Electrocardio automatic diagnosis method based on intelligent simulation modeling

Abstract

The invention provides an electrocardio automatic diagnosis method based on intelligent simulation modeling, and the method comprises the following steps: S1, carrying out the preprocessing of electrocardio signasl, employing a fast planting filter with a window length of 0.5*sr+1 to remove baseline offset, employing the sr as a sampling rate, and employing fast wavelet transform to remove high-frequency noise; S2, waveform positioning: respectively positioning the starting point and the ending point of a QRS, the starting points, the ending points and the peak values of a P wave and a T wave, and the positions of three wave crests of a Q wave, an R wave and an S wave based on a full-automatic electrocardiograph waveform detection algorithm of wavelet transformation, and unifying the number of cardiac beats of each lead according to a lead II; and when the starting point and the end point of the QRS are positioned, carrying out secondary high-frequency noise removal processing on the electrocardio signals; S3, feature extraction: extracting related features required by electrocardio diagnosis; and S4, electrocardio diagnosis: converting diagnosis thinking of a doctor into electrocardiogram feature description by using a rule method so as to diagnose electrocardio diseases; the obtained aluminum alloy base material has good conductivity.

Description

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AI Technical Summary

Benefits of technology

This patented technology allows for automated interpretation by physicians who are trained through simulations that mimic how they see things like cardiac problems or symptoms from people being tested during clinics testing. These models help healthcare professionals better understand what makes them feel sick faster than usual without having their hands busy doing other tasks such as analyzing data collected over time.

Problems solved by technology

The technical problem addressed in this patented text relates to identifying potential dangerous conditions that may occur during long periods after taking measurements made through traditional methods like chest X ray photography. This can be difficult due to lack of sufficient training and knowledge about how well pacing systems work.

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