Method for constructing intracardiac abnormal activation point location model based on CNN and LSTM

    公开(公告)号:US12097036B2

    公开(公告)日:2024-09-24

    申请号:US17618495

    申请日:2019-12-20

    Abstract: The present invention discloses a method for constructing an intracardiac abnormal activation point location model based on CNN and LSTM. The model can well locate specific locations of abnormal activation points of VT and obtain three-dimensional coordinates of the locations, while obtaining 12-lead body surface potential data of a patient. The method introduces an idea of deep learning into locating of the abnormal activation points of ventricular tachycardia, uses collected QRS data as an input in a training phase, as well as three-dimensional coordinates of the QRS data corresponding to mapping points as a label to train a CNN-LSTM network, utilizes Conv1D to extract features from the input data, employs LSTM for feature fusion in a time domain, and exploits fully connected layers for regression prediction of the three-dimensional coordinates to finally construct the CNN-LSTM network. The network model of the present invention achieves prediction of the locations of the abnormal activation points of VT from a perspective of data drive, thus effectively solving a problem that clinical catheter ablation time consuming and laborious.

    Method and system for calculating conduction velocity of a cardiac activation wavefront

    公开(公告)号:US11950918B1

    公开(公告)日:2024-04-09

    申请号:US17339997

    申请日:2021-06-05

    Applicant: Neucures Inc.

    CPC classification number: A61B5/367 A61B5/333

    Abstract: A method for calculating conduction velocity of a cardiac activation wavefront from electrophysiological (“EP”) data points generated by a mapping system during a mapping procedure for a heart is provided. The method comprises for each EP data point comprising a local activation time, and position data defining a location within the heart corresponding to the local activation time: defining a neighborhood of EP points comprising the EP data point and a selection of neighboring EP data points; representing local activation time as a function f(x,y), where x and y our coordinates within a hyperplane defined to contain the neighborhood of EP data points based on the position data for each EP data point in the neighborhood; and calculating conduction velocity at the EP data point as a norm function of a gradient for the function f(x,y).

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