Biosense Webster (israel) Ltd.

Biosense Webster, Inc.

Elad Nakar

Meir Bar-Tal

Natan Sharon Katz

Aharon Turgeman

Lior Botzer

Eliyahu Ravuna

Jonathan Yarnitsky

Noam Seker Gafni

Amir Ben-Dor

Refael Itah

Yaron Kadoshi

Yoav Benaroya

Leonid Zaides

Lior Greenbaum

Noga Salomon

Gal Hayam

Shmuel Auerbach

Assaf Cohen

Fady Massarwa

Fady Massarwi

Ido Ilan

Vladimir Rubinstein

Tal Haim Bar-on

Shiran Eliyahu

Goren Cohn

Sigal Altman

Michal Alroy Levy

Meytel Segev

Nir Yanovich

Natalia Etin Zait

Dor Zeev Keren Tal

Ana Kaufman

Nuno Miguel Rocha Cortez-Diaz

Amiram Ben Dor

Hadar Reuveny

Marc Wolff

Lior Zar

Dor Zeev Keren-Tal

Tal Haim Bar-On

Michal Alroy

A method includes, based on respective signals acquired by a plurality of electrodes on an anatomical surface of a heart, computing respective local activation times (LATs) at respective locations of the electrodes. The method further includes, based on the LATs, computing respective directions of electrical propagation at the locations. The method further includes selecting pairs of adjacent ones of the electrodes such that, for each of the pairs, a vector joining the pair is aligned, to within a predefined threshold degree of alignment, with the direction of electrical propagation at the location of one of the electrodes belonging to the pair. The method further includes associating respective bipolar voltages measured by the pairs of electrodes with a digital model of the anatomical surface. Other examples are also described.

Computing local propagation velocities in real-time

A method is provided. The method is implemented by a device orientation engine being executed by one or more processors. The method includes determining a movement between each electrode group of a catheter to provide movements and determining a total movement of electrodes of the catheter. The method also includes removing a standard component from the movements and the total movement and outputting a movement indication for the catheter based on the movements and the total movement with the standard component.

Signal analysis of movements of a reference electrode of a catheter in a coronary sinus vein

Systems and methods are disclosed for generating a pace-mapping prediction model. Techniques are provided that utilize a training dataset associated with biometrics of patients' hearts, including electrophysiological data associated with cardiac arrhythmia, pace-mapping datasets, and correlation data measuring the degree of correlation between the pace-mapping datasets and the electrophysiological data. Based on the training dataset, the pace-mapping prediction model is trained to predict a degree of correlation between a patient's electrophysiological data and a pace-mapping dataset. Based on the predicted degree of correlation, a cardiac location in the heart of a patient is predicted as the location for the next pace-mapping. Further systems and methods are disclosed for generating a pacing maneuver prediction model. The pacing maneuver prediction model is trained to predict interval measurement based on a pacing maneuver obtained during cardiac pace-mapping.

System and method to detect and identify cardiac pace-mapping sites and pacing maneuvers

A method includes acquiring intracardiac unipolar signals and intracardiac bipolar signals at a given region of a heart of a patient. The unipolar signals are pruned by eliminating ones of the unipolar signals that correspond in time to respective bipolar signals. One or more unipolar signals are identified among the pruned unipolar signals, that are associated with far-field P-waves. Using the identified P-waves, a window of interest (WOI) is set on electrograms acquired in an atrium of the heart, and, using the electrograms having the set WOI, an electrophysiological (EP) map is generated, of the atrium indicative of atrial tachycardia (AT) tissue locations therein.

P-wave detection using intracardiac electrodes

A system and method for detecting a mapping annotation for an electrophysiological (EP) mapping system. The system includes a processor comprising a machine learning algorithm configured to receive a first heartbeat at an identified cardiac spatial location including a first set of attributes information corresponding to the first heartbeat; receive a second heartbeat at the identified cardiac spatial location including a second set of attributes information corresponding to the second heartbeat; compare the first set of attributes information with the second set of attributes information; and determine which of the first heartbeat and the second heartbeat has optimal characteristics based on the compared attribute information.

System and method to detect stable arrhythmia heartbeat and to calculate and detect cardiac mapping annotations

A method, including receiving a unipolar ECG signal from the location in the heart from a selected one electrode of a pair of electrodes, computing a local unipolar minimum derivative of the unipolar signal at a plurality of times of occurrences of the local unipolar minimum derivative, identifying candidate time of occurrences of the plurality of times of occurrences of the local unipolar minimum derivative as candidate annotations of the time of activation of the myocardium, extracting features for each of the candidate annotations, assigning a confidence level based on a feature value for each of the candidate annotations, eliminating candidate annotations that have a confidence level below a threshold and generating a local activation time map using the remaining candidate annotations.

Annotation of an electrocardiogramic wavefront

In an example, a method includes receiving a cardiac signal that is sensed by an electrode at a tissue location inside the heart. Fractionations are identified in the cardiac signal. The fractionations identified at the tissue location are compared between first and second cardiac cycles of the cardiac signal. Based on the comparing, a likelihood is estimated, that the tissue location is causing a stable arrhythmia. Based on the estimated likelihood, the tissue location is indicated to a user as likely to be causing the stable arrhythmia.

