王學(xué)民,郭 丹,王 欣,陸小左,周 鵬
(1. 天津大學(xué)精密儀器與光電子工程學(xué)院,天津 300072;2. 天津市生物醫(yī)學(xué)檢測(cè)技術(shù)與儀器重點(diǎn)實(shí)驗(yàn)室,天津 300072;3. 天津中醫(yī)藥大學(xué)中醫(yī)工程學(xué)院,天津 300193)
多部脈象信息采集及處理
王學(xué)民1,2,郭 丹1,王 欣1,陸小左3,周 鵬1,2
(1. 天津大學(xué)精密儀器與光電子工程學(xué)院,天津 300072;2. 天津市生物醫(yī)學(xué)檢測(cè)技術(shù)與儀器重點(diǎn)實(shí)驗(yàn)室,天津 300072;3. 天津中醫(yī)藥大學(xué)中醫(yī)工程學(xué)院,天津 300193)
基于中醫(yī)三部脈象儀,探究一種新的多部脈象采集方法及各部之間的影響,提出一種新的脈象信號(hào)時(shí)域特征提取法NILP.通過(guò)小波高頻去噪和基于三次樣條插值的LIP算法對(duì)寸、關(guān)、尺三部脈象信號(hào)預(yù)處理.利用NILP、譜能比、小波熵和HHT提取時(shí)頻域上的多個(gè)特征參數(shù).結(jié)果發(fā)現(xiàn),寸部信號(hào)隨著尺部壓力的增大,時(shí)域平滑化,頻域高頻成分減少;尺部信號(hào)隨著寸部壓力的增大,時(shí)域陡化,頻域高頻成分增加;寸關(guān)尺最佳取脈壓力存在定量關(guān)系.這種影響關(guān)系表明單部采集與多部采集存在較大差異,應(yīng)通過(guò)臨床樣本的積累,逐步建立符合三部脈象檢測(cè)規(guī)律的脈象判讀標(biāo)準(zhǔn).
中醫(yī)脈象;最佳取脈壓力;NILP;HHT
中醫(yī)脈診是中醫(yī)理論的重要組成部分,三部九侯診法[1]是我國(guó)中醫(yī)自古以來(lái)脈診所使用的一套方法,辯證辨病,九侯相參,體現(xiàn)了中醫(yī)整體觀思想.經(jīng)過(guò)多年的發(fā)展,中醫(yī)脈象儀及脈象分析在理論和臨床應(yīng)用上已經(jīng)取得了巨大的進(jìn)步.目前已經(jīng)建立了單部脈象判斷標(biāo)準(zhǔn),模擬三部九侯的三部脈象儀硬件基礎(chǔ)發(fā)展成熟,但是完全體現(xiàn)三部九侯思想的多部脈象標(biāo)準(zhǔn)尚未出爐,而且三部脈象儀如何實(shí)現(xiàn)多部壓力控制尚在探索中.因此,本文首先探索一種新的三部脈象信號(hào)采集方法,通過(guò)傳感器梯度加減壓模擬手指切脈壓力變化,利用三部傳感器模擬中醫(yī)師三部九侯診法.目前對(duì)于寸關(guān)尺一部壓力變化對(duì)另兩部脈象信號(hào)影響的研究處于定性分析階段,本文通過(guò)信號(hào)處理的時(shí)、頻域特征提取對(duì)此做出了定量分析.該定量分析為三部脈象儀采集的壓力控制提供更好的方案,也為多部脈象判斷標(biāo)準(zhǔn)作出一定參考,有利于促進(jìn)中醫(yī)現(xiàn)代化發(fā)展.
1.1實(shí)驗(yàn)設(shè)備及采集說(shuō)明
本文數(shù)據(jù)來(lái)源基于天津大學(xué)精密儀器與光電子工程學(xué)院中醫(yī)工程實(shí)驗(yàn)室自主研發(fā)的袖帶式中醫(yī)三部快速采集脈象儀.三部快速采集脈象儀系統(tǒng)框圖如圖1所示.
