Method for Extracting Respiration Signal and Respiratory Frequency from Wearable ECG

Abstract

The present invention proposes a method for extracting respiratory signals and respiratory frequency from wearable ECG. The method first obtains the original wearable ECG data signal, then filters the ECG data, and then identifies the characteristic points of the QRS wave group. , the respiration signal is obtained by the amplitude transformation method, the first respiration rate is calculated according to the peak detection method, the second respiration rate is obtained according to the autocorrelation function and fast Fourier transform, and finally the respiration rate is fused. The method for extracting respiratory signal and respiratory frequency from the wearable ECG provided by the present invention, through this method, the extraction of the respiratory signal does not depend on special hardware, and the respiratory signal can be obtained only by the ECG signal, and the obtained data The accuracy is high, the error is small, and it is less affected by the environment, movement, etc. At the same time, it will not increase the discomfort of the patient to be monitored and the physical and mental burden of the patient, and is convenient for daily physiological monitoring.

Description

technical field [0001] The invention relates to the field of breath detection, in particular to a method for extracting breath signals and breath frequency from a wearable electrocardiogram. Background technique [0002] Respiration is one of the most important physiological processes of the human body, and it is also one of the signs of life extension. The monitoring of human respiration is an important part of daily comprehensive monitoring and an important part of modern monitoring technology in the medical field. Medicine has also proved that diseases such as hypertension, heart disease, and atrial fibrillation are all related to respiratory dysfunction, and technologies related to medical research, military research, and sports medicine related to respiratory monitoring have been extremely widely used. [0003] As a very important physiological process, the respiratory signal has been paid more and more attention and researched by people, and in the past few decades, wi...

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Problems solved by technology

[0005] However, the existing extraction of respiratory signal (EDR) from ECG signal mainly determines the respiratory signal through a single feature point, and is aimed at the ECG signal of the subject in a static state, for example, by identifying the feature point of the ECG signal The periodic change of the amplitude of the R wave is used to judge the trend of the respiratory signal. Although this algorithm is relatively simple and logically clear, it is easily affected by the baseline drift of the ECG signal and random interference, etc., resulting in large The error makes the respiration rate deviation larger

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