Physiological electrical signal analysis method based on ensemble empirical mode decomposition

Abstract

The invention discloses a physiological electrical signal analysis method based on ensemble empirical mode decomposition. The method is as below: firstly ensemble empirical mode decomposition is performed on heart rate variability signals to obtain intrinsic mode functions with different frequencies of the signals; the intrinsic mode functions with less signal information are removed, and then thebasic scale entropy values of the different intrinsic mode functions of the signals are calculated; and an intrinsic mode function layer with substantial distinguishing effect is found as an indicator for diagnosing heart disease, thereby providing a powerful theoretical basis for clinical medical research. The method can sharply reveal the complexity of the signals from a shorter time series, and can provide convenience for practical applications, and if random noise is added into the signals, the method is still effective; and the method is not limited by the specific waveforms of the signals and can be used to analyze the signals of an arbitrary waveform.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a physiological electrical signal analysis method based on set empirical mode decomposition. Background technique [0002] At present, the number of patients with various cardiovascular diseases in my country has reached 290 million. According to the latest survey, about 4 million people die of various cardiovascular diseases every year. Cardiovascular diseases have become a major health problem that must attract the attention of the whole people in our country. Therefore, research on the complexity of the cardiac system and the prediction, diagnosis, and treatment of cardiac system diseases is of great significance. At present, the research on the output signal of the cardiac system is mainly divided into two categories. The first category is the analysis of the ECG waveform. This method is simple and easy to operate, and the analysis results can be obtained intuitive...

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Problems solved by technology

[0003] At present, the analysis of the heart rate variability signal is mainly based on the signal as a whole, and requires a large number of continuous data points. It has a certain impact on the analysis results, making the analysis results inaccurate, so it is necessary to propose a new technical solution to solve the above problems

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