圖1 三部脈象儀系統(tǒng)框圖Fig.1 System block diagram of three-portion pulse collection instrument
本系統(tǒng)使用的袖帶式脈搏傳感器集加減壓和信號(hào)采集于一體,模擬中醫(yī)師手指切脈,通過(guò)獨(dú)立氣囊及氣動(dòng)加減壓模塊改變傳感器探頭對(duì)腕部的壓力.此系統(tǒng)可以實(shí)現(xiàn)多種加減壓模式,本文中采用快速加壓連續(xù)減壓模式,即傳感器壓力快速增大到一定值后,壓力緩慢連續(xù)減小.這種采集方式精確度高,相較于前人通過(guò)梯度加壓得到的最佳取脈壓力及多部脈象采集影響[2]準(zhǔn)確性提高.
1.2實(shí)驗(yàn)方案
本文所用數(shù)據(jù)的采集對(duì)象為天津大學(xué)精密儀器與光電子工程學(xué)院的20名大學(xué)生,均體檢正常,年齡在20~25歲之間.
統(tǒng)一檢測(cè)部位為被試者的左手腕部.先用手指找到安靜端坐于儀器前的被試者的寸、關(guān)、尺,用筆標(biāo)示.根據(jù)實(shí)驗(yàn)方法,將相應(yīng)數(shù)目的傳感器探頭準(zhǔn)確地固定在相應(yīng)部位.具體步驟如下:
(1)分別以連續(xù)減壓方式采集寸、尺部脈象信號(hào);
(2)尺部連續(xù)減壓,采集保持在最佳取脈壓力下的寸部信號(hào);
(3)寸部施加80克力的恒力,尺梯度加壓(40→80→120→160克力),每個(gè)壓力梯度寸部采集1,min;
(4)寸部連續(xù)減壓,采集保持在最佳取脈壓力下的尺部信號(hào);
(5)尺部施加100克力的恒力,寸梯度加壓(40→80→120→160克力),每個(gè)壓力梯度尺部采集1,min.
通過(guò)提取脈象信號(hào)特征參數(shù)分析影響,本文主要介紹NILP(new intersection points of lines and pulse waveform)算法和HHT(Hilbert-Huang transform)法.
2.1NILP算法
NILP算法是對(duì)王鵬[2]提出的提取脈象時(shí)域特征ILP算法的改進(jìn).NILP能準(zhǔn)確地找出各個(gè)特征點(diǎn),準(zhǔn)確性高,且具有抗噪性.其原理是不同高度直線與單個(gè)周期脈象信號(hào)交點(diǎn)個(gè)數(shù)不同,特征點(diǎn)前后交點(diǎn)個(gè)數(shù)發(fā)生突變,如圖2所示.根據(jù)此特點(diǎn),交點(diǎn)個(gè)數(shù)數(shù)組前后相減,不為零處即為特征點(diǎn),因精度所限差值一般為2.得到的特征點(diǎn)數(shù)組順序?qū)?yīng)H4、H5、H2、H3、H1,如圖3所示,然而對(duì)于圖4所示的非標(biāo)準(zhǔn)脈象,會(huì)出現(xiàn)特征點(diǎn)誤判為H4、H2、H3、H5、H1,本文根據(jù)特征點(diǎn)時(shí)間順序糾正誤判錯(cuò)誤.
圖2 NILP算法原理Fig.2 Principle of NILP algorithm
圖3 標(biāo)準(zhǔn)信號(hào)及其與直線交點(diǎn)個(gè)數(shù)Fig.3 Standard signal and its node number with line
圖4 非標(biāo)準(zhǔn)信號(hào)及其與直線交點(diǎn)個(gè)數(shù)Fig.4 Non-standard signal and its node number with line
將脈象信號(hào)歸一化到0~1之間.經(jīng)過(guò)大量實(shí)驗(yàn)發(fā)現(xiàn)直線移動(dòng)步進(jìn)為0.000,01時(shí)效果最理想.在此基礎(chǔ)上,步進(jìn)減小1個(gè)數(shù)量級(jí),同長(zhǎng)度的數(shù)據(jù)處理時(shí)間增加幾十秒.步進(jìn)增加1個(gè)數(shù)量級(jí),遺漏某些特征點(diǎn).因?yàn)閿?shù)據(jù)為離散的數(shù)值點(diǎn),而且直線移動(dòng)步進(jìn)為0.000,01,不可能得到與直線的交點(diǎn).因此,設(shè)置1個(gè)閾值,當(dāng)脈象信號(hào)的數(shù)值與直線數(shù)值的差值小于此閾值時(shí)認(rèn)為兩者相交.經(jīng)大量實(shí)驗(yàn),判斷脈象信號(hào)與直線相交的閾值為步進(jìn)的10倍.圖5為NILP算法提取特征效果圖,從圖5可知此算法可以準(zhǔn)確提取單、雙、三波峰信號(hào)的特征點(diǎn).
