CN104644151B - A kind of pressure pulse wave wave travel Forecasting Methodology based on photoelectricity volume pulse signal - Google Patents

A kind of pressure pulse wave wave travel Forecasting Methodology based on photoelectricity volume pulse signal Download PDF

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CN104644151B
CN104644151B CN201510051739.XA CN201510051739A CN104644151B CN 104644151 B CN104644151 B CN 104644151B CN 201510051739 A CN201510051739 A CN 201510051739A CN 104644151 B CN104644151 B CN 104644151B
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张松
顾冠雄
杨琳
杨益民
李旭雯
杨星星
王薇薇
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Beijing University of Technology
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Abstract

一种基于光电容积脉搏信号的压力脉搏波波形传播预测装置,其特征在于:包括波形输入模块,波形调理模块,波形拟合模块,波形转换模块,及波形输出模块。其中:波形调理模块包括预处理电路,单拍分离器及归一化电路,波形拟合模块包含拟合函数设定器,波形拟合器及波形质量判别器,波形转换模块包括部位设定器,目标函数设定器,特征人群设定器,参数转换器及波形合成器。该装置可利用人体各部位光电容积脉搏信号根据生理学统计规律预测具有人体各部位压力脉搏波波形信号,该装置的使用范围、预测效果及稳定性都较现有装置有一定提高。

A device for predicting the propagation of pressure pulse wave waveform based on photoplethysmographic signals is characterized in that it includes a waveform input module, a waveform conditioning module, a waveform fitting module, a waveform conversion module, and a waveform output module. Among them: the waveform conditioning module includes a preprocessing circuit, a single-shot separator and a normalization circuit, the waveform fitting module includes a fitting function setter, a waveform fitter and a waveform quality discriminator, and the waveform conversion module includes a position setter , Target function setter, characteristic crowd setter, parameter converter and waveform synthesizer. The device can use the photoplethysmographic pulse signals of various parts of the human body to predict the pressure pulse wave waveform signals of various parts of the human body according to physiological statistical laws.

Description

一种基于光电容积脉搏信号的压力脉搏波波形传播预测方法A Prediction Method of Pressure Pulse Wave Waveform Propagation Based on Photoplethysmography Signal

技术领域technical field

本发明涉及医疗设备技术领域,特别涉及一种基于光电容积脉搏波预测各部位压力脉搏波波形的方法。The invention relates to the technical field of medical equipment, in particular to a method for predicting pressure pulse wave waveforms of various parts based on photoplethysmography waves.

背景技术:Background technique:

脉搏波中蕴含着丰富的血流动力学信息。历来作为临床诊断和治疗的依据,大量的临床实测结果证实,脉搏波的特征与心血管生理状态有着密切的关系。脉搏波所表现出来的形态(波的形状)、强度(波的幅值)、速率(波的速度)与节律(波的周期)等方面的综合信息在相当程度上反映出人体心血管系统的许多生理和病理特征。Pulse waves contain rich hemodynamic information. It has always been used as the basis of clinical diagnosis and treatment, and a large number of clinical measurement results have confirmed that the characteristics of pulse wave are closely related to the cardiovascular physiological state. The comprehensive information of the form (shape of wave), intensity (amplitude of wave), velocity (speed of wave) and rhythm (period of wave) exhibited by pulse wave reflects the cardiovascular system of the human body to a considerable extent. Many physiological and pathological features.

在采集原理方面,目前脉搏波的采集方式主要有使用压力传感器的压力脉搏波采集或使用光电传感器的光电容积脉搏波采集。动脉内压力脉搏波已得到了较全面的分析研究,流体力学模型较为明确,对应的血流动力学特性及心血管生理意义应用亦较为广泛。然而,人体压力脉搏波的采集极易受到采集位置等多方面干扰,所需操作技能要求较高,且缺乏可重复性,不便于连续检测。光电容积脉搏波指端采集具有较好的稳定性及重复性,但其对心血管功能判断的准确性较已研究较为完善的压力脉搏波欠佳。In terms of acquisition principles, the current pulse wave acquisition methods mainly include pressure pulse wave acquisition using a pressure sensor or photoplethysmography pulse wave acquisition using a photoelectric sensor. The arterial pressure pulse wave has been relatively comprehensively analyzed and studied, the fluid dynamics model is relatively clear, and the corresponding hemodynamic characteristics and cardiovascular physiological significance are widely used. However, the collection of human pressure pulse waves is easily interfered by various aspects such as the collection location, requires high operational skills, and lacks repeatability, making continuous detection inconvenient. Photoplethysmography fingertip acquisition has good stability and repeatability, but its accuracy in judging cardiovascular function is not as good as that of pressure pulse wave, which has been well studied.

