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Lead inversion recognition method for ECG equipment based on machine learning

A technology of machine learning and recognition methods, which is applied in the direction of character and pattern recognition, instruments, sensors, etc., and can solve problems such as the reduction of recognition accuracy of pattern recognition methods

Active Publication Date: 2022-02-18
安徽心之声医疗科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] If the positive and negative poles are reversed, and the acquired waveform is an inverted lead, the shape of the P wave, QRS complex, ST segment, T wave and other characteristic waves will be inverted. In this case, the pattern recognition method The recognition accuracy will be greatly reduced
This problem occurs especially in scenarios where there is no medical staff to take care of it, such as portable ECG collection equipment. If the user does not carefully read the instructions, this problem is easy to occur

Method used

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Embodiment Construction

[0017] The following clearly and completely describes the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0018] In describing the present invention, it is to be understood that the terms "opening", "upper", "lower", "thickness", "top", "middle", "length", "inner", "surrounding" etc. Indicating orientation or positional relationship is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be construed as limiting the pres...

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PUM

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Abstract

The invention discloses a method for identifying lead inversions of electrocardiographic equipment based on machine learning, comprising the following steps: collecting normal lead data, generating inverted lead data, data preprocessing, feature extraction, model training, and model prediction; the lead inversion can be realized The recognition process does not rely on the participation of medical staff, but builds a machine learning model based on existing historical data, so that the model can automatically judge whether the collected ECG signal is a normal lead or an inverted lead.

Description

technical field [0001] The invention relates to an identification method based on machine learning, in particular to an identification method for lead inversion of electrocardiographic equipment based on machine learning. Background technique [0002] The ECG signal data collected by the ECG equipment has strict regulations on the position of the positive and negative poles. For example, the limb I lead collected by the portable ECG signal acquisition device requires the positive pole to be connected to the left upper limb, and the negative pole to be connected to the right upper limb. Based on this, the standard limb I lead analysis method is adopted, and the pattern recognition method is further used to identify P wave, QRS complex, ST segment, T wave and other characteristic waves are produced, and finally the diagnosis conclusion is given. [0003] If the positive and negative poles are reversed, and the collected waveform is the inverted lead, the shape of the P wave, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/318A61B5/316A61B5/308G06K9/00
CPCA61B5/316A61B5/303A61B5/318G06F2218/12
Inventor 洪申达傅兆吉周荣博俞杰
Owner 安徽心之声医疗科技有限公司