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Electrocardiosignal ST section automatic judging method and device based on artificial intelligent technology

An ECG signal and artificial intelligence technology, applied in the field of data processing, can solve problems such as drift, large interference of ECG signals, and reduced accuracy of ST segment recognition and judgment, and achieve improved accuracy, simple calculation, and easy implementation Effect

Active Publication Date: 2019-04-16
SHANGHAI SID MEDICAL CO LTD
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AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies of the prior art, the object of the present invention is to provide a method and device for automatically judging the ST segment of the ECG signal based on artificial intelligence technology, aiming at solving the problem of the ST segment when there is large interference or drift in the ECG signal in the prior art. The problem that the accuracy of segment recognition and judgment is greatly reduced

Method used

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  • Electrocardiosignal ST section automatic judging method and device based on artificial intelligent technology
  • Electrocardiosignal ST section automatic judging method and device based on artificial intelligent technology
  • Electrocardiosignal ST section automatic judging method and device based on artificial intelligent technology

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specific Embodiment 1

[0062] like Figure 1a , Figure 1b , Figure 1c As shown, in the embodiment of the present invention, the determination results of the ST segment are divided into three categories, including normal level, elevation, and depression. in, Figure 1a The ST segment is normal; Figure 1b For ST segment depression; Figure 1c For ST segment elevation.

[0063] like figure 2 and Figure 9 As shown, the embodiment of the present invention provides a method for automatically judging the ST segment of an electrocardiographic signal based on artificial intelligence technology, comprising the following steps:

[0064] Step S1: For the filtered ECG signal s(t), on the premise of knowing the position of the R wave peak, through local amplification, find the minimum value before and after the R wave peak, and accurately locate the Q wave peak and the S wave peak. Specifically, the desensitized ECG data is used as the ECG signal s(t) to be processed, the ECG signal has been filtered a...

specific Embodiment 2

[0098] like Figure 10 As shown, the embodiment of the present invention provides a device for automatic determination of ECG ST segment based on artificial intelligence technology, including:

[0099] The first module 201 is used to: for the filtered ECG signal s(t), on the premise that the position of the R peak is known, through local amplification, find the minimum value before and after the R peak, and accurately locate the Q peak and S peak;

[0100] The second module 202 is used for: performing wavelet transformation on the accurate position of the QRS wave group obtained by the first module 201, and accurately locating the P wave peak and the T wave peak by using the triangle area method through local amplification;

[0101] The third module 203 is used to: use the triangular area method to find the start and end points of the P wave and the start and end points of the T wave in the search window for the P wave peak and the T wave peak obtained by the second module 20...

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Abstract

The invention discloses an electrocardiosignal ST section automatic judging method and device based on the artificial intelligent technology. For filtered human body electrocardiosignals, on the basisof wavelet filtering and a triangular area method, key character points of the electrocardiosignals are extracted, positioning S waves and T waves are included, the ST section initial point and slopecharacteristics are accurately recognized, then, a base line removal method based on mean value filtering is put forwards, extracted base line sequences are subtracted, novel electrocardiosignals areobtained, ST section and base lines are extracted for the electrocardiosignals, the heart rate and the slope of each section base line are calculated, the standard reference line is selected comprehensively, finally ST section abnormal changes are recognized according to the standard reference line, the qualitative and quantitative ST section judging result is obtained, and whether the base lineis lifted, lowered or normal is determined. The problems that due to base line shifting, base line errors are caused, standard base line selection is not accurate, and the abnormal heartbeat number difference is large are solved, the ST section abnormal change judging accuracy is indirectly improved, calculation is easy, and the method is easy to implement.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method and device for automatically determining the ST segment of an electrocardiographic signal based on artificial intelligence technology. Background technique [0002] The electrocardiogram is a comprehensive reflection of bioelectrical signals on the body surface during cardiac activity. Each cardiac cycle is usually composed of a series of P waves, QRS complexes, and T waves. The QRS complexes include Q waves, R waves, and S waves. The time interval between the onset and offset of each characteristic sub-band is significant, reflecting the physiological processes of the heart and autonomic nervous system. The section from the end of the QRS complex to the beginning of the T wave is called the ST segment. [0003] The ST segment represents the potential change of the repolarization process after the completion of ventricular depolarization. The normal ST segment s...

Claims

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Application Information

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IPC IPC(8): A61B5/0452A61B5/366
CPCA61B5/7225A61B5/7253A61B5/349A61B5/725A61B5/726A61B5/358A61B5/36A61B5/0245A61B5/353A61B5/355G16H50/20G16H40/63
Inventor 朱俊江张德涛伍尚实汪朝阳陈广怡
Owner SHANGHAI SID MEDICAL CO LTD
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