发明内容:Invention content:

现有的技术方案主要利用采集部位光电容积信号及对应目标部位压力脉搏波信号的功率谱分析建立的传递函数等非生理参数模型,并主要关注于指端容积脉搏信号及桡动脉压力脉搏信号。由于脉搏信号的个体差异性较大,上述装置在大规模应用时稳定性较差,功能较为单一,且所建立模型本身无生理意义,不利于对模型的修正与改进。Existing technical solutions mainly use non-physiological parameter models such as transfer functions established by the power spectrum analysis of the photoelectric volume signal of the acquisition site and the pressure pulse wave signal of the corresponding target site, and mainly focus on the fingertip volume pulse signal and radial artery pressure pulse signal. Due to the large individual differences in pulse signals, the above-mentioned devices have poor stability and single functions when applied on a large scale, and the established model itself has no physiological significance, which is not conducive to the correction and improvement of the model.

为解决上述问题,本发明分别提出了一种基于脉搏波生理特征的容积脉搏信号和压力脉搏信号的波形含参表达式,并利用先验统计规律建立采集部位光电容积脉搏波表达式参数与对应目标部位压力脉搏波形表达式参数间的回归方程组。从而实现将输入的光电容积脉搏信号转换为目标部位的压力脉搏波信号。波形拟合的方法具有较好的稳定性,回归方程组具有较明确的生理意义,方便针对不同生理状态进行微调与改进。由此可以解决现有技术中预测波形稳定性差,及模型无法修正的问题。In order to solve the above problems, the present invention respectively proposes a waveform containing parameter expression of volume pulse signal and pressure pulse signal based on pulse wave physiological characteristics, and uses prior statistical laws to establish the photoplethysmography expression parameters and corresponding A group of regression equations between the parameters of the pressure pulse waveform expression at the target site. In this way, the input photoplethysmogram signal is converted into the pressure pulse wave signal of the target site. The waveform fitting method has good stability, and the regression equation group has a relatively clear physiological meaning, which is convenient for fine-tuning and improvement for different physiological states. Therefore, the problems of poor stability of predicted waveform and inability to correct the model in the prior art can be solved.

为达到上述目的,本发明所采取的技术方案为:一种基于光电容积脉搏信号的压力脉搏波传播预测装置,其特征在于:包括信号输入调理模块,波形拟合模块,波形转换模块,波形合成模块及输出模块。In order to achieve the above object, the technical solution adopted by the present invention is: a pressure pulse wave propagation prediction device based on photoplethysmography signal, which is characterized in that it includes a signal input conditioning module, a waveform fitting module, a waveform conversion module, and a waveform synthesis modules and output modules.

所述波形输入模块接收自人体某一部位实测的时域光电容积脉搏信号。The waveform input module receives a time-domain photoplethysmography signal measured from a certain part of the human body.

所述信号调理模块,对输入的时域光电容积脉搏信号进行预处理,利用现有技术将其分解为对应单一心动周期的单拍信号,对每一单拍信号的幅值与波长进行归一化处理。The signal conditioning module preprocesses the input time-domain photoplethysmogram signal, decomposes it into single-beat signals corresponding to a single cardiac cycle by using existing technology, and normalizes the amplitude and wavelength of each single-beat signal treatment.

所述波形拟合模块接收归一化后的单拍脉搏信号,并利用给定的波形含参表达式fI应用曲线拟合算法对其进行拟合,波形的含参表达式由分别代表脉搏波波形主波、重搏波、反射波的含参表达式相加确定,拟合所得解析表达式各项参数向量为II,作为波形特征参数向量。The waveform fitting module receives the normalized single beat pulse signal, and utilizes the given waveform containing the parameter expression f I to apply a curve fitting algorithm to fit it, and the waveform containing the parameter expression is represented by respectively pulse The parametric expressions of main wave, dicrotic wave, and reflected wave are determined by summing, and the parameter vectors of the analytical expressions obtained by fitting are I I , which are used as waveform characteristic parameter vectors.

