Cardioinsight Technologies, Inc.

Case Western Reserve University

Washington University

Ping Jia

Charulatha Ramanathan

Qingguo Zeng

Ryan M Bokan

Maria Strom

Brian P George

Venkatesh Vasudevan

Harold Wodlinger

Qing Lou

Remi Dubois

Steven G Arless

Jeffrey B Adair

Connor S Edel

Raja N Ghanem

Yong Wang

Yoram Rudy

Kevin R Ponziani

Meredith E Stone

John E Anderson

Soniya Bhojwani

Jonathan D Small

Matthew J Sabo

Lalita Bhetwal

Ketal C Patel

Vladimir A Turovskiy

Timothy G Laske

Harris Gasparakis

Rémi DuBois

Rémi Dubois

Jeff Burrell

Daniel Varghai

Shahabedin Shahdoostfard

Lijun Yu

Cheng Yao

Andrew E Hoover

Rahsean Ellis

Vivek Jayan

Torsten Konrad

Rudy Yoram

Edel S Connor

Andy E Hoover

Gasparakis Harris

This disclosure provides one or more computer-readable media having computer-executable instructions for performing a method. The method includes storing geometry data representing a primary geometry of a cardiac envelope that includes nodes distributed across the cardiac envelope and geometry of a body surface that includes locations where electrical signals are measured. The body surface is spaced apart from the cardiac envelope. The method also includes perturbing the primary geometry of the cardiac envelope a given distance and direction to define the perturbed geometry of the cardiac envelope including nodes spaced from the nodes of the primary geometry. The method also includes computing reconstructed bipolar electrical signals on the nodes of the primary cardiac envelope based on the electrical signals measured from the body surface and the geometry data, including the primary and perturbed geometries of the cardiac envelope.

Determining bipolar electrical activity

This disclosure relates to integrated channel integrity detection and to reconstruction of electrophysiological signals. An example system includes a input channels configured to receive respective electrical signals from respective electrodes. An amplifier stage includes a plurality of differential amplifiers, each of the differential amplifiers being configured to provide an amplifier output signal based on a difference between a respective pair of the electrical signals. Channel detection logic is configured to provide channel data indicating an acceptability of each of the input channels based on an analysis of a common mode rejection of the amplifier output signals.

Channel integrity detection and reconstruction of electrophysiological signals

A map generator can be programmed to generate a multi-parameter graphical map by encoding at least two different physiological parameters for a geometric surface, corresponding to tissue of a patient, using different color components of a multi-dimensional color model such that each of the different physiological parameters is encoded by at least one of the different color components.

Multi-parameter physiological mapping to a multi-dimensional color model

Systems and methods are disclosed to determine one or more sensing zones on a body surface for electrocardiographic mapping of a region of interest associated with the heart. The sensing zone can be utilized to facilitate acquisition, processing and mapping of electrical activity for the corresponding region of interest. In other examples, an application-specific arrangement of electrodes can also be provided based on the sensing zone that is determined for the region of interest.

Sensing zone for spatially relevant electrical information

An example method includes applying a localization signal to a source electrode positioned within a conductive volume and a ground electrode at a known location. Electrical activity is sensed at a plurality of sensor electrodes distributed across an outer surface of the conductive volume. The locations of each of the sensor electrodes and the location of the ground electrode being stored in memory as part of geometry data. The electrical activity sensed at each of the sensor electrodes is stored in the memory as electrical measurement data. The method also includes computing a location of the source electrode by minimizing a difference between respective pairs of source voltages determined for the plurality of sensor electrodes. The source voltage for each of the sensor electrodes is determined based on the electrical measurement data and the geometry data.

Localization of objects within a conductive volume

Systems and methods can be used to provide an indication of heart function, such as an indication of mechanical function or hemodynamics of the heart, based on electrical data. For example, a method for assessing a function of the heart can include determining a time-based electrical characteristic for a plurality of points distributed across a spatial region of the heart. The plurality of points can be grouped into at least two subsets of points based on at least one of a spatial location for the plurality of points or the time-based electrical characteristics for the plurality of points. An indication of synchrony for the heart can be quantified based on relative analysis of the determined time-based electrical characteristic for each of the at least two subsets of points.

Systems and methods for assessing heart function

A method can include storing input electrical signal data representing at least a given electrophysiological signal acquired from a patient. A non-local mean filter can be applied to the given electrophysiological signal, the non-local mean filter including a spatial filter component and an intensity filter component. The method can also include controlling parameters to establish weighting of each of the spatial filter component and the intensity filter component in response to a control input. Filtered signal data can be stored based on the applying and the controlling.

Non-local mean filtering for electrophysiological signals

An example method includes analyzing morphology and/or amplitude of each of a plurality of electrophysiological signals across a surface of a patient's body to identify candidate segments of each signal satisfying predetermined conduction pattern criteria. The method also includes determining a conduction timing parameter for each candidate segment in each of the electrophysiological signals.

Detecting conduction timing

Systems and methods for cardiac fast firing (e.g., atrial fast firing) detection perform frequency analysis on channels of collected cardiac waveform data and test the data for outlier frequency complex content that is of higher frequency than baseline frequency complex content associated with cardiac fibrillation (e.g., atrial fibrillation) or other arrhythmogenic activity. Anatomical regions from whence the cardiac fast firing originates can be displayed in real time on an epicardial surface map via a graphical display, aiding administration of therapy. Prior to such detection, QRST complex removal can be performed to ensure that ventricular activity does not infect the atrial fast firing analysis. A frequency-based method for QRST complex removal is also disclosed.

Detection and localization of cardiac fast firing

In an example, an n-dimensional method of fundamental solution (MFS) is used to compute reconstructed electrical activity on a cardiac envelope based on geometry data and electrical data, where n is a positive integer greater than three. The electrical data represents electrical activity measured non-invasively from a plurality of locations distributed on a body surface of a patient, and the geometry data represents three-dimensional body surface geometry for the locations distributed on the body surface where the electrical activity is measured and three-dimensional heart geometry for the cardiac envelope.

Multi-dimensional method of fundamental solutions for reconstruction of electrophysiological activity

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.

Localization and tracking of an object

This disclosure relates to integrated channel integrity detection and to reconstruction of electrophysiological signals. An example system includes a plurality of input channels configured to receive respective electrical signals from a set of electrodes. An amplifier stage includes a plurality of differential amplifiers, each of the differential amplifiers being configured to provide an amplifier output signal based on a difference between a respective pair of the electrical signals. Channel detection logic is configured to provide channel data indicating an acceptability of each of the plurality of input channels based on an analysis of a common mode rejection of the amplifier output signals.

One or more non-transitory computer-readable media have instructions executable by a processor and programmed to perform a method. The method includes analyzing the electrical data to locate one or more wave front lines over a given time interval. The electrical data represents electrophysiological signals distributed across a cardiac envelope for one or more time intervals. A respective trajectory is determined for each wave end of each wave front line that is located across the cardiac envelope over the given time interval. A set of connected trajectories are identified based on a duration that the trajectories are connected to each other by a respective wave front line during the given time interval. A connectivity association is characterized for the trajectories in the set of connected trajectories.

Connectivity analysis for arrhythmia drivers

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Solon, OH, United States of America

Ping Jia