 1999). Peterson (1994) presented a rigid body model of the arm, but he neither gave any data concerning the dynamical parameters of his model, nor mentioned the methods with which such parameters were determined.…”

Section: Introductionmentioning

confidence: 99%

A rigid body model of the forearm

Reich¹,

Daunicht²

2000

In this article the forearm, with its complex, continuous motion of masses during pronation/supination, was approximated by a rigid body model consisting of a radial segment rotating around an ulnar segment. The method used to obtain the model parameters is based on three-dimensional voxel data that include velocity information. We propose a criterion that allows the voxels to be attributed to either of the two segments. It is based on the notion that the rotational kinetic energy determined from the voxel data equals the kinetic energy of the rigid body model. To obtain a three-dimensional smoothing we further propose a parameterization of the shape of both segments. These shapes can then be used to determine the dynamic integrals of the segments, i.e. mass, center of mass, and inertia. Using this approach we determined all model parameters for a human forearm from three series of MRI scans in a supinated, a pronated, and an intermediate position. In the appendix, a procedure is described that allows the dynamic quantities to be scaled homogeneously without recalculation of the integrals. Thus, this article provides all essential parameters required for three-dimensional dynamic simulations of general movements of the forearm.