光电容积脉搏信号的含参表达式为:The parametric expression of the photoplethysmogram signal is:

其中,Hin,bin,Win为参数,t为自变量,表示采样点数。表达式中n=1,2,3的部分分别对应脉搏波波形的主波、反射波、重搏波波形。其中,Hin表示波动的幅值,bin表示波动的中心位置,Win波动的宽度。Among them, H in , bin in , Win in are parameters, and t is an independent variable, indicating the number of sampling points. Parts of n=1, 2, and 3 in the expression correspond to the main wave, reflected wave, and dicrotic wave waveform of the pulse wave waveform respectively. Among them, H in represents the amplitude of the fluctuation, bin represents the center position of the fluctuation, and W in represents the width of the fluctuation.

曲线拟合过程算法采用最小二乘算法,并根据各波动生理意义对各项参数范围进行限定,之后设定拟合初始条件Hi1>Hi2>Hi3,bi1<bi2<bi3,Win>0。拟合确定的特征参数向量II为:The curve fitting process algorithm adopts the least squares algorithm, and limits the range of each parameter according to the physiological meaning of each fluctuation, and then sets the initial fitting condition H i1 >H i2 >H i3 , b i1 <b i2 <b i3 , Win >0. The characteristic parameter vector II determined by fitting is:

II=[Hi1,Hi2,Hi3,bi1,bi2,bi3,Wi1,Wi2,Wi3]I I =[H i1 ,H i2 ,H i3 , bi1 , bi2 , bi3 ,W i1 ,W i2 ,W i3 ]

在上述波形含参表达式条件下,拟合效果主要取决于脉搏波采集受到的干扰程度,故以拟合确定系数R2作为波形质量判别的定量化标准。拟合确定系数R2是常用的判断两曲线相似程度的计算方法。在本发明中R2同样作为采集质量判别参数,对应R2小于一定值的单拍波形认为采集质量差并予以舍弃。Under the condition that the above-mentioned waveform contains parametric expressions, the fitting effect mainly depends on the degree of interference received by the pulse wave acquisition, so the fitting determination coefficient R2 is used as the quantitative standard for the judgment of the waveform quality. The fitting determination coefficient R2 is a commonly used calculation method for judging the similarity of two curves. In the present invention, R 2 is also used as an acquisition quality discrimination parameter, and the single-shot waveform corresponding to R 2 less than a certain value is considered to be of poor acquisition quality and discarded.

R2计算公式如下:R2 calculation formula is as follows:

其中,fi分别表示实测光电容积脉搏数据点、实测光电容积脉搏数据平均值及数据点拟合期望值,pl为单波数据点个数。Among them, f i , Respectively represent the measured photoplethysmography data points, the average value of the measured photoplethysmography data and the expected value of the data point fitting, and pl is the number of single-wave data points.

所述波形转换模块,根据被测者性别、年龄、平均动脉压指标进行分组,并根据对应分组下光电容积脉搏波实测部位与所需预测压力脉搏波部位波形特征参数间的先验统计规律,利用实测光电容积脉搏波特征参数计算预测对应部位压力脉搏波波形特征参数。The waveform conversion module is grouped according to the gender, age, and average arterial pressure index of the subject, and according to the prior statistical law between the measured part of the photoplethysmography wave and the waveform characteristic parameter of the required predicted pressure pulse wave part under the corresponding grouping, The measured photoplethysmographic characteristic parameters are used to calculate and predict the characteristic parameters of the pressure pulse wave waveform at the corresponding part.

上述对应分类下光电容积脉搏波实测部位与所需预测压力脉搏波部位波形特征参数间的先验统计规律建立方法如下:The method for establishing the prior statistical law between the measured photoplethysmography position and the required predicted pressure pulse wave position waveform characteristic parameters under the above corresponding classification is as follows:

(1)首先,将参与实验的人群按照性别、年龄、平均动脉压(MAP)进行分组,其中年龄以20岁为起始,5岁为间隔。平均动脉压以70mmHg为起始,10mmHg为间隔。对参与实验的人群进行分组。分别对上述各组实验人群同时检测耳部、手指端、脚趾端处光电容积脉搏波,并利用压力传感器检测桡动脉、肱动脉、颈动脉处压力脉搏波信号。从而获得不同人群特征的实测压力脉搏波及光电容积脉搏波信号。(1) First, the people participating in the experiment were divided into groups according to gender, age, and mean arterial pressure (MAP), where the age started at 20 years old and the interval was 5 years old. The mean arterial pressure starts at 70mmHg, with intervals of 10mmHg. Group the people who participated in the experiment. The photoelectric plethysmography waves at the ear, fingertips, and toes were simultaneously detected for the above-mentioned experimental groups, and the pressure pulse wave signals at the radial artery, brachial artery, and carotid artery were detected by pressure sensors. Thereby, the measured pressure pulse wave and photoplethysmography signals of different population characteristics are obtained.

