Method for combining electrocardiogram with respiration to calculate heart rate variability on basis of EMD decomposition

Abstract

The invention discloses a method for combining an electrocardiogram with respiration to calculate the heart rate variability (HRV) on the basis of EMD decomposition. A heart rate is subjected to EMD decomposition first to be decomposed into several intrinsic mode layers, the correlation between signals, obtained through EMD decomposition of the heart rate, of each layer and corresponding respiratory slopes is used as a basis, each mode layer of the heart rate is divided into respiratory-related modes and modes which are not related to the respiration, the respiratory-related modes and the modes which are not related to the respiration are used as representations of high frequency bands (HF) and low frequency bands (LF) of the HRV respectively, continuous wavelet transform is adopted, and time-frequency HRV change results can be obtained. Different from the problems in HF and LF fixed frequency segmentation points (f=0.15Hz) of a traditional HRV analysis method that the HF spectrum peakmoves horizontally along with the respiratory frequency and is even smaller than 0.15 Hz, the method is based on a physiological mechanism, the influence of the respiration on the HRV is used as reference, and the problems of inconsistency and difficult reproducibility of experimental results and unscientific explanation of the experimental results existing in the field of HRV analysis for a longtime are avoided.

Description

technical field [0001] The invention belongs to the technical field of biomedical signal processing, and aims to propose a method for calculating heart rate variability based on EMD decomposition of ECG and respiration. Background technique [0002] The heart is an extremely important organ in the human body. Through rhythmic contraction and relaxation, it promotes blood to circulate continuously in a certain direction in the blood vessels, thus ensuring a relatively constant internal environment and normal metabolism. Studies have confirmed that the heart not only beats according to the basic rhythm of the sinoatrial node, but also is regulated by humor and nerves (the latter is dominant) to adapt to changes in the body and the external environment. Neuromodulation is primarily achieved through the autonomic nervous system (sympathetic and parasympathetic nervous systems). [0003] Imbalances in cardiac autonomic function are strongly associated with cardiovascular disease...

AI Technical Summary

Problems solved by technology

And due to the uncertainty principle, the FFT method cannot have good characterization capabilities in both the time domain and the frequency domain

Therefore, the traditional HRV analysis method calculates which components are generally included in the heart rate variability over a period of time, but cannot describe the change of each component over time, resulting in two signals with a large difference in time domain. possible spectrum Figure 1 Sample

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