Cardioinsight Technologies, Inc.

Viewray Technologies, Inc.

Case Western Reserve University

Qingguo Zeng

Ping Jia

Charulatha Ramanathan

Ryan M Bokan

Qing Lou

Brian P George

Venkatesh Vasudevan

Maria Strom

Timothy G Laske

Remi Dubois

Jeffrey B Adair

Connor S Edel

Kevin R Ponziani

James F Dempsey

Shmaryu M Shvartsman

John Lester Patrick

Yong Wang

Roger Nana

Meredith E Stone

Matthew J Sabo

Timothy P Eagan

Vladimir A Turovskiy

Ketal C Patel

Glenn D Raudins

Soniya Bhojwani

Rémi Dubois

Rémi DuBois

Lijun Yu

William E Rowland

Jeff Burrell

Shahabedin Shahdoostfard

Daniel Varghai

David Anthnoy Simon

Raja N Ghanem

John E Anderson

Cheng Yao

Vivek Jayan

Torsten Konrad

Richard N Lartey

Weihong Guo

Gregory Scott Brumfield

Koonlawee Nademanee

Hae Won Lim

Rahsean Ellis

Andrew E Hoover

Quin Lou

Edel S Connor

Andy E Hoover

One or more non-transitory machine-readable media to store data and instructions executable by one or more processors. The instructions are programmed to analyze workflow data for a given phase of a plurality of phases of an ongoing electrophysiology (EP) workflow implemented using a first computing apparatus. The instructions can also determine at least one support event based on the analysis of the workflow data and send a request to at least one remote support specialist responsive to determining the at least one support event. The instructions further can establish a communication link between the first computing apparatus and a second computing apparatus, which is associated with a respective remote support specialist, and enable user interaction with and control of the machine-readable EP workflow instructions on the first computing apparatus responsive to a user input by the respective remote support specialist at the second computing apparatus.

Automated triggers for electrophysiology case support

In an example, a signal segment evaluator can be programmed to evaluate a morphology of at least one electrophysiological signal to identify a signal segment of interest. The morphology of the signal segment of interest can be indicative of an electrophysiological event of a patient during a respective time interval. A reconstruction engine can be programmed to reconstruct electrophysiological signals on a surface of interest within a body of the patient based on the electrophysiological signals measured from an outer surface of the patient and geometry data representing an anatomy of the patient. A map generator can be programmed to generate a map representing the reconstructed electrophysiological signals on the surface of interest for the respective time interval of the signal segment of interest. A target generator can be programmed to identify a target site within the patient's body based on the map for the electrophysiological event.

Systems and methods for electrocardiographic mapping and target site identification

In a described example, a method includes identifying, by a processor, negative deflections of at least one unipolar signal representing cardiac electrical activity on a surface of interest during a respective interval of the at least one signal. The method also includes determining, by a processor, an activation time for a last identified negative deflection in the respective interval. The method also includes detecting, by the processor, an instance of late activation based on comparing the activation time to a temporal threshold.

Late activation of cardiac signals

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

A computer-implemented method includes storing location data for at least one invasive electrode that is movable within a patient's body. The method also includes storing electrophysiological measurement data representing the electrophysiological signals measured at the outer surface of a patient's body by body surface electrodes and within the patient's body by the at least one invasive electrode. The method also includes storing geometry data representing anatomy of the patient spatially, and locations of the respective body surface electrodes and the at least one invasive electrode in three-dimensional space. The geometry data for the at least one invasive electrode can vary based on movement of the at least one invasive electrode within the patient's body. The method also includes reconstructing electrophysiological signals on a surface of interest within the patient's body based on the electrophysiological measurement data and the geometry data.

Monitoring and analysis of invasive and non-invasive electrophysiological signals

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

A method includes placing a set of electrodes on a body surface of a patient's body. The method also includes digitizing locations for the electrodes across the body surface based on one or more image frames using range imaging and/or monoscopic imaging. The method also includes estimating locations for hidden ones of the electrodes on the body surface not visible during the range imaging and/or monoscopic imaging. The method also includes registering the location for the electrodes on the body surface with predetermined geometry information that includes the body surface and an anatomical envelope within the patient's body. The method also includes storing geometry data in non-transitory memory based on the registration to define spatial relationships between the electrodes and the anatomical envelope.

Imaging to determine electrode geometry

An example method includes establishing a communications link between an electrophysiology (EP) monitoring system and an implantable medical device (IMD). IMD electrical data is received at the monitoring system via the communications link. The IMD electrical data may be synchronized with EP measurement data to provide synchronized electrical data based on timing of a synchronization signal sensed by an IMD electrode and/or EP electrodes. The method also includes computing reconstructed electrical signals for locations on a surface of interest within the patient's body based on the synchronized electrical data and geometry data. The geometry data represents locations of the EP electrodes, a location of the IMD electrode within the patient's body and the surface of interest.

Using implantable medical devices to augment noninvasive cardiac mapping

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 for graph total variation (GTV) based reconstruction of electrical potentials on a cardiac surface are disclosed. GTV-based systems and methods incorporate information about the graph structure of the heart surface as well as imposing sparsity constraints on neighboring nodes. To this end, the present disclosure uses a novel way of calculating derivatives on irregular meshes, and provides a fast solver to compute an inverse solution more efficiently than in previous systems and methods. Moreover, fast-changing signals can be recovered with less smoothing and thus greater fidelity to the original signals.

Graph total variation for ECGI

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

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Solon, OH, United States of America

Qingguo Zeng