Method for determining contact position parameters of a joint connecting two bones

US9852268B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9852268-B2
Application numberUS-201114363040-A
CountryUS
Kind codeB2
Filing dateDec 9, 2011
Priority dateDec 9, 2011
Publication dateDec 26, 2017
Grant dateDec 26, 2017

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Abstract

Official abstract text for this publication.

A data processing method for determining six parameters of a contact position of a joint which connects two bones, comprising the steps of acquiring a plurality of sample contact position datasets, each dataset comprising six parameters, acquiring a subset of n of the parameters of the contact position as an input parameter dataset, selecting at least two of the sample contact position datasets based on the input parameter dataset and determining the m=6−n remaining parameters of the contact position based on the at least two selected sample contact position datasets.

First claim

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The invention claimed is: 1. A data processing method performed in a computer having a memory for determining six parameters of a contact position of a physiological or artificial joint which connects two bones, wherein the contact position is a relative position between the two bones in which physiological or artificial surfaces defined at ends of the two bones respectively by the bones or by implants carried on the bones are in contact with each other, and wherein three of the parameters define a translational shift and three of the parameters define a rotational shift, the method comprising: acquiring a plurality of sample contact position datasets, each dataset comprising six parameters that correspond to the six parameters describing the contact position; acquiring a subset of n of the parameters of the contact position as an input parameter dataset; selecting at least two of the sample contact position datasets based on the input parameter dataset; and determining the m=6−n remaining parameters of the contact position based on the at least two selected sample contact position datasets. 2. The method of claim 1 , wherein the remaining parameters are determined by interpolation or extrapolation. 3. The method according to claim 2 , wherein the interpolation is a spline interpolation or uses inverse distance weighting. 4. The method according to claim 1 , wherein the selected sample contact position datasets correspond to sample contact positions which are, regarding the input parameters, the nearest neighbors of the contact position. 5. The method of claim 4 , wherein a distance between the contact position and a sample contact position is calculated using a Minkowski distance function. 6. The method according to claim 1 , wherein the sample contact position datasets are arranged in an n-dimensional array and each array entry comprises the m remaining parameters. 7. The method according to claim 1 , wherein the sample contact positions are arranged at equidistant intervals. 8. The method according to claim 1 , wherein a sample contact position dataset is void for an impossible joint contact position. 9. The method of claim 1 , wherein a sample contact position dataset further comprises affiliate information which indicates that the sample contact position belongs to a contact profile of contact positions. 10. The method according to claim 1 , wherein the step of determining the m=6−n remaining parameters of the contact position is repeated for a sequence of input parameter datasets, thus resulting in a sequence of contact positions. 11. The method according to claim 1 , wherein a sample position dataset is determined by virtually positioning three-dimensional images of the two bones such that they are in contact and using the relative position of the bones thus positioned as a sample contact position. 12. The method according to claim 1 , wherein a sample position dataset is automatically determined by using collision detection of three-dimensional models of the two bones. 13. The method according to claim 1 , wherein a sample position dataset is determined by measuring a real joint. 14. A computer program embodied on a non-transitory computer readable medium which, when running on a computer or when loaded onto a computer, causes the computer to determine six parameters of a contact position of a physiological or artificial joint which connects two bones, wherein the contact position is a relative position between the two bones in which physiological or artificial surfaces defined at ends of the two bones respectively by the bones or by implants carried on the bones are in contact with each other, and wherein three of the parameters define a translational shift and three of the parameters define a rotational shift, by performing steps comprising: acquiring a plurality of sample contact position datasets, each dataset comprising six parameters that correspond to the six parameters describing the contact position; acquiring a subset of n of the parameters of the contact position as an input parameter dataset; selecting at least two of the sample contact position datasets based on the input parameter dataset; and determining the m=6-n remaining parameters of the contact position based on the at least two selected sample contact position datasets. 15. A computer on which the computer program according to claim 14 is running or into the memory of which the computer program is loaded.

Assignees

Inventors

Classifications

  • A61B34/10Primary

    Computer-aided planning, simulation or modelling of surgical operations · CPC title

  • Physics · mapped topic

  • for simulation or modelling of medical disorders · CPC title

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What does patent US9852268B2 cover?
A data processing method for determining six parameters of a contact position of a joint which connects two bones, comprising the steps of acquiring a plurality of sample contact position datasets, each dataset comprising six parameters, acquiring a subset of n of the parameters of the contact position as an input parameter dataset, selecting at least two of the sample contact position datasets…
Who is the assignee on this patent?
Gotte Hubert, Brainlab Ag
What technology area does this patent fall under?
Primary CPC classification A61B34/10. Mapped technology areas include Human Necessities.
When was this patent published?
Publication date Tue Dec 26 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 3 related publications on this page (citations in our corpus or others sharing the same primary CPC).