Cardioinsight Technologies, Inc.

Novartis Ag

Venkatesh Vasudevan

Charulatha Ramanathan

Ping Jia

Qingguo Zeng

Ryan M Bokan

Brian P George

Maria Strom

Remi Dubois

Rémi Dubois

Rémi DuBois

Brian William McDonell

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 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

Ablation therapy control based on multi-parameter graphical maps

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 method to calculate and visualize dynamic wave front propagation of electrical signals on a geometric surface is described. Wave front locations are identified on the geometric surface between each identified pair of adjacent nodes on the geometric surface. A graphical map can be generated to represent the identified wave front locations on at least a portion of the geometric surface.

Phase values and wave front detection for electrophysiological cardiac signals

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.

Composite singularity mapping

A vitrectomy surgical system includes a vitrectomy probe having a cutting portion comprising an inner tube, an outer tube, and an aspiration port. The inner tube may be movable relative to the outer tube to cut vitreous fibers. The system also includes a controller associated with the vitrectomy probe and configured to control movement of the inner tube by generating control signals corresponding to a cutting scheme including a plurality of series of cuts with each cut being evenly spaced in time, the plurality of series of cuts separated by a recovery period.

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Beachwood, OH, United States of America

Venkatesh Vasudevan