Continuous monitoring method for dynamic changes of autonomic nervous system

Abstract

The invention discloses a continuous monitoring method for dynamic changes of the autonomic nervous system. The method comprises the following steps that firstly, electrocardiography signals or body surface photoelectric plethysmography signals are acquired, and are original signals which are not subjected to filtering processing and have the sampling frequency being 500Hz; the acquired signals are intercepted according to a certain computation window length; the intercepted signals are subjected to preprocessing of base line removing, power frequency interference removing and the like; R-wave peaks of obtained preprocessed electrocardiography signals or peak points of obtained preprocessed photoelectric plethysmography signals are detected; R-to-R interphase or the peak-to-peak interphase of each beat are calculated; Poincare parameters including SD1, SD2 and SD1 / SD2 of an extracted interphase sequence are calculated; calculation of the Poincare parametsrs is repeated through continuous backward shifting of a calculation window until all data are processed completely; and changing curves of the three obtained Poincare parameters are drawn correspondingly to represent the continuous dynamic changes of the autonomic nervous system, and continuous monitoring on a fine time scale is achieved.

Description

technical field [0001] The invention relates to a digital signal processing method, in particular to a continuous monitoring method for dynamic changes of the autonomic nervous system. Background technique [0002] The regulation of the autonomic nervous system to the cardiovascular system is a dynamic process. When the physiological state of the human body changes, is affected by external stimuli, or is affected by pathological factors, the autonomic nervous system will respond quickly to meet new metabolic needs or to protect the body. Generally speaking, the response of the vagus nerve branch The speed is within 1 second, while the response speed of the sympathetic branch is relatively slow, but it is also within 4 or 5 seconds. For example, when the human body enters a state of exercise from a resting state, the activity of the vagus nerve declines suddenly, which causes the heart rate to rise rapidly at the beginning of exercise, and as the exercise intensity increases...

AI Technical Summary

Problems solved by technology

However, from the perspective of statistical significance, the existing heart rate variability analysis has limitations in the detection of dynamic changes in the autonomic nervous system, and the existing heart rate variability indicators can only reflect the overall state of the autonomic nervous system in a certain period of time as a whole

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