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Reducing noise of intracardiac electrocardiograms using an autoencoder and utilizing and refining intracardiac and body surface electrocardiograms using deep learning training loss functions

A loss function, noise reduction automatic coding technology, applied in the direction of medical automatic diagnosis, instrumentation, application, etc.

Pending Publication Date: 2021-12-07
BIOSENSE WEBTER (ISRAEL) LTD
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Encoding consists of performing a denoising autoencoder operation on the raw signal data to produce a latent representation

Method used

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  • Reducing noise of intracardiac electrocardiograms using an autoencoder and utilizing and refining intracardiac and body surface electrocardiograms using deep learning training loss functions
  • Reducing noise of intracardiac electrocardiograms using an autoencoder and utilizing and refining intracardiac and body surface electrocardiograms using deep learning training loss functions
  • Reducing noise of intracardiac electrocardiograms using an autoencoder and utilizing and refining intracardiac and body surface electrocardiograms using deep learning training loss functions

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Embodiment Construction

[0026] This paper discloses a system for exploiting and refining intracardiac and surface ECGs using one or more deep learning training loss functions (i.e., types of artificial intelligence and machine learning operations), generally referred to herein as training algorithm. The training algorithm for the system utilizing and refining intracardiac and surface electrocardiograms is processor executable code or software necessarily derived from the processing operations and processing hardware of the medical device equipment to provide Improved ECG and intracardiac ECG for the treatment of cardiac disorders. According to one embodiment, the training algorithm provides a specific training method for the medical device equipment and the autoencoder therein. This particular training method involves multi-step data manipulation of the electrical signal of the heart that emphasizes clinically significant regions or events within the electrical signal (eg, potential origin locations...

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Abstract

The invention discloses a system and a method. The system includes a memory storing processor executable code for a denoised autoencoder, and one or more processors coupled to the memory to execute the processor executable code to receive raw signal data comprising signal noise, encode, by the denoised autoencoder, the raw signal data by performing a denoising autoencoder operation to produce a latent representation, and decode, by the denoised autoencoder, the latent representation to produce clean signal data reconstructed without the signal noise. A first filter is applied to a signal to emphasize activity within the signal and to produce a first modified signal, a rectifier and a second filter are applied to the first modified signal to smooth areas of the first modified signal with clinical importance and to produce a second modified signal, and high frequency energy zones of the second modified signal are automatically detected using an energy threshold to produce a weights vector.

Description

[0001] Cross References to Related Applications [0002] This patent application claims U.S. Provisional Patent Application No. 63 / 034,694 (JNJBIO-6332USPSP1) filed June 4, 2020 and U.S. Provisional Patent Application No. 63 / 034,694 (JNJBIO-6368USPSP1) filed August 6, 2020 ), these patent applications are incorporated by reference as if fully set forth. technical field [0003] The present invention relates to signal processing, artificial intelligence and machine learning. More specifically, the present invention relates to systems and methods for denoising intracardiac ECGs using autoencoders and utilizing and refining intracardiac and surface ECGs using one or more deep learning training loss functions. Background technique [0004] Treatment of cardiac disorders such as cardiac arrhythmias often requires cardiac mapping (ie, mapping of cardiac tissue, chambers, veins, arteries, and / or pathways, which is also referred to as cardiac mapping). An electrocardiogram or ele...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/318A61B5/346A61B5/349A61B5/283A61B5/287
CPCA61B5/318A61B5/346A61B5/349A61B5/283A61B5/287A61B5/7203A61B5/367A61B5/7267A61B5/0022G16H50/20A61B5/725G06F18/24143G06F18/214G06F2218/04G06F2218/12
Inventor Y·A·阿摩司M·阿米特S·戈德堡L·特索夫
Owner BIOSENSE WEBTER (ISRAEL) LTD
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