Heart rate fusion labeling method and system based on Bayesian prior probability

A priori probability and heart rate technology, applied in the field of signal detection and medical equipment electronics, can solve problems such as poor robustness and reduced detection accuracy, and achieve the effects of reliable heart rate estimation, high detection efficiency, and improved heart rate estimation accuracy.
CN113139604AActive Publication Date: 2021-07-20SOUTHEAST UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SOUTHEAST UNIV
Publication Date
2021-07-20

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Abstract

The invention discloses a heart rate fusion labeling method and system based on Bayesian prior probability; reading, preprocessing and signal segmentation are performed on initial electrocardiosignals to obtain electrocardiograph data samples, and feature extraction is performed on the electrocardiograph data samples; according to different types of initial electrocardiosignal sets, a single-lead database or a multi-lead database, a proper heart rate labeling fusion process based on Bayesian prior probability is developed. In addition, probability estimation and iterative solution are carried out on the heart rate tags marked by multiple leads or multiple algorithms through a Bayesian criterion and an expectation maximization algorithm, and a heart rate tag value with higher precision is obtained through fusion. The fusion model automatically knows potential differences among different labeled samples; due to the fact that a label generated by a single algorithm or a lead is possibly unreliable, a label value with higher dependency is obtained through a fusion model, the accuracy of long-term dynamic heart rate estimation is improved, and more accurate information is provided for diagnosis of clinical cardiovascular diseases.
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Description

technical field

[0001] The invention belongs to the technical field of signal detection and medical equipment electronics, and in particular relates to a heart rate fusion labeling method and system based on Bayesian prior probability. Background technique

[0002] Cardiovascular disease is the main cause of death worldwide, and the detection of ECG signals is one of the basic methods for detecting and diagnosing cardiovascular diseases. Therefore, the real-time monitoring and intelligent labeling and analysis of ECG signals have received great attention. In order to achieve this goal, the automatic labeling of the QRS wave and heart rate parameters of ECG signals must be realized first, because they are not only the research basis for intelligent diagnosis of cardiovascular diseases, but also the target parameters monitored by ECG instruments.

[0003] Sustained high accuracy is the key to the practical application of Holter's heart rate detection algorithm. In fact, most o...

Claims

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