A device for evaluating arterial elasticity function based on pulse analysis

Abstract

The invention provides an arterial elasticity evaluating device based on pulse analysis. The device comprises a left-and-right channel pulse signal detecting module, a computer and a data storage card, wherein the left-and-right channel pulse signal detecting module is connected with an analog-digital conversion module and used for collecting pulse signals of bilateral limbs of a subject; the data storage card is used for storing the pulse signals of the subject and a created arterial elasticity evaluation report; the analog-digital conversion module, the data storage card and a printer are all connected with the computer; the computer is used for performing real-time analysis on the pulse signals, displaying and storing, and printing control, as well as realizing evaluation on pulse signal quality, normalization of the pulse signals, creation and analysis of a pulse template, adjustment of wavelet characteristic parameters, arterial elasticity evaluation and creation of the evaluation report. With the adoption of the device, the pulse signals can be collected from different positions in both sides of the subject and then analyzed and treated on real time, so as to accurately evaluate the arterial elasticity of the bilateral limbs of the subject.

Description

technical field [0001] The invention relates to a device for evaluating arterial elastic function, which belongs to the technical field of non-invasive detection of human arterial elastic function. Background technique [0002] The damage of cardiovascular and cerebrovascular diseases to the human body is hidden, gradual, systemic, and has no obvious clinical symptoms, so it is called "silent disease". However, it is the number one killer of human health. According to the data released by the World Health Organization (WHO), 16 million people die from cardiovascular and cerebrovascular diseases every year in the world, accounting for more than 50% of the total mortality; The absolute number of patients with cardiovascular and cerebrovascular diseases in my country ranks first in the world. Among the causes of cardiovascular and cerebrovascular diseases, arteriosclerosis is the main cause, which is the basis of cardiovascular and cerebrovascular diseases such as hypertension,...

AI Technical Summary

Problems solved by technology

[0003] For a long time, the main technical means to evaluate the arterial elasticity function clinically is angiography, but this method is an invasive test, which requires high technical and equipment conditions, the inspection price is relatively expensive, and there may be adverse reactions related to the operation (such as contrast agent allergy and contrast agent nephropathy, etc.), these deficiencies largely affect its wide application in clinic; more importantly, invasive arteriography can only find that obvious Arterial structural lesions with stenosis of the lumen, and limited help in the detection of arterial elastic function before the arterial structural lesions

At present, there are three main methods for non-invasive detection of arterial elasticity function: the first is pulse wave velocity (pulse wave velocity, PWV) measurement method, which evaluates arterial elasticity by measuring the propagation speed of pulse wave between two fixed points when passing through the arterial system , the disadvantage is that the pulse wave propagation distance is required to calculate PWV, which is estimated by empirical formula based on the subject's height and weight information, and the empirical formula is based on demographic data, so it is difficult to guarantee the accuracy of individual detection; second One is to evaluate the arterial elastic function by analyzing the pulse wave waveform and calculating the augmentation index (AI), but the calculation of the AI ​​index is very unstable and easily affected by noise, resulting in a relatively large deviation between the two measurements of the same subject before and after. The third is to use ultrasound imaging to directly detect the compliance (compliance, C) of the wall of a specific artery. This detection method also requires high technical and equipment conditions, and the detection results depend on individual doctors. Judgment, statistical stability is not high

In addition, the above-mentioned three methods of non-invasive detection of arterial elasticity function have the following common shortcomings: First, the calculation of various indicators (PWV, AI, C) is mostly based on the pulse waveform in one or several cardiac cycles, while The impact of pulse waveform variation in different cardiac cycles is not considered, and the existing research results show that physiological signals have both short-term and long-term variability, and the impact of variability on the stability of indicators cannot be ignored. Therefore, a study of different A new non-invasive evaluation method of arterial elastic function that takes into account the variability of cardiac cycle signals is particularly necessary; second, the computer analysis software of the above-mentioned non-invasive detection method does not pay enough attention to the evaluation of pulse signal quality. There are serious quality problems in the pulse waveform in the cycle, which will lead to poor statistical stability of the calculation results. The pulse signal quality assessment is the premise and prerequisite for the medical interpretation of the pulse signal. The third is that most of the above-mentioned non-invasive detection methods are fixed pulse signal collection points, and the arterial elasticity evaluation criteria cannot change with the position of the pulse detection point. However, existing studies have shown that the arterial elasticity at different positions is different. Assessment criteria Analyzing the pulse signals detected at different sites and then assessing arterial elasticity will lead to assessment errors, so it is necessary to study a technique that can be used for non-invasive assessment of multi-point arterial elasticity function

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