(2)之后建立实测光电容积脉搏波与实测目标部位压力脉搏波波形特征参数间的统计学关系。与上述光电容积脉搏波特征提取方式相似,为提取压力脉搏波波形特征参数,利用压力脉搏波表达式对实测压力脉搏波波形进行拟合,压力脉搏波含参表达式为:(2) Afterwards, the statistical relationship between the measured photoplethysmography wave and the characteristic parameters of the pressure pulse wave waveform at the target site is established. Similar to the feature extraction method of the photoplethysmogram above, in order to extract the characteristic parameters of the pressure pulse wave, the pressure pulse wave expression is used to fit the measured pressure pulse wave waveform. The pressure pulse wave contains parameter expressions:

表达式参数及定义域均与fI相同。拟合过程算法采用最小二乘算法,并根据各波动生理意义对各项参数范围进行限定,之后设定拟合初始条件Ho1>Ho2>Ho3,bo1<bo2<bo3,Won>0。The expression parameters and domain are the same as f I. The fitting process algorithm adopts the least squares algorithm, and limits the range of each parameter according to the physiological meaning of each fluctuation, and then sets the initial fitting condition H o1 >H o2 >H o3 , b o1 <b o2 <b o3 ,W on >0.

其特征参数向量为IO=[Ho1,Ho2,Ho3,bo1,bo2,bo3,Wo1,Wo2,Wo3]Its characteristic parameter vector is I O =[H o1 ,H o2 ,H o3 ,b o1 ,b o2 ,b o3 ,W o1 ,W o2 ,W o3 ]

(3)对不同分组不同部位的实测波形分别利用fI及fO对实测的光电容积脉搏波波形及压力脉搏波波形采用波形拟合模块进行拟合,获得对应实测各光电容积脉搏信号的II及压力脉搏信号的IO向量。对于每一部位压力脉搏信号IO向量每项参数,建立对应不同分组的同时采集的光电容积脉搏信号特征参数向量的多元线性回归方程,即:(3) Use f I and f O for the measured waveforms of different groups and different parts, respectively, to fit the measured photoplethysmography waveform and pressure pulse wave waveform with the waveform fitting module, and obtain the corresponding I of each photoplethysmogram signal measured. I and the I O vector of the pressure pulse signal. For every parameter of each position pressure pulse signal I O vector, set up the multivariate linear regression equation of the photoplethysmogram signal feature parameter vector that corresponds to different groupings and collect simultaneously, namely:

Ho1=TM11×Hi1+TM12×Hi2+......+TM19×Wi3+CM1 H o1 =TM 11 ×H i1 +TM 12 ×H i2 +...+TM 19 ×W i3 +CM 1

Ho2=TM21×Hi1+TM22×Hi2+......+TM29×Wi3+CM2 H o2 =TM 21 ×H i1 +TM 22 ×H i2 +......+TM 29 ×W i3 +CM 2

Ho3=TM31×Hi1+TM32×Hi2+......+TM39×Wi3+CM3 H o3 =TM 31 ×H i1 +TM 32 ×H i2 +......+TM 39 ×W i3 +CM 3

bo1=TM41×Hi1+TM42×Hi2+......+TM49×Wi3+CM4 b o1 =TM 41 ×H i1 +TM 42 ×H i2 +...+TM 49 ×W i3 +CM 4

bo2=TM51×Hi1+TM52×Hi2+......+TM59×Wi3+CM5 b o2 =TM 51 ×H i1 +TM 52 ×H i2 +......+TM 59 ×W i3 +CM 5

bo3=TM61×Hi1+TM62×Hi2+......+TM69×Wi3+CM6 b o3 =TM 61 ×H i1 +TM 62 ×H i2 +......+TM 69 ×W i3 +CM 6