圖5 NILP算法效果Fig.5 Renderings of NILP algorithm
2.2HHT原理
HHT[3]近年來(lái)發(fā)展應(yīng)用勢(shì)頭迅猛,應(yīng)用于醫(yī)學(xué)、工程、地球、海洋等多個(gè)領(lǐng)域.1998年,美國(guó)華裔科學(xué)家Norden E Huang提出HHT,適用于非線性非平穩(wěn)信號(hào)的分析研究,解決了時(shí)頻分辨率相互制約的難題.傅里葉變換是將信號(hào)分解為多個(gè)正余弦函數(shù)的疊加,小波變換是將信號(hào)分解為多個(gè)小波基函數(shù)的疊加,同理,HHT是用經(jīng)驗(yàn)?zāi)B(tài)分解法將信號(hào)分解為多個(gè)本征模態(tài)函數(shù)(IMF)的疊加.時(shí)頻能量分布圖根據(jù)IMF分量的希爾伯特變換得到.
EMD分解法認(rèn)為所有信號(hào)都由IMF分量組成.IMF必須滿足兩個(gè)條件:①其極值點(diǎn)與過(guò)零點(diǎn)的個(gè)數(shù)相同或最多相差1個(gè);②其極大極小值包絡(luò)線關(guān)于時(shí)間軸局部對(duì)稱(chēng).EMD分解信號(hào),當(dāng)滿足一定條件時(shí),得到1個(gè)IMF分量,當(dāng)最后1個(gè)IMF即殘差為單調(diào)函數(shù)時(shí),分解停止,得到該信號(hào)的EMD分解集IMF.對(duì)IMF分量X(t)做希爾伯特變換:
式中PV為柯西主值.
將IMF集的希爾伯特變換整理為式(2),即可得到信號(hào)的時(shí)頻分布圖.
式中n為EMD分解集IMF的個(gè)數(shù).
對(duì)希爾伯特譜H(w,t)時(shí)間積分可得到邊際譜圖,即
邊際譜能較準(zhǔn)確地反映信號(hào)的實(shí)際頻率成分.
脈象信號(hào)是弱生理信號(hào),采集時(shí)受到工頻、被試呼吸體動(dòng)等影響,因此首先對(duì)實(shí)驗(yàn)數(shù)據(jù)進(jìn)行高頻小波去噪[4-6]和基于LIP算法的三次樣條差值基線糾飄.
3.1最佳取脈壓力
中醫(yī)師在切脈時(shí),會(huì)不斷地調(diào)整切脈壓力,直至脈動(dòng)應(yīng)指最強(qiáng)烈,最佳取脈壓力大小因人而異.對(duì)這種壓力調(diào)整,研究者在數(shù)學(xué)上提出了血管的最佳取脈壓力數(shù)學(xué)模型[7],說(shuō)明并驗(yàn)證了最佳取脈壓力的存在.湯偉昌等[8]根據(jù)不同壓力段尋找最佳取脈壓力,本文以快速加壓連續(xù)減壓方式采集單部脈象信號(hào),壓力值可精確到1,g,準(zhǔn)確度大大提高.如圖6所示,根據(jù)NILP算法提取每個(gè)脈動(dòng)周期的主波峰峰值H1及其對(duì)應(yīng)壓力,對(duì)壓力-H1的散點(diǎn)圖進(jìn)行擬合,如圖7所示,即可精確地得到最佳取脈壓力.
圖6 連續(xù)減壓方式所得脈象信號(hào)及峰值Fig.6 Pulse signal and its peakcollected with the way of continuous reducing pressure
圖7 壓力-峰值散點(diǎn)圖及其擬合曲線Fig.7 Pressure-peak scatterplot and its fitting curve
本實(shí)驗(yàn)采集被試者的左手寸口各部最佳取脈壓力,根據(jù)被試實(shí)驗(yàn)時(shí)的配合程度,篩選出每個(gè)被試最有效的數(shù)據(jù)組,共20組數(shù)據(jù),統(tǒng)計(jì)方法為t檢驗(yàn),三部最佳取脈壓力統(tǒng)計(jì)結(jié)果如表1所示.
