Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method for visualization of electrophysiology information can include storing electroanatomic data in memory, the electroanatomic data representing electrical activity on an anatomic region within a patient's body over a time period. An interval within the time period is selected in response to a user selection. A visual representation of physiological information for the user selected interval can be generated by applying at least one analysis method to the electroanatomic data. The visual representation can spatially represented on a graphical representation of the anatomic region within the patient's body.

Abstract: A method for visualization of electrophysiology information can include storing electroanatomic data in memory, the electroanatomic data representing electrical activity on an anatomic region within a patient's body over a time period. An interval within the time period is selected in response to a user selection. A visual representation of physiological information for the user selected interval can be generated by applying at least one analysis method to the electroanatomic data. The visual representation can spatially represented on a graphical representation of the anatomic region within the patient's body.

Abstract: A method for visualization of electrophysiology information can include storing electroanatomic data (14) in memory, the electroanatomic data representing electrical activity on a surface of an organ over a time period. An interval within the time period is selected in response to a user selection (28). Responsive to the user selection of the interval, a visual representation (26) of physiological information for the user selected interval is generated by applying at least one method to the electroanatomic data (14). The visual representation (26) is spatially represented on a graphical representation of a predetermined region of the surface of the organ.

Abstract: A method for visualization of electrophysiology information can include storing electroanatomic data (14) in memory, the electroanatomic data representing electrical activity on a surface of an organ over a time period. An interval within the time period is selected in response to a user selection (28). Responsive to the user selection of the interval, a visual representation (26) of physiological information for the user selected interval is generated by applying at least one method to the electroanatomic data (14). The visual representation (26) is spatially represented on a graphical representation of a predetermined region of the surface of the organ.