基于小波变换的充气法测量血压的算法研究

目的探索腕部充气测量血压的方法及原理,实现小波变换提取脉搏波以及无创血压的计算,为现有腕式电子血压计提供更精确的算法。方法采用小波变换对采集的袖带脉搏压力混合信号进行去噪处理,并分离脉搏波与袖带压。在此基础上采用差分法与阈值法寻找脉搏波峰值点并修正波形干扰点,再对脉搏波峰值点进行高斯曲线拟合法拟合出平滑包络线,并采用改进的幅度系数法进行收缩压、舒张压的计算,并对30名测试者用本方法与听诊法进行对比测试,观察相关性。结果该方法的测试结果与听诊法对比相关性良好,测量血压速度快,舒适度高。结论基于小波变换的充气法测量血压的算法相比传统方法去噪效果好,脉搏波提取精确度高,血压计算结果符合AAMI标准,但需在软件处理算法中做进一步简化研究。     

基于脉搏波特征参数的无创血压测量改进算法

解决目前利用脉搏波特征参数无法准确计算出病理及生理血压(高血压、低血压和正常血压)的问题。利用主成分分析得到脉搏波主成分参数,利用脉搏波主成分参数和血压进行线性回归得到初步血压计算模型,借助较大的数据库和逐步逼近法建立多级模型,提高模型计算值的精度。改进后的算法能够使用脉搏波特征参数建立普适的血压计算模型,计算出的血压值精度较高。本研究提出的基于脉搏波特征参数的无创血压测量改进算法能够有效扩大血压计算范围,实现包括高血压、低血压和正常血压在内的无创血压测量。     

基于手指压力示波法的血压测量系统设计

我国高血压患病人数在不断上升,而市场上基于示波法的电子血压计在测量时需袖套辅助。鉴于此,我们设计一种基于手指压力示波法的无袖套血压测量系统。通过手指按压传感器来改变手指内动脉所受压力,并以此改变血管容积,测量出施加的压力和光电容积脉搏波信号。采用双高斯拟合方法,建立光电容积脉搏波信号、施加压力与血压之间的模型关系,计算出人体的血压值。系统采集了24例志愿者的血压数据,与欧姆龙电子血压计测量的血压值进行对比分析;两组数据的收缩压相关性为0.841,标准差为6.78 mmHg;舒张压相关性为0.809,标准差为4.91 mmHg。通过手指压力示波法测量血压是一种可行的方案,它为血压测量装置的小型化、移动医疗及全民健康服务提供了一种思路。     

基于DSP的血压计设计与实现

设计一种基于(DSP)的、带USB接口的大容量存储的电子血压计.该系统充分利用TMS320VC5402的片内外资源和结合电源管理的设计,使系统具有低功耗、便携式的特点.通过USB与PC机进行数据传送实现血压信息的远程监控,触摸屏的运用使操作更加简单.利用示波法测量血压值,经过校正后得到准确的血压测量值,温度补偿算法使得...     

用有创血压验证示波法测量血压的准确性

本文用山羊有创血压作对比研究了示波法无创测量血压的准确性.示波法一般通过袖带放气过程中脉搏波包络线顶点来估计平均压,而用幅度系数算法来估计收缩压和舒张压.虽然示波法能提供较为准确的平均压,但是估计收缩压和舒张压却存在较大误差.用5只山羊进行了试验,以研究幅度系数在不同个体之间的变异性.在用示波法测量山羊血压的同时记录山羊的有创血压.根据放气过程中的袖带内脉搏波包络线和用有创法得到的收缩压和舒张压,计算出每只羊的幅度系数.结果显示5只羊的幅度系数呈现出较大的离散性.究其根源在于,幅度系数法采用的系数是用统计方法得到的,它针对群体而不是个体,是一种经验算法.采用幅度系数算法的示波法血压测量技术不够准确,必须寻找一种新的血压测量方法.     

基于多脉搏波参数的人体血压检测的研究

为了提高可穿戴设备中血压测量的准确性,本文提出了一种基于多脉搏波参数的人体血压检测方法,该方法通过对脉搏传输时间(PWTT)、每搏心输出量、波形系数、升支平均斜率、脉率等多脉搏波参数的多元线性回归分析,建立了基于多脉搏波参数的人体血压计算模型,利用该模型计算出血压值;以心音信号为参考计算PWTT(PWTTPCG),克服了以心电信号为参考计算PWTT(PWTTECG)需要更换电极、有导连线穿戴不方便的不足。分别对基于PWTTPCG和多脉搏波参数的人体血压计算模型计算血压进行了实验验证,实验结果表明利用PWTTPCG作为PWTT计算人体血压的可行性;利用该模型计算的收缩压和舒张压的平均误差分别为1.62 mm Hg和1.12mm Hg,较单一参数分别提高了57%和53%,具有较高的测量精度。     

柯氏音法与示波法相结合的新型血压测量仪研究

为提高电子血压计的准确性,研制出将柯氏音法与示波法结合的新型血压测量装置.首先在研究测量过程和信号处理方法的基础上,设计基于驻极体麦克风和电容式压力传感器的电子血压计系统架构;再利用柯氏音和脉搏波的密切相关性,建立基于统计规律的时域窗函数对柯氏音声强信号进行选择性放大,并设计相关实验验证了该方法的有效性;然后提出利用柯氏音法准确性和示波法稳定性的血压值综合求算逻辑.通过初步测试实验和分析,证实了该装置测量结果具有较高的准确性和稳定性.研究表明,利用柯氏音与脉搏波的关系进行综合信号处理和血压值测算,有望获得高准确性的血压自动测量方法.     

