Cardioinsight Technologies, Inc.

Connor S Edel

Ping Jia

Qingguo Zeng

Ryan M Bokan

Qing Lou

Charulatha Ramanathan

Brian P George

Jeffrey B Adair

Meredith E Stone

Matthew J Sabo

Vladimir A Turovskiy

Ketal C Patel

Kevin R Ponziani

Timothy G Laske

Raja N Ghanem

John E Anderson

Andrew E Hoover

Cheng Yao

Rahsean Ellis

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

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

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

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Independence, OH, United States of America

Connor S Edel