Wo1=TM71×Hi1+TM72×Hi2+......+TM79×Wi3+CM7 W o1 =TM 71 ×H i1 +TM 72 ×H i2 +...+TM 79 ×W i3 +CM 7

Wo2=TM81×Hi1+TM82×Hi2+......+TM89×Wi3+CM8 W o2 =TM 81 ×H i1 +TM 82 ×H i2 +......+TM 89 ×W i3 +CM 8

Wo3=TM91×Hi1+TM92×Hi2+......+TM99×Wi3+CM9 W o3 =TM 91 ×H i1 +TM 92 ×H i2 +......+TM 99 ×W i3 +CM 9

TM及CM各项系数由多元线性回归方程确定。整理IO各项参数建立方程组,整理系数矩阵及常数矩阵,可得TM及CM,其中,TM为9阶方阵,CM为9元素列向量。The coefficients of TM and CM were determined by multiple linear regression equations. Arranging various parameters of I O to establish a system of equations, arranging the coefficient matrix and constant matrix, TM and CM can be obtained, where TM is a 9-order square matrix, and CM is a 9-element column vector.

根据上述利用先验概率所得TM及CM矩阵,在应用过程中,利用采集部位的波形特征参数向量II计算目标部位的特征参数向量IO。根据所测光电容积脉搏波,提取其特征II,则可得目标部位特征向量IO为:According to the TM and CM matrices obtained by using the prior probability, in the application process, the characteristic parameter vector I O of the target part is calculated by using the waveform characteristic parameter vector I I of the acquisition part. According to the measured photoplethysmography wave, extract its characteristic I I , then the characteristic vector I O of the target part can be obtained as:

IO=TM×II+CMI O =TM×I I +CM

之后将获得的目标部位特征参数向量IO代入对应部位的压力脉搏波含参表达式fO,得到对应的压力脉搏波解析表达式。完成波形转换。Then, the obtained characteristic parameter vector I O of the target part is substituted into the parametric expression f O of the pressure pulse wave at the corresponding part to obtain the corresponding analytical expression of the pressure pulse wave. Complete the waveform conversion.

所述波形输出模块,将上述波形合成模块的结果及目标部位特征参数向量IO按要求形式输出。The waveform output module outputs the result of the above waveform synthesis module and the target part characteristic parameter vector I O in the required form.

本发明的有益效果在于:The beneficial effects of the present invention are:

(1)本发明装置仅需检测人体单一部位光电容积脉搏信号,即可在一定精度下获取不同部位的压力脉搏波信号。操作简单方便,且波形质量稳定。克服了常规压力脉搏波采集过程中测试流程复杂,使用不便,以及难以获取稳定脉搏波形的问题。在实际应用过程中可有效减少压力脉搏波直接采集次数,减少对操作技能的需求,提高了被测者舒适程度。经过大量的验证实验,效果良好。(1) The device of the present invention only needs to detect the photoplethysmographic pulse signal of a single part of the human body, and can obtain the pressure pulse wave signals of different parts with a certain accuracy. The operation is simple and convenient, and the waveform quality is stable. It overcomes the problems of complicated test process, inconvenient use, and difficulty in obtaining a stable pulse waveform in the conventional pressure pulse wave acquisition process. In the actual application process, it can effectively reduce the number of direct collection of pressure pulse waves, reduce the demand for operating skills, and improve the comfort level of the testee. After a lot of verification experiments, the effect is good.

(2)首次将基于脉搏波生理性波动特点的波形拟合装置应用于多部位脉搏波形,从而分析其传播过程中的生理性变化。方便了模型的调整与校正,为大规模临床应用奠定了一定基础。(2) For the first time, a waveform fitting device based on the characteristics of pulse wave physiological fluctuations is applied to multiple pulse waveforms, so as to analyze the physiological changes during its propagation. It facilitates the adjustment and correction of the model, and lays a certain foundation for large-scale clinical application.

附图说明:Description of drawings:

图1为本发明结构框图Fig. 1 is a structural block diagram of the present invention

图2为本发明操作流程图Fig. 2 is the operation flowchart of the present invention

图3为波形拟合及特征参数示意图Figure 3 is a schematic diagram of waveform fitting and characteristic parameters

图4为一个实测示例,并给出了与实测压力波形的对比Figure 4 is a measured example, and gives a comparison with the measured pressure waveform

图5为本发明在利用指端光电容积脉搏波预测桡动脉压力脉搏波的实验效果图。R2数据为实测压力脉搏单拍波形与预测单拍波形间的交叉验证效果,共实验426例。Fig. 5 is an experimental effect diagram of the present invention in predicting the pressure pulse wave of the radial artery by using the fingertip photoplethysmography wave. R 2 data is the cross-validation effect between the measured pressure pulse single-beat waveform and the predicted single-beat waveform, a total of 426 cases were tested.

