An intelligent evaluation method of ecg signal noise pollution degree and category

Abstract

The present invention proposes an intelligent evaluation method for ECG signal noise pollution degree and category, including the following steps: S1, ECG signal preprocessing; S2, ECG signal component characteristic mathematical statistical calculation; S3, ECG signal noise pollution degree judgment; S4, low frequency baseline Judgment of drift noise pollution degree; S5, judgment of high-frequency component noise pollution category and pollution degree; S6, comprehensive evaluation of ECG signal overall noise pollution degree and category. The evaluation method of the present invention integrates the M-CEEMD signal decomposition and the SVC network cluster to accurately complete the evaluation of the noise pollution degree of the ECG signal and the automatic classification of pollution types. Realize the screening of available ECG signals, provide a basis for the selection of targeted filtering methods, improve the filtering effect while retaining the original ECG data information to the greatest extent, reduce the false positive rate of ECG intelligent diagnosis, and improve the diagnostic accuracy rate , has the characteristics of strong clinical generalization and high classification accuracy.

Description

technical field [0001] The present invention relates to the field of artificial intelligence technology and smart medical technology, in particular to an intelligent evaluation method for ECG signal noise pollution degree and category Background technique [0002] The monitoring and analysis of ECG signals is the main means to reduce the mortality of cardiovascular diseases. According to the World Health Organization report in 2017, cardiovascular diseases (CVD) are the first cause of death in the world. According to statistics, the number of cardiovascular patients in my country is as high as 290 million, and its mortality rate accounts for more than 40% of the causes of death among residents, which is much higher than that of tumors and other diseases. With the aging process in our country, the morbidity and mortality of CVD are also increasing year by year. Since CVD diseases have the characteristics of rapid deterioration of chronic diseases in a short period of time, l...

AI Technical Summary

Problems solved by technology

However, most of the existing filtering technologies can only obtain better filtering effects for specific noises. However, if the current signal noise pollution degree and pollution type are unknown, direct filtering processing will not only fail to obtain good filtering results, but may even cause ECG The waveform of the signal itself is deformed, which further deteriorates the intelligent diagnosis results of the ECG signal

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