Localization and tracking of an object

US10323922B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10323922-B2
Application numberUS-201514841198-A
CountryUS
Kind codeB2
Filing dateAug 31, 2015
Priority dateAug 29, 2014
Publication dateJun 18, 2019
Grant dateJun 18, 2019

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

This disclosure relates to localization and tracking of an object. As one example, measurement data can be stored in memory to represent measured electrical signals at each of a plurality of known measurement locations in a given coordinate system in response to an applied signal at an unknown location in the given coordinate system. A dipole model cost function has parameters representing a dipole location and moment corresponding to the applied signal. A boundary condition can be imposed on the dipole model cost function. The unknown location in the given coordinate system, corresponding to the dipole location, can then be determined based on the stored measurement data and the dipole model cost function with the boundary condition imposed thereon.

First claim

Opening claim text (preview).

What is claimed is: 1. A method comprising: storing measurement data in memory representing measured electrical signals at each of a plurality of known measurement locations in a given coordinate system in response to an applied signal at an unknown location in the patient's body and in the given coordinate system the applied signal comprising a predetermined waveform that is distinct from anatomically generated signals, the plurality of known measurement locations comprising locations of respective electrophysiological sensors in the given coordinate system registered with respect to a patient's anatomy and used to sense the measured electrical signals, and the locations of the respective sensors comprising at least one of non-invasive locations distributed about a surface of the patient's body or invasive locations within the patient's body where the sensors have been attached; providing, to a processor communicatively coupled to the memory, a dipole model cost function having parameters representing a dipole location and moment corresponding to the applied signal; imposing a boundary condition on the dipole model cost function; and determining, with the processor, the unknown location in the given coordinate system, corresponding to the dipole location, based on the stored measurement data and the dipole model cost function with the boundary condition imposed thereon. 2. The method of claim 1 , wherein imposing the boundary condition further comprises: reconstructing the measured electrical signals on a spatial envelope in the given coordinate system and storing the reconstructed electrical signals in the memory, the unknown location in the given coordinate system being determined based on the dipole model cost function and the reconstructed electrical signals. 3. The method of claim 2 , wherein the spatial envelope is a first spatial envelope, and wherein determining the unknown location further comprises: repeatedly reconstructing electrical signals to another envelope at a location between the first spatial envelope and the unknown location and determining the unknown location based on applying the reconstructed electrical signals on the other envelope to the dipole model cost function until a difference between the dipole location and a previously determined dipole location is less than a threshold. 4. The method of claim 1 , wherein the boundary condition is integrated in the dipole model cost function. 5. The method of claim 1 , wherein the dipole model cost function is configured to parameterize noise associated with the measured electrical signals. 6. The method of claim 5 , wherein the noise is parameterized in the dipole model cost function as a variance associated with the measured electrical signals. 7. The method of claim 6 , wherein the variance associated with the measured electrical signals varies depending on the known measurement locations for at least some of the measured electrical signals. 8. The method of claim 1 , further comprising computing a difference between each of the measured electrical signals with respect to a reference electrical signal at a predefined location, and wherein the dipole model cost function parameterizes an electric field of the applied signal with respect to the computed difference. 9. The method of claim 8 , wherein the predefined location is selected from one of the plurality of known measurement locations. 10. The method of claim 9 , wherein the predefined location is chosen regionally for each of the measured electrical signals according to the known measurement locations of the measured electrical signals to help compensate for effects of inhomogeneity through a volume in which the applied signal is provided. 11. The method of claim 1 , wherein determining the unknown location in the given coordinate system further comprises minimizing a difference based on the measured electrical signals and a dipole field computed for the dipole model cost function over a set of locations residing in the given coordinate system, the unknown location in the given coordinate system being determined based on the minimizing. 12. The method of claim 1 , wherein determining the unknown location in the given coordinate system further comprises implementing a Gauss-Newton method to determine the unknown location in the given coordinate system. 13. The method of claim 1 , further comprising: storing in memory the determined unknown location over a plurality of time instances that collectively define a three-dimensional path of travel; and displaying an animated output trace corresponding to the path of travel with respect to patient anatomy that is co-registered with the coordinates in space. 14. The method of claim 1 , further comprising displaying an indication of the determined unknown location in a graphical map that includes anatomical geometry. 15. The method of claim 1 , wherein the applied signal comprises a predetermined waveform that is applied from electrode disposed on a probe. 16. A method comprising: storing measurement data in memory representing measured electrical signals at each of a plurality of known locations in a given coordinate system in response to an applied signal at an unknown location in the patient's body and residing in the given coordinate system, the applied signal comprising a predetermined waveform that is distinct from anatomically generated signals, the plurality of known measurement locations comprising locations of respective electrophysiological sensors in the given coordinate system registered with respect to a patient's anatomy and used to sense the measured electrical signals, and the locations of the respective sensors comprising at least one of non-invasive locations distributed about a surface of the patient's body or invasive locations within the patient's body where the sensors have been attached; providing, to a processor communicatively coupled to the memory, a dipole model cost function having unknown parameters representing a dipole location and moment as a function of the measured electrical signals, the dipole model cost function also parameterizing noise associated with the measured electrical signals; and determining, with the processor, the unknown location in the given coordinate system, corresponding to the dipole location, based on the dipole model and the stored measurement data. 17. The method of claim 16 , wherein the noise is parameterized in the dipole model cost function as a variance representing noise associated with the measured electrical signals at each of the plurality of known locations. 18. The method of claim 17 , wherein the variance associated with the measured electrical signals has a value that varies depending on the known locations for at least some of the measured electrical signals. 19. The method of claim 16 , further comprising computing a difference between each of the measured electrical signals with respect to a reference electrical signal at a predefined location, and wherein the dipole model cost function parameterizes an electric field of the applied signal with respect to the computed difference. 20. The method of claim 19 , wherein the predefined reference location is selected either from one of the plurality of known locations or is chosen regionally for each of the measured electrical signals according to the known locations of the measured electrical signals to help compensate for effects of inhomogeneity through a volume in which the applied signal is provided. 21. The m

Assignees

Inventors

Classifications

  • Correlation of different images or relation of image positions in respect to the body · CPC title

  • Image-producing devices or illumination devices not otherwise provided for · CPC title

  • A61B5/061Primary

    Determining position of a probe within the body employing means separate from the probe, e.g. sensing internal probe position employing impedance electrodes on the surface of the body (A61B1/00158 takes precedence) · CPC title

  • G01B7/003Primary

    for measuring position, not involving coordinate determination (coordinate measuring G01B7/004) · CPC title

  • Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis · CPC title

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What does patent US10323922B2 cover?
This disclosure relates to localization and tracking of an object. As one example, measurement data can be stored in memory to represent measured electrical signals at each of a plurality of known measurement locations in a given coordinate system in response to an applied signal at an unknown location in the given coordinate system. A dipole model cost function has parameters representing a di…
Who is the assignee on this patent?
Cardioinsight Technologies Inc
What technology area does this patent fall under?
Primary CPC classification A61B5/061. Mapped technology areas include Human Necessities.
When was this patent published?
Publication date Tue Jun 18 2019 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 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).