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Arrhythmia detection method and system

A technology for arrhythmia and detection methods, applied in diagnostic recording/measurement, medical science, sensors, etc., can solve problems such as unreliability, difficulty in model training, inconsistent public data labeling standards, etc., and achieve the effect of improving accuracy

Pending Publication Date: 2021-11-05
济南汇医融工科技有限公司
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  • Claims
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AI Technical Summary

Problems solved by technology

[0004] A large number of existing electrocardiograms are directly collected without expert labeling data, and the public data labeled by experts also has inconsistent labeling standards. It is difficult to directly perform model training on ECG data from multiple databases using supervised learning algorithms, resulting in arrhythmia detection. results are inaccurate and unreliable

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  • Arrhythmia detection method and system
  • Arrhythmia detection method and system
  • Arrhythmia detection method and system

Examples

Experimental program
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Effect test

Embodiment 1

[0042] Embodiment 1 provides a system for detecting arrhythmia, which includes:

[0043] An acquisition module, configured to acquire the original ECG signal to be detected;

[0044] The preprocessing module is used to preprocess the original ECG signal to obtain time-series ECG signals and Hilbert spectrograms respectively;

[0045] The extraction module is used to extract the time-series electrocardiographic signal feature and the Hilbert spectrum feature respectively based on the time-series electrocardiogram signal and the Hilbert spectrum;

[0046] The detection module is used to use the trained detection model to process the time-series ECG signal features and Hilbert spectrum features to obtain the final detection result; wherein, the detection result includes whether the original ECG signal to be detected is arrhythmia Signal.

[0047] In the present embodiment 1, a kind of arrhythmia detection method is realized by using the above-mentioned arrhythmia detection syst...

Embodiment 2

[0060] Embodiment 2 provides an arrhythmia detection system, which includes:

[0061] An acquisition module, configured to acquire the original ECG signal to be detected;

[0062] The preprocessing module is used to preprocess the original ECG signal to obtain time-series ECG signals and Hilbert spectrograms respectively;

[0063] The extraction module is used to extract the time-series electrocardiographic signal feature and the Hilbert spectrum feature respectively based on the time-series electrocardiogram signal and the Hilbert spectrum;

[0064] The detection module is used to use the trained detection model to process the time-series ECG signal features and Hilbert spectrum features to obtain the final detection result; wherein, the detection result includes whether the original ECG signal to be detected is arrhythmia Signal.

[0065] In this embodiment 2, a kind of arrhythmia detection method is realized by utilizing the arrhythmia detection system as described above,...

Embodiment 3

[0134] like figure 1As shown, in the present embodiment 3, a kind of arrhythmia detection and screening system based on contrast learning is provided, and this system comprises: ECG signal acquisition module, ECG signal preprocessing module, contrast learning module and evaluation module, ECG signal The acquisition module is connected with the ECG signal preprocessing module, and the two channels of data output by the preprocessing module are respectively sent to the corresponding two sub-modules in the comparison learning module, and the pre-training model and the labeled data generated after the comparison learning model is trained Combined to train a supervised model for clinical needs.

[0135] The ECG signal acquisition module is used to filter and denoise the original ECG signal; the ECG signal preprocessing module is used to normalize the collected ECG signal, and then output one ECG time series and another One ECG signal Hilbert spectrogram; Contrastive Predictive Cod...

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Abstract

The invention provides an arrhythmia detection method and system, and belongs to the technical field of heart rhythm detection equipment, and the method comprises the steps: obtaining a to-be-detected original electrocardiosignal; preprocessing the original electrocardiosignal to obtain a time sequence electrocardiosignal and a Hilbert spectrogram respectively; extracting time sequence electrocardiosignal features and Hilbert spectrum features respectively based on the time sequence electrocardiosignal and the Hilbert spectrogram; using a trained detection model for processing the time sequence electrocardiosignal features and the Hilbert spectrum features, and obtaining a final detection result; wherein the detection result comprises whether the to-be-detected original electrocardiosignal is an arrhythmia signal or not. According to the invention, existing big data is fully utilized, model training is carried out on electrocardiogram data of a plurality of databases, and the problem that a large amount of manpower and material resources need to be consumed to uniformly divide standards is solved; and in addition, Hilbert spectrum analysis is introduced for the randomness problem of the electrocardiosignals, so that the model obtains richer information, and the arrhythmia detection precision is further improved.

Description

technical field [0001] The invention relates to the technical field of heart rhythm detection equipment, in particular to a method and system for detecting arrhythmia. Background technique [0002] Patients with myocardial injury and arrhythmia have a high mortality rate, especially some patients with frequent arrhythmia (atrial fibrillation, ventricular fibrillation, etc.), arrhythmia detection (or early warning) is very important for the rescue of severe emergency patients, and is of great importance to public health. Safety prevention and control or the treatment of epidemic diseases are also of great significance. [0003] ECG signal, especially for critically ill patients, is a typical non-stationary medical signal and can be used as the basis for the diagnosis of arrhythmia. In terms of arrhythmia detection, traditional detection methods generally use ECG signals as stationary random signals to analyze directly from the time domain or frequency domain. [0004] A lar...

Claims

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Application Information

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IPC IPC(8): A61B5/318A61B5/346A61B5/00
CPCA61B5/318A61B5/346A61B5/7235A61B5/7267A61B5/7253
Inventor 刘常春王吉阔杨磊
Owner 济南汇医融工科技有限公司
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