Cardioinsight Technologies, Inc.

Case Western Reserve University

Vitalxchange, Inc.

Charulatha Ramanathan

Ping Jia

Qingguo Zeng

Ryan M Bokan

Maria Strom

Brian P George

Harold Wodlinger

Venkatesh Vasudevan

Remi Dubois

Steven G Arless

Qing Lou

Jeffrey B Adair

Connor S Edel

John E Anderson

Soniya Bhojwani

Meredith E Stone

Raja N Ghanem

Yoram Rudy

Jonathan D Small

Matthew J Sabo

Harris Gasparakis

Lalita Bhetwal

Vladimir A Turovskiy

Ketal C Patel

Kevin R Ponziani

Glenn D Raudins

Rémi Dubois

Rémi DuBois

Lijun Yu

Pierre Roussel-Ragot

Jeff Burrell

Jason Grant Tilk

Lindsey Tufts, Jr

Jeffrey Silver Taggart

David L Bacon

Paul Durant, Jr

Torsten Konrad

Vivek Jayan

Cheng Yao

Andrew E Hoover

Jiyan Gardi

Edel S Connor

Andy E Hoover

Jia Ping

Gasparakis Harris

As an example, a system includes a hierarchical tag database that includes a plurality of tags arranged according to a hierarchical data schema for a number of tag hierarchies, and tags within each level of a respective tag hierarchy have a different specificity relative to each other level of the respective tag hierarchy. The data can also include profile tag data for a given user. The system can also include a processor configured to access the media and execute the instructions to expand each of the stored profile tags for the given user to provide an expanded profile tag data set for the given user, in which the expanded profile tag data set includes each of the assigned profile tags and each one or more higher-level tag in each associated tag hierarchy to which each of the assigned profile tags belongs. The instructions can also be programmed to determine which tags in the expanded profile tag data set match corresponding item tags representative of available actions, services, products and/or activities. The instructions can also be programmed to generate a results list representative of a matching set of the actions, services, products and/or activities based on the determination. At least a portion of the results list can be presented in a user-perceptible format.

Hierarchical tagging for personalized matching

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

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

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

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

System and methods for assessing heart function

Growing community of inventors

Solon, OH, United States of America

Charulatha Ramanathan