Detection of fractionated signals in stable arrhythmias

A method including processing electrocardiograph (ECG) signals taken over a heartbeat received over a plurality of channels, selecting a subset of the ECG signals captured at a point in time with a window of interest (WOI) around reference annotations and having a morphology pattern within the WOI, storing the morphology patterns, receiving continuous sets of ECG signals taken over a plurality of heartbeats over the plurality of channels and having a morphology pattern within the WOI, performing a correlation between the stored morphology patterns of the ECH signals and the morphology patterns of the continuous sets of ECH signals for each heartbeat, generating a correlation coefficient that is a measure of a goodness of fit between geometries of the ECG signals and the continuous sets of ECG signals and identifying each heartbeat having a correlation coefficient that exceeds a threshold coefficient as having been caused by an arrhythmia.

Identifying ECG signals having the same morphology

An apparatus includes a shaft, configured for insertion into a body of a subject, and an expandable element coupled to a distal end of the shaft. The expandable element includes multiple electrodes arranged in a hexagonal grid when the expandable element is expanded. Other embodiments are also described.

Staggered electrode arrangements for electrophysiological sensing

In one embodiment, a medical system includes respective electrodes for application to a body of a subject and to output a set of respective activation signals in response to electrical activity of a heart of the subject captured over a sequence of heartbeat intervals, and a processor to classify a first heartbeat interval of the set of activation signals as a first morphological template, compute a measure of similarity between a second heartbeat interval of the set of activation signals and the first morphological template, group the second heartbeat interval of the set of activation signals in a first morphological group with the first morphological template responsively to the measure exceeding a predefined threshold, and classify the second heartbeat interval of the set of activation signals as a second morphological template responsively to the measure not exceeding the predefined threshold, and repeat the above, mutatis mutandis, for subsequent heartbeat intervals.

Automatic pattern acquisition

A method, including receiving a bipolar signal from a pair of electrodes in proximity to a myocardium of a human subject, and receiving a unipolar signal from a selected one of the pair of electrodes. The method further includes delineating a window of interest (WOI) for the unipolar and bipolar signals, within the WOI computing local unipolar minimum derivatives of the unipolar signal, and times of occurrence of the local unipolar minimum derivatives, and within the WOI computing bipolar derivatives of the bipolar signal at the times of occurrence. The method also includes evaluating ratios of the bipolar derivatives to the local unipolar minimum derivatives, and when the ratios are greater than a preset threshold ratio value, assigning the times of occurrence as times of activation of the myocardium, counting a number of the times of activation; and classifying the unipolar signal according to the number.

Classifying ECG signals

A method includes receiving a bipolar signal sensed by a pair of electrodes at a location in a heart of a patient. One or more electrocardiogram (ECG) signals are received, sensed by body-surface electrodes attached to the patient. Two or more successive QRS complexes are identified in the bipolar signal. One or more activations are detected in the bipolar signal, which occur within a window-of-interest that begins at least a given time with respect to the identified QRS complexes. The detected activations are checked whether they are late potentials, by verifying whether (i) the activations do not coincide with a predefined event observed in the ECG signals, and (ii) the activations are repeatable in the successive QRS complexes. In response to deciding that at least one of the detected activations is a late potential, the latest of the at least one of the late potentials is visualized to a user.

Annotation of late potentials comprising local abnormal ventricular activation (LAVA) signals

Methods, apparatus, and systems for medical procedures are disclosed herein and include detecting points of an intra-cardiac area that exhibits abnormal activations, such as local abnormal ventricular activations (LAVAs). Points that exhibit such abnormal activations may be referred to as seed points that are identified during a first step of the process disclosed herein. The seed points may be identified using one or more inputs such as unipolar and bipolar mapping channels, body surface ECGs, past activations, neighboring points and the like during the first step which prioritizes high specificity over sensitivity. During a second step which prioritizes high sensitivity, electrical activations of neighboring points near the seed points are analyzed to determine if the activations are similar (e.g., have a similar time) as the abnormal activations corresponding to the corresponding seed points.

Method and apparatus to find abnormal activations in intra-cardiac electrocardiograms based on specificity and sensitivity

Acquiring ECG signals from electrodes positioned in a heart taken over a single heartbeat, selecting a morphology pattern within a window of interest around time of occurrence annotations for the signals; computing a weighted cross-correlation between each morphology pattern of the signals and a stored template morphology pattern, to generate a weighted correlation coefficient of a match between the morphology patterns of the acquired signals and the stored morphology pattern; iteratively changing a phase of the signals relative to the phase of the morphology pattern and repeating the step of generating the weighted correlation coefficient at each iteration; determining a maximum value of the weighted correlation coefficient based on the iterations; comparing the maximum value to a threshold; and when the maximum value exceeds the threshold, accepting the heartbeat as having been caused by the arrhythmia and incorporating a location of the arrhythmia into a local activation map.

A method, including receiving a bipolar ECG signal from a location in the heart from the pair of electrodes, receiving a unipolar ECG signal from the location in the heart from a selected one electrode of the pair of electrodes, computing a local unipolar minimum derivative of the unipolar signal at a plurality of times of occurrences of the local unipolar minimum derivative, computing a bipolar derivative of the bipolar signal, evaluating a ratio of the bipolar derivative to the local unipolar minimum derivative at the plurality of times of occurrences of the local unipolar minimum derivative, annotating each time of occurrence as a time of activation of the myocardium at the location in the heart when the ratio is greater than a preset threshold value, merging two annotations that arise from a single occurrence as a single annotation, evaluating features of the annotations and assigning a confidence level to each feature, eliminating annotations that have a confidence level below a threshold and generating a local activation time map using the remaining annotations.

Growing community of inventors

Timrat, Israel

Elad Nakar