Biosense Webster (israel) Ltd.

Elias Shamilov

Vladimir Rubinstein

Shiran Eliyahu

Avram Dan Montag

Limor Provizor

Konstantin Feldman

Alexander Gorovoy

Inbal Dubiner

Herman-Eyal Lencovski

A system includes a display and a processor. The processor is configured to compute multiple forecasted local activation times (LATs) at different respective locations on cardiac tissue of a subject, by simulating a propagation of a physiological activation potential along the cardiac tissue with a particular portion of the cardiac tissue, which is currently conductive, being non-conductive. The processor is further configured to generate, based on the forecasted LATs, a forecasted electroanatomical map representing a forecasted state of the cardiac tissue following an ablation of the particular portion of the cardiac tissue, and to display the forecasted electroanatomical map on the display. Other embodiments are also described.

Forecasted electroanatomical maps for ablation planning

A cardiac simulation method includes storing, in a memory, a measured electrophysiological (EP) map of at least part of wall tissue of a heart of a patient. Based on the stored EP map, simulated electrical activity in response to computer-simulated pacing, which simulates actual electrical activity that would occur across the wall tissue of the heart of the patient in response to actual pacing, is calculated in a processor. Based on the simulated electrical activity calculated in the processor, one or more candidate locations on the wall tissue of the heart at which arrhythmia is suspected of originating are identified and indicated to a user.

Simulation of heart pacing for modeling arrhythmia

A medical analysis system, includes at least one catheter to be inserted into a body-part having a tissue surface, and comprising sensing electrodes to contact and receive electrical signals from the tissue surface, and processing circuitry to receive unipolar signals from individual ones of the plurality of the sensing electrodes, compute a combined far-field and mid-field signal based on summing and filtering ones of the received unipolar signals received from at least a pair of sensing electrodes disposed around a point of interest, compute a far-field signal as a weighted average of the received unipolar signals, weighted according to respective distances of the sensing electrodes from the point of interest, and compute and output a mid-field signal, representative of electrical activity below the tissue surface at the point of interest, based on subtracting the computed far-field signal from the computed combined far-field and mid-field signal.

Mid-field signal extraction

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Eshhar, Israel

Elias Shamilov