Biosense Webster (Israel) Ltd.

Biosense Webster, Inc.

Eliyahu Ravuna

Elad Nakar

Lior Botzer

Assaf Govari

Natan Sharon Katz

Dean M Ponzi

Shmuel Auerbach

Itamar Bustan

Tamir Avraham Yellin

Refael Itah

Eden Kidishman

Leonid Zaides

Jonathan Yarnitsky

Eid Adawi

Tal Haim Bar-on

Yoav Benaroya

Yaron Kadoshi

Nakdimon Nissim Levy

Aharon Turgeman

Benjamin Cohen

Gal Hayam

Assaf Cohen

Fady Massarwa

Fady Massarwi

Shiran Eliyahu

Matityahu Amit

Stanislav Goldberg

Goren Cohn

Yariv Avraham Amos

Michael Maydel

Lior Greenbaum

Ana Kaufman

Alon Ben Natan

Guy Wekselman

Michal Alroy Levy

Elad Azaria

Hue Nguyen

Or Yaacobovich

Iyar Rom

Aleksey Vladimirovich Shovkun

Natalia Etin Zait

Nir Yanovich

Meytel Segev

Netta Dov

Simon Rivron

Roey Lehman

Yochai Alon Timmer

Nuno Miguel Rocha Cortez-Diaz

Elena Igorevna Kuzhnareva

Andrey Evgenyevich Kiryasov

Hadar Reuveny

Marc Wolff

Schmuel Cohen

Lior Zar

Shlomo Am-Shalem

Tal Haim Bar-On

Michal Alroy

A method includes receiving a plurality of data points including electrical activation (EA) values measured at respective positions in at least a portion of a surface of a cardiac chamber of a heart of a patient. Using a predefined EA value criterion, the EA values in a given region of the cardiac surface are classified into multiple distinct EA wave-fronts, and multiple layers of EA values are calculated for the given region, wherein each EA layer includes the EA values found to belong to a respective and contiguous EA wave-front. The multiple EA layers are overlayed on a graphical representation of the surface. The graphical representation with the multiple overlaid EA layers is displayed to a user, with a graphical indication distinguishing between the multiple EA layers.

Layered multi-activation local activation times (LAT) mapping

A medical device includes a QR generator and a user access/activity log. The QR generator generates a QR code at least from a username of a user and at least one OTP (one-time password) for the user and enables access of the user to the medical device upon receiving an OTP from the user. The user sends the QR code to an online authorization server for the medical device for decryption upon authentication of the user. The log lists user activity once the user is authenticated by the server. The server receives the QR code, which includes at least an encrypted text containing at least the OTP and a user identification, and decrypts the encrypted text using a private key associated with the medical device. The authorization server enables the user to log in for authentication and, if authenticated, displays the at least one OTP to the user.

Online authentication for medical devices

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

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 positioning an expandable balloon, coupled to a distal end of a catheter, at a target location within an organ of a patient, the expandable balloon including multiple electrodes and one or more sensors in proximity to each electrode, wherein the one or more sensors are configured each to measure a characteristic of blood. The expandable balloon is expanded at the target location. A fluid is flowed through an inner lumen of the catheter and into the blood in a vicinity of each electrode. A dependence of the characteristic of blood on time is measured, via the one or more sensors, in proximity to each electrode. Using a processor, it is determined whether or not each electrode is in physical contact with tissue, based on the measured dependence of the characteristic of blood. An indication of whether or not each electrode is in physical contact with tissue is outputted to a user.

Touch indication of balloon-catheter ablation electrode via balloon surface temperature measurement

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

In one embodiment, a system includes a catheter, at least one position sensor to provide position signal(s) indicative of a position of a distal end of the catheter over time, a first smoothing filter to provide first filtered position signal(s) responsively to the position signal(s) and a first filtering level, a second smoothing filter to provide second filtered position signal(s) responsively to the position signal(s) and a second filtering level, wherein the second filtering level provides more smoothing than the first filtering level, and processing circuitry to find first and second position coordinates of the distal end responsively to the first and second filtered position signal(s), respectively, generate, and render to a display, an anatomical map of a body part responsively to the second position coordinates, and render a representation of the distal end to the display while showing movement of the distal end responsively to the first position coordinates.

Reducing perceived latency of catheters

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 catheter is disclosed comprising: a connector including a plurality of first contacts and one or more second contacts; a shaft including a plurality of electrodes, each electrode being coupled to a different one of the plurality of first contacts; a memory coupled to at least one of the second contacts, wherein the memory is configured to: store a pinout map identifying an order in which the plurality of electrodes is coupled to the plurality of first contacts; and provide the pinout map to an external device via one or more of the second contacts after the connector is coupled to the external device.

Random pinout catheter

A method includes collecting a plurality of bipolar electrograms and respective unipolar electrograms of patients, the electrograms including annotations in which one or more human reviewers have identified and marked a window-of-interest and one or more activation times inside the window-of-interest. A ground truth data set is generated from the electrograms, for training at least one electrogram-preprocessing step of a Machine Learning (ML) algorithm. The ML algorithm is applied to the electrograms, to at least train the at least one electrogram-preprocessing step, so as to detect an occurrence of an activation in a given bipolar electrogram within the window-of-interest.

Detection of activation in electrograms using neural-network-trained preprocessing of intracardiac electrograms

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

A system, device and method for left atrial appendage occlusion detection is disclosed. The system for occlusion detection comprises a sheath; a delivery system comprising: a delivery catheter extending between a proximal end and a distal end; and a handle coupled to the proximal end of the delivery catheter; a medical tool coupled to a distal end of the delivery catheter at a target location within a portion of an organ of a patient, the medical device comprising a hub including a bore defining an axis, an occluder portion coupled to the hub and an anchor portion extending between a first end and a second end; at least one pressure sensor configured to measure a pressure of the target cavity while blood is suctioned form inside the left atrial appendage; and at least one processor configured to process the pressure measurement acquired from the at least one pressure sensor.

Occlusion detection by pressure measurement

A method includes receiving an anatomical map of at least a portion of a heart. Positions and respective bipolar intracardiac electrogram (EGM) signals measured at the positions are received for at least a region of the anatomical map. Primary activations and secondary activations are identified in the bipolar intracardiac EGM signals. A surface representation of the bipolar intracardiac EGM signals over the region is derived, including the identified primary activations and secondary activations. The surface representation is presented overlaid on the anatomical map.

Visually differentiating primary and secondary activations on electrophysiological maps

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Kiryat Ata, Israel

Eliyahu Ravuna