Cardioinsight Technologies, Inc.

Brian P George

Charulatha Ramanathan

Ping Jia

Qingguo Zeng

Ryan M Bokan

Maria Strom

Venkatesh Vasudevan

Qing Lou

Remi Dubois

Harold Wodlinger

Jeffrey B Adair

Kevin R Ponziani

Connor S Edel

Meredith E Stone

Lalita Bhetwal

Jonathan D Small

Matthew J Sabo

Vladimir A Turovskiy

Ketal C Patel

Soniya Bhojwani

Rémi Dubois

Lijun Yu

Jeff Burrell

Shahabedin Shahdoostfard

Daniel Varghai

Pierre Roussel-Ragot

Timothy G Laske

Raja N Ghanem

John E Anderson

Rémi DuBois

Rahsean Ellis

Andrew E Hoover

Cheng Yao

Edel S Connor

Andy E Hoover

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

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 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

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.

For example, one or more non-transitory computer-readable media includes executable instructions to perform a method. The method includes defining a plurality of spatial regions distributed across a geometric surface. At least one wave front that propagates across the geometric surface is detected based on electrical data representing electrophysiological signals for each of a plurality of nodes distributed on the geometric surface over at least one time interval. An indication of conduction velocity of the wave front is determined for at least one spatial region of the plurality of spatial regions during the time interval based on a duration that the wave front resides within the at least one spatial region. Slow conduction activity is identified for the at least one spatial region based on comparing the indication of conduction velocity relative to a threshold. Conduction data is stored in memory to represent each slow conduction event.

Detection of regions exhibiting irregular electrophysiological activity

An example method includes performing amplitude-based detection to determine location of R-peaks for a plurality of electrograms. The method also includes performing wavelet-based detection to determine location of R-peaks for the plurality of electrograms. The method also includes adjusting the location of the R-peaks determined by the wavelet-based detection of R-peaks based on the location of R-peaks determined by the amplitude-based detection of R-peaks. The method also includes storing, in memory, R-peak location data to specify R-peak locations for the plurality of electrograms based on the adjusting.

Detection and analysis of cardiac waveforms

A non-transitory computer-readable medium can have instructions executable by a processor. The instructions can include an electrogram reconstruction method to generate reconstructed electrogram signals for each of a multitude of points residing on or near a predetermined cardiac envelope based on geometry data and non-invasively measured body surface electrical signals. The instructions can include a phase calculator to compute phase signals for the multitude of points based on the reconstructed electrogram signals and a visualization engine to generate an output based on the computed phase signals.

Physiological mapping for arrhythmia

Systems and methods are provided to detect and analyze arrhythmia drivers. In one example, a system can include a wave front analyzer programmed to compute wave front lines extending over a surface for each of the plurality of time samples based on phase information computed from electrical data at nodes distributed across the surface. A trajectory detector can be programmed to compute wave break points for each of the wave front lines and to determine a trajectory of at least one rotor core across the surface. A stability detector can be programmed to identify at least one stable rotor portion corresponding to subtrajectories of the determined trajectory.

Analysis and detection for arrhythmia drivers

A computer-implemented method can include determining an amplitude for each of a plurality of input channels, corresponding to respective nodes. A measure of similarity can be computed between the input channel of each node and the input channel of its neighboring nodes. The method can also include comparing an amplitude for each node relative to other nodes to determine temporary bad channels. For each of the temporary bad channels, a measure of similarity can be computed between the input channel of each node and the input channel of its neighboring nodes. Channel integrity can then be identified based on the computed measures of similarity.

Channel integrity detection

A method can determine one or more origins of focal activation. The method can include computing phase for the electrical signals at a plurality of nodes distributed across a geometric surface based on the electrical data across time. The method can determine whether or not a given candidate node of the plurality of nodes is a focal point based on the analyzing the computed phase and magnitude of the given candidate node. A graphical map can be generated to visualize focal points detected on the geometric surface.

Focal point identification and mapping

A method can include storing a plurality of data sets including values computed for each of a plurality of points for a given spatial region of tissue, the values in each of the data sets characterizing electrical information for each respective point of the plurality of points for a different time interval. The method can also include combining the values computed for each of a plurality of points in a first interval, corresponding to a first map, with the values for computed for each of the respective plurality of points in another interval and to normalize the combined values relative to a common scale. The method can also include generating a composite map for the given spatial region based on the combined values that are normalized.

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Cleveland, OH, United States of America

Brian P George