表1 寸、關(guān)、尺最佳取脈壓力統(tǒng)計(jì)結(jié)果Tab.1Statistical result of cun-guan-chi best feeling pressure
圖8為20名被試者的最佳取脈壓力(即壓力最大值)關(guān)系.根據(jù)寸、關(guān)、尺生理解剖結(jié)構(gòu),尺部最低,關(guān)部最高,寸部居中,所以要取得尺部脈象信號(hào)需要施加更大的力.據(jù)此,可解釋三部最佳取脈壓力的大小關(guān)系,且三者有顯著性差異.最佳取脈壓力大小存在個(gè)體性差異.前10例被試為女性,后10例為男性.結(jié)果表明男性的脈動(dòng)較女性更強(qiáng)烈,經(jīng)t檢驗(yàn)兩者有顯著性差異.
圖8 三部最佳取脈壓力關(guān)系Fig.8 Relationship of cun-guan-chi best feeling pressure
3.2尺對(duì)寸的影響
圖9為20名被試者的均值,圖10為某名被試者的數(shù)據(jù)結(jié)果.分析圖9、10的結(jié)果,根據(jù)人體的血管特性及手部解剖結(jié)構(gòu),先開(kāi)始加壓時(shí),尺部血管橫截面變小,單位時(shí)間流過(guò)的血液量減少,所以寸部脈象信號(hào)主波峰峰值h1減小.尺部壓力增大到120 克力時(shí),經(jīng)掌弓通道[9]流來(lái)的血液受到尺部的阻擾,聚集在寸部,所以寸部脈象信號(hào)h1有一個(gè)小上升,但其幅值不會(huì)超過(guò)尺部不加壓時(shí)寸部的信號(hào)幅值.尺部的壓力再增大完全阻斷了尺部前后的血流通道,橈動(dòng)脈的血液不再對(duì)寸部脈象信號(hào)起作用,所以寸部脈象信號(hào)幅值又有所下降.升支時(shí)間t1沒(méi)有產(chǎn)生顯著性差異.根據(jù)h1和t1可知尺部加壓時(shí)寸部信號(hào)時(shí)域平滑化,圖10是信號(hào)變化的直觀反映.
圖9 尺部壓力對(duì)寸部信號(hào)影響之特征趨勢(shì)Fig.9 Characteristics trend of cun signal caused by chi pressure
圖10 不同尺壓下寸部信號(hào)對(duì)比Fig.10 Comparison of cun signals under different chi pressures
對(duì)于圖9中代表信號(hào)頻率復(fù)雜程度的小波熵S、代表0~3,Hz信號(hào)譜能比的E的變化,認(rèn)為尺部無(wú)壓力時(shí),寸部有大、中動(dòng)脈連接,與血液循環(huán)中樞的流阻較小.當(dāng)尺部壓力逐漸增大,寸部與主動(dòng)脈的通道被阻斷,此時(shí)寸部主要反映手部外周血液循環(huán),它與血液循環(huán)中樞的流阻較大,因此高頻成分減少.
3.3寸對(duì)尺的影響
寸開(kāi)始加壓時(shí),寸部血管橫截面變小,單位時(shí)間流過(guò)的血液量減少,橈動(dòng)脈流來(lái)的血液受到寸部的阻擾,聚集在尺部,沖擊尺部血管使得h1變大.寸部的壓力再增大就完全阻斷了寸部前后的血流通道,掌弓旁路作用失效,尺動(dòng)脈的血液不再對(duì)尺部脈象信號(hào)起作用,所以尺部信號(hào)峰值有所下降.t1單調(diào)減小,將血管模型看成彈性水管,當(dāng)流速流量不變時(shí),在某點(diǎn)處逐漸阻斷,在其前方會(huì)有水流聚集,當(dāng)完全阻擋時(shí)聚集的水流最多,對(duì)水管壁的沖擊最大,水管壁達(dá)到最大形變的時(shí)間也最小.根據(jù)h1和t1可知寸部加壓時(shí)尺部信號(hào)時(shí)域陡化,圖11是信號(hào)變化的直觀反映.