具体实施方式:detailed description:

以下结合附图对本发明的一种较为典型的具体实施方式进行详细描述。A more typical specific implementation manner of the present invention will be described in detail below with reference to the accompanying drawings.

本发明的一种典型应用场景在于利用人体指端光电容积脉搏波信号预测桡动脉压力脉搏波信号。由此可以利用指端采集的成熟技术及高质量波形获得生理意义更加明确的桡动脉压力脉搏波数据。A typical application scenario of the present invention is to predict the pressure pulse wave signal of the radial artery by using the photoplethysmographic pulse wave signal of the fingertip of the human body. Therefore, the mature technology and high-quality waveform of fingertip acquisition can be used to obtain radial artery pressure pulse wave data with clearer physiological meaning.

如图1所示,预测过程开始后,首先根据被测者的性别年龄,血压选择相应的特征人群,并根据需要选择对应的预测部位。以一位年龄56岁女性,血压值为90/130mmHg的被测者为例,在步骤S201中设定性别,年龄与血压值,采集部位为指端,目标预测部位为桡动脉。在S202中根据设定,系统即根据先验统计规律的分组情况,自动选择出对应人群及部位的TM与CM矩阵。As shown in Figure 1, after the prediction process starts, first select the corresponding characteristic population according to the sex, age and blood pressure of the subject, and select the corresponding prediction part according to the need. Taking a 56-year-old female with a blood pressure of 90/130mmHg as an example, set gender, age and blood pressure in step S201, the collection site is the fingertip, and the target prediction site is the radial artery. In S202, according to the settings, the system automatically selects the TM and CM matrices corresponding to the groups of people and parts according to the grouping situation of the prior statistical rules.

步骤S203中系统开始接收实测波形,步骤S204对输入波形进行调理,滤除基线与工频干扰,将连续波形按照心动周期分离成分立波形,并以波形为单位进行波形幅度与波长的归一化,其中,波长的归一化通过插值的方法实现。In step S203, the system starts to receive the measured waveform, and in step S204, the input waveform is adjusted, the baseline and power frequency interference are filtered out, the continuous waveform is separated into discrete waveforms according to the cardiac cycle, and the waveform amplitude and wavelength are normalized in units of waveforms , where the normalization of the wavelength is achieved by interpolation.

在S205步骤中,根据S203中给定的采集波形拟合表达式,对每一单拍波形利用最小二乘方法进行曲线拟合。In step S205, according to the acquisition waveform fitting expression given in S203, curve fitting is performed on each single-beat waveform using the least square method.

拟合表达式为:The fitting expression is:

设定初始条件。从而获得对应每一单拍波形的II并计算R2Set initial conditions. Thus, I I corresponding to each single-beat waveform is obtained and R 2 is calculated.

在本例中,将波形幅值及波长均分别定义为100单位,则In this example, the waveform amplitude and wavelength are both defined as 100 units, then

II=[Hi1,Hi2,Hi3,bi1,bi2,bi3,Wi1,Wi2,Wi3]=[43,69,49,15,27,48,14,25,52]I I =[H i1 ,H i2 ,H i3 , bi1 ,bi2 ,bi3 ,W i1 , W i2 , W i3 ]=[43,69,49,15,27,48,14,25,52 ]

R2>0.99R 2 >0.99

步骤S206中根据R2数值进行波形质量判断,对R2<0.95的波形予以舍弃,并记录舍弃比例。若出现波形舍弃,重新提取下一拍波形进行分析。通常情况下R2<0.95的波形比例<3%,舍弃比例大于5%时,应考虑调整采集方式。In step S206, the waveform quality is judged according to the value of R 2 , the waveform with R 2 <0.95 is discarded, and the discarding ratio is recorded. If the waveform is discarded, re-extract the next beat waveform for analysis. Generally, the proportion of waveforms with R 2 <0.95 is less than 3%, and when the discarding proportion is greater than 5%, consideration should be given to adjusting the acquisition method.

