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Arrhythmia detection method and device and storage medium

A technology of arrhythmia and storage media, applied in diagnostic recording/measurement, medical science, diagnosis, etc., can solve problems that have not been proposed, the accuracy of the algorithm is not satisfactory, and affect the accuracy of the arrhythmia detection algorithm, so as to avoid the impact , the effect of improving the accuracy

Pending Publication Date: 2020-04-28
刘堃 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing automatic arrhythmia identification algorithm based on feature extraction needs to directly or indirectly identify the waveform features of different stages of each heartbeat cycle in the ECG signal, and identify the complex interrelationship between them over time
Since each person's ECG waveform has different shapes, and the collection scene of single-lead ECG data is different from that of medical institutions, there are more interferences and uncertainties, which makes the accuracy of existing algorithms unsatisfactory.
[0004] In view of the uncertainty in the ECG waveforms of different groups of people in the above-mentioned prior art, therefore, no effective solution has been proposed for the technical problems that affect the accuracy of the arrhythmia detection algorithm.

Method used

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  • Arrhythmia detection method and device and storage medium

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Embodiment 1

[0021] According to this embodiment, an embodiment of a method for detecting arrhythmia is provided. It should be noted that the steps shown in the flow charts of the drawings can be executed in a computer system such as a set of computer-executable instructions, and, Although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

[0022] The method embodiments provided in this embodiment can be executed in mobile terminals, computer terminals, servers or similar computing devices. figure 1 A block diagram of a hardware structure of a computing device for implementing a method for detecting arrhythmia is shown. Such as figure 1 As shown, the computing device may include one or more processors (processors may include but not limited to processing devices such as microprocessors MCUs or programmable logic devices FPGAs), memory for storing data, and memory for communicat...

Embodiment 2

[0053] Figure 5 The apparatus 500 for detecting arrhythmia according to this embodiment is shown, and the apparatus 500 corresponds to the method according to the first aspect of Embodiment 1. refer to Figure 5 As shown, the device 500 includes: a data acquisition module 510, used to acquire the ECG data of the object to be detected; an identification module 520, used to identify the ECG data through a preset neural network model, and generate a The identification result of the arrhythmia type of the object; and the abnormality determination module 530, configured to determine the arrhythmia of the object to be detected according to the identification result.

[0054] Optionally, the identification module 520 includes: an identification sub-module, configured to identify the ECG data through a plurality of neural network models respectively used to identify different types of arrhythmias, and generate different heart rhythms respectively used to identify the object to be de...

Embodiment 3

[0062] Figure 6 The apparatus 600 for detecting arrhythmia according to this embodiment is shown, and the apparatus 600 corresponds to the method according to the first aspect of Embodiment 1. refer to Figure 6 As shown, the device 600 includes: a processor 610; and a memory 620, connected to the processor 610, for providing the processor 610 with instructions for processing the following processing steps: acquiring the ECG data of the subject to be detected; The network model identifies the electrocardiographic data, generates a recognition result for identifying the arrhythmia type of the object to be detected; and determines the arrhythmia of the object to be detected according to the recognition result.

[0063] Optionally, using a preset neural network model to identify the ECG data, generating a recognition result for identifying the type of arrhythmia of the object to be detected, including: using multiple neural networks for identifying different types of arrhythmia...

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Abstract

The invention discloses an arrhythmia detection method and device and a storage medium. The method comprises the following steps: acquiring electrocardiogram data of a to-be-detected object; identifying the electrocardiogram data through a preset neural network model, and generating an identification result for identifying the arrhythmia type of the to-be-detected object; and determining the arrhythmia condition of the to-be-detected object according to the identifying result. The invention solves the technical problem that the accuracy of an arrhythmia detection algorithm is affected due to the fact that the electrocardio waveforms of different people are different and have uncertainty in the prior art.

Description

technical field [0001] The present application relates to the technical field of computer artificial intelligence, in particular to a method, device and storage medium for detecting arrhythmia. Background technique [0002] The traditional arrhythmia detection method uses a multi-lead electrocardiogram, and the doctor makes a diagnosis based on the image results of the electrocardiogram and his own medical experience. Some medical institutions have launched remote ECG diagnosis services. Users can use multi-lead ECG machines at home to collect ECG data, upload them to the remote diagnosis platform, and then analyze the ECG by doctors or machine algorithms. With the popularity of smart portable devices, single-lead ECG data has been more widely used due to its easy-to-acquire characteristics. Correspondingly, the automatic ECG analysis algorithm for single-lead ECG data has also been further developed. [0003] The existing single-lead arrhythmia automatic identification al...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0245A61B5/0452
CPCA61B5/0245A61B5/35A61B5/349
Inventor 卢欣晔刘堃
Owner 刘堃