圖11 不同寸壓下尺部信號(hào)對(duì)比Fig.11Comparison of chi signals under different cun pressures
圖12 寸部壓力對(duì)尺部信號(hào)影響之特征趨勢(shì)Fig.12 Characteristics trend of chi signal caused by cun pressure
關(guān)于圖12結(jié)果,小波熵表示頻率分布的集中程度,因此意味著隨著寸壓的增大,尺部信號(hào)的頻率成分分布變大.由圖13可知,重搏前波和重搏波的頻率范圍高于3.5,Hz.從圖11可知,隨著寸壓的增大,尺部脈象信號(hào)的重搏前波由不明顯變明顯,因此高頻成分增加.對(duì)應(yīng)于小波熵S的增大和0~3,Hz譜能比的下降.
圖13 脈搏波及其希爾伯特譜Fig.13 Pulse wave and its Hilbert spectrum
本文基于三部脈象快速采集系統(tǒng),依照中醫(yī)師三部九侯脈診法,設(shè)計(jì)了實(shí)驗(yàn)采集方案.改進(jìn)ILP算法,通過(guò)提取、分析時(shí)頻域特征參數(shù),得到精確化的三部最佳取脈壓力及其關(guān)系,同時(shí)初步得到寸口之間的影響關(guān)系,即不同部位施壓對(duì)另一部的時(shí)頻特征會(huì)產(chǎn)生不同的影響.中醫(yī)認(rèn)為寸口六部分別對(duì)應(yīng)不同的臟器,各個(gè)臟器有各自的固有頻率[10],寸口受相應(yīng)臟器生物全息律[11]的調(diào)控,按壓一部會(huì)引起周?chē)M織的變化,所以寸對(duì)尺和尺對(duì)寸的影響不同.因此,在中醫(yī)脈象多部采集的客觀化過(guò)程中,需要綜合寸口各部的信息,同時(shí)逐步建立多部脈象判別標(biāo)準(zhǔn),此過(guò)程依賴(lài)于大量數(shù)據(jù)分析,本文對(duì)該過(guò)程進(jìn)行了初探.
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(責(zé)任編輯:趙艷靜)
Acquisition and Processing of Multi-Portion Pulse Information
Wang Xuemin1,2,Guo Dan1,Wang Xin1,Lu Xiaozuo3,Zhou Peng1,2
(1.School of Precision Instrument and Opto-Electronics Engineering,Tianjin University,Tianjin 300072,China;2.Tianjin Key Laboratory of Biomedical Instrument and Detection Technology,Tianjin 300072,China;3.School of Traditional Chinese Medicine Engineering,Tianjin University of Traditional Chinese Medicine,Tianjin 300193,China)
Based on the cun-guan-chi pulse acquisition instrument,a new method for multi-channel pulse acquisition was explored in this paper,and the effect of pulse condition information varying withsingle sensor pressure of other departments was studied.Moreover a new method named NILP(new intersection points of lines and pulse waveform)was proposed.LIP(lowest point in one period)algorithm based on cubic spline interpolation and wavelet transform was used to preprocess cun-guan-chi signals.The multiple features of time and frequency domain parameters were extracted by NILP,spectral ratio,the wavelet entropy and HHT(Hilbert-Huang transform).The results show that increasing pressure in chi results in the smoothing phenomenon in time domain of cun and the decreasing of high frequency components in frequency domain of cun.For chi,with the increasing pressure in cun,steep phenomenon occurs in time domain,and high frequency components increase.There exists a quantitative relationship for cunguan-chi best feeling pressure.The effect relationship indicates that there is a great difference between single-portion and multi-portion pulse acquisitions,and it is essential to establish a standard for three-portion pulse by the accumulation of clinical samples.
pulse in Chinese medicine;best feeling pressure;NILP;HHT
R318.01
A
0493-2137(2016)05-0541-07
10.11784/tdxbz201412014
2014-12-05;
2015-06-07.
國(guó)家自然科學(xué)基金資助項(xiàng)目(51377120,51007063,31271062,81173202);天津市自然科學(xué)基金資助項(xiàng)目(13JCQNJC 13900).
王學(xué)民(1961—),男,博士,副教授,xueminw@tju.edu.cn.
周 鵬,zpzp@tju.edu.cn.
網(wǎng)絡(luò)出版時(shí)間:2015-07-03. 網(wǎng)絡(luò)出版地址:http://www.cnki.net/kcms/detail/12.1127.N.20150703.1621.001.html.