步骤S207对S206中质量合格波形的II进行转换,计算目标部位波形的特征向量IO,依据公式:Step S207 converts the I I of the qualified waveform in S206, and calculates the eigenvector I O of the waveform of the target part, according to the formula:

IO=TM×II+CMI O =TM×I I +CM

在本例中,TM与CM均由该患者之前同时测得的桡动脉压力脉搏波及指端光电容积脉搏波信号分别根据fi与fo拟合,并由得到的参数分别建立对应的回归方程获得。In this example, both TM and CM are fitted by the radial artery pressure pulse wave and the fingertip photoplethysmography pulse wave signal measured at the same time, according to f i and f o respectively, and the corresponding regression equations are respectively established from the obtained parameters get.

经计算可得:Calculated to get:

IO=[Ho1,Ho2,Ho3,bo1,bo2,bo3,Wo1,Wo2,Wo3]=[64,71,35,14,25,49,13,22,48]I O =[H o1 ,H o2 ,H o3 ,b o1 ,b o2 ,b o3 ,W o1 ,W o2 ,W o3 ]=[64,71,35,14,25,49,13,22,48 ]

步骤S208中将IO中各项参数代入给定的目标部位压力脉搏波表达式,即In step S208 , each parameter in 10 is substituted into the given target site pressure pulse wave expression, namely

得到目标部位预测波形表达式及分别对应的主波,反射波及重搏波预测波形。The predicted waveform expression of the target part and the corresponding main wave, reflected wave and dicrotic wave predicted waveforms are obtained.

步骤S209将上述波形及参数按照指定格式输出。Step S209 outputs the above-mentioned waveform and parameters according to the specified format.

Claims (1)

1. A pressure pulse wave waveform propagation prediction method based on photoplethysmography signals is characterized by comprising the following steps: the device comprises a waveform input module, a signal conditioning module, a waveform fitting module, a waveform conversion module and a waveform output module;
the waveform input module receives a time domain photoelectric volume pulse signal actually measured from a certain part of a human body;
the signal conditioning module is used for preprocessing the input time domain photoplethysmography pulse signals, decomposing the preprocessed time domain photoplethysmography pulse signals into single-beat pulse signals corresponding to a single cardiac cycle, and normalizing the amplitude and wavelength of each single-beat pulse signal;
the waveform fitting module receives the normalized single-beat pulse signal and utilizes a given waveform containing a parameter expression fIFitting the pulse waveform by using a curve fitting algorithm, wherein the parameter-containing expressions of the waveform are determined by adding the parameter-containing expressions respectively representing the main wave, the dicrotic wave and the reflected wave of the pulse waveform, and each parameter vector of the analytical expression obtained by fitting is IIAs a waveform characteristic parameter vector;
the waveform of the photoplethysmography signal contains a reference expression as follows:
wherein Hin,bin,WinIs a parameter, t is an independent variable and represents the number of sampling points; in the expression, the parts of n being 1, 2 and 3 respectively correspond to a main wave, a reflected wave and a dicrotic wave of the pulse wave waveform; wherein HinRepresenting the amplitude of the wave, binIndicating the center position of the wave, WinThe width of the undulations;
the curve fitting process algorithm adopts a least square algorithm, limits each parameter range according to each fluctuation physiological significance, and then sets fitting initial conditions Hi1>Hi2>Hi3,bi1<bi2<bi3,Win>0; fitting the determined characteristic parameter vector IIComprises the following steps:
II=[Hi1,Hi2,Hi3,bi1,bi2,bi3,Wi1,Wi2,Wi3]
under the condition that the waveform contains the parameter expression, the fitting effect mainly depends on the interference degree of pulse wave acquisition, so that the coefficient R is determined by fitting2As the quantification standard for waveform quality discrimination; fitting to determine the coefficient R2The method is a commonly used calculation method for judging the similarity degree of two curves; r2As an acquisition quality discrimination parameter, corresponds to R2A single beat waveform less than a certain value is considered to be sampledCollecting the quality difference and abandoning;
R2the calculation formula is as follows:
wherein,respectively representing an actually measured photoplethysmogram data point, an actually measured photoplethysmogram data average value and a data point fitting expected value, wherein pl is the number of data points of a single-beat pulse signal;
the waveform conversion module is used for grouping according to sex, age and average arterial pressure indexes of a measured person, and calculating and predicting pressure pulse wave waveform characteristic parameters of a corresponding part by utilizing measured photoplethysmography pulse wave characteristic parameters according to a priori statistical rule between the measured part of the photoplethysmography pulse wave and the waveform characteristic parameters of the part of the pressure pulse wave to be predicted under the corresponding grouping;
the method for establishing the prior statistical rule between the waveform characteristic parameters of the actual measurement part of the photoplethysmogram and the part of the pressure pulse wave needing to be predicted under the corresponding grouping comprises the following steps:
(1) firstly, grouping the population participating in the experiment according to gender, age and mean arterial pressure, wherein the age is started at 20 years and is separated from the age at 5 years; mean arterial pressure started at 70mmHg, spaced at 10 mmHg; grouping the population participating in the experiment; respectively and simultaneously detecting photoelectric volume pulse waves at ear, finger and toe positions of each group of experimental population, and detecting pressure pulse wave signals at radial artery, brachial artery and carotid artery positions by using pressure sensors; thereby obtaining actually measured pressure pulse waves and photoplethysmography signals of different crowd characteristics;
(2) then, establishing a statistical relationship between the waveform characteristic parameters of the actually measured photoplethysmogram and the actually measured pressure pulse wave of the target part; similar with above-mentioned photoplethysmography pulse wave waveform characteristic parameter vector extraction mode, for extracting pressure pulse wave waveform characteristic parameter, utilize pressure pulse wave waveform to contain the parameter expression and carry out the fitting to actual measurement pressure pulse wave waveform, pressure pulse wave waveform contains the parameter expression and is:
the expression parameters and the definition domain are all equal to fIThe same; the fitting process algorithm adopts a least square algorithm, limits each parameter range according to each fluctuation physiological significance, and then sets fitting initial conditions Ho1>Ho2>Ho3,bo1<bo2<bo3,Won>0;
The characteristic parameter vector is IO=[Ho1,Ho2,Ho3,bo1,bo2,bo3,Wo1,Wo2,Wo3]
(3) Respectively using f for the measured waveforms of different groups and different partsIAnd fOFitting the actually measured photoplethysmogram waveform and pressure pulse waveform by a waveform fitting module to obtain I corresponding to each actually measured photoplethysmogram signalIAnd I of pressure pulse signalOVector quantity; for each part of the pressure pulse signal IOEstablishing a multiple linear regression equation of the feature parameter vectors of the photoplethysmography signals which correspond to different groups and are acquired simultaneously for each parameter of the vector, namely:
Ho1=TM11×Hi1+TM12×Hi2+......+TM19×Wi3+CM1
Ho2=TM21×Hi1+TM22×Hi2+......+TM29×Wi3+CM2
Ho3=TM31×Hi1+TM32×Hi2+......+TM39×Wi3+CM3
bo1=TM41×Hi1+TM42×Hi2+......+TM49×Wi3+CM4
bo2=TM51×Hi1+TM52×Hi2+......+TM59×Wi3+CM5
bo3=TM61×Hi1+TM62×Hi2+......+TM69×Wi3+CM6
Wo1=TM71×Hi1+TM72×Hi2+......+TM79×Wi3+CM7
Wo2=TM81×Hi1+TM82×Hi2+......+TM89×Wi3+CM8
Wo3=TM91×Hi1+TM92×Hi2+......+TM99×Wi3+CM9
each coefficient of TM and CM is determined by multiple linear regression equation; finishing IOEstablishing an equation set by each parameter, and sorting a coefficient matrix and a constant matrix to obtain TM and CM, wherein TM is a 9-order square matrix, and CM is a 9-element column vector;
according to the TM and CM matrixes obtained by using the prior probability, in the application process, the waveform characteristic parameter vector I of the collected part is usedICalculating a feature parameter vector I of the target regionO(ii) a Extracting characteristic I from the measured photoplethysmographyIObtaining the characteristic parameter vector I of the target partOComprises the following steps:
IO=TM×II+CM
then obtaining the target part characteristic parameter vector IOSubstituting into the corresponding part of the pressure pulse waveform containing parameter expression fOObtaining a corresponding pressure pulse wave analytic expression; completing the waveform conversion;
the waveform output module converts the result of the waveform conversion module and the characteristic parameter vector I of the target partOAnd outputting according to a required form.
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