基于形态分量分析和集合经验模态分解的心电信号工频干扰消除法

针对心电信号(ECG)在采集和转换的过程中容易受到工频干扰(PLI)的问题,提出了一种基于形态分量分析(MCA)和集合经验模态分解(EEMD)的PLI消除新算法。首先根据ECG特征波形的形态差异性,利用MCA将其分解为突变成分、平滑成分和残余白噪声成分,然后对含PLI的平滑成分进行EEMD,再滤除PLI的本征模态函数(IMF),最后重构ECG信号。文中采用噪声抑制率(NSR)和信号失真率(SDR)来评价算法的降噪效果。通过实验发现,该算法不仅能够有效地滤除工频干扰,而且SDR值较小,滤波效果优于改进的Levkov算法。     

R波相关振动法血压测量

为了提高振地血压测量的准确性，提出了一咱基于心电Ｒ波与血压振动波之间相关性，识别振动信号的一种抗干扰方法＝－Ｒ波相关法，结合振动波形特征识别，该方法可有效地提取信号，消除干扰影响，该算法已在１６位８０９８单片机上实现，本文同时给出了程序的详细流程图。     

基于SVR的桡动脉血压预测

目的现有的电子血压计主要使用示波法及示波改进法等方法进行血压判定。当患者体征不同时,其脉搏波形也各不相同,可能无法找到脉搏波形中对应的血压值点。本文拟根据临床采集到的桡动脉脉搏波数据使用支持向量回归(support vector regression,SVR)的方法完成与之相对应的血压的预测。方法使用欧姆龙血压计采集到的6581个任意波形的血压样本作为实验数据,其中约3/4样本作为训练集。SVR利用血压样本统计信息进行血压预测。结果实验中95%以上测试样本的收缩压和舒张压误差在[-3%,3%]以内,这表明SVR能够很好地对各类波形样本对应的血压值进行预测。结论使用SVR进行任意波形脉搏波的血压预测是可行且有效的,可以用于桡动脉处血压值的预测。     

Implication of the systolic hump in systemic arterial pressure waves

The systolic hump in the aortic blood pressure wave is defined as the aorticresistance component proportional to the aortic blood flow superimposed on the windkessel component. An electrical analogue comprising a series resistance (aortic resistance) plus a resistance (peripheral resistance) and capacitance (aortic compliance) in parallel (i.e. windkessel component) is used for analysis. Curve fitting using the leastsquares method is performed on calculated and measured blood pressure waves from dogs under haemodynamical conditions induced by infusion of three drugs (noradrenaline, isoproterenol and acetylcholine). The curve fitting RMS (root mean square) errors are <3% for blood pressure waves and <30% for blood flow waves, with good agreement between measured and calculated blood flow waveforms. Infusion of noradrenaline and acetylcholine is found to induce a significant decrease and increase in the aortic resistance, respectively. Although only a small fraction of the blood pressure wave, the systolic hump has a marked effect on the systolic pressure waveform.     

基于扩展卡尔曼滤波和奇异值分解算法的单通道胎儿心电提取方法

提出一种将扩展卡尔曼滤波(EKF)算法和奇异值分解(SVD)算法相结合的单通道胎儿心电提取方法。首先,建立母体心电的动态模型,利用该模型通过扩展卡尔曼滤波或扩展卡尔曼平滑(EKS),从孕妇的单通道腹部信号中估计出母体心电成分,然后与单通道腹部信号相减得到胎儿心电信号的初步估计,随后再利用奇异值分解算法,对初步估计出的胎儿心电信号进行去噪处理,以期得到高信噪比的胎儿心电信号。另外,针对胎儿心律不齐的情况,在奇异值分解算法中提出一种改进的心电信号重构矩阵构造方法。对合成腹部信号和实际腹部信号(源于DaISy数据库和PhysioNet中的非侵入式胎儿心电数据库,共计49个腹部通道的数据),进行胎儿心电提取实验。结果表明,使用EKF+SVD或EKS+SVD的算法比单独使用EKF或EKS的算法,提取出的胎儿心电信号的信噪比提高约5 dB,胎儿心电提取的准确性分别达95.60%和95.94%。结合EKF和SVD算法的单通道胎儿心电提取方法,可以有效地提高胎儿心电信号的信噪比和提取的准确性,并且适用于母体或胎儿心律不齐的情况。     

Ransacking the curve of cardiac isovolumic pressure decay by logistic-and-oscillation regression

The decelerative part of the left ventricular isovolumic pressure decay is an important phase to make the heart ready for diastolic refill (lusitropy). Its widely used characterization by an exponential regression with zero pressure asymptote or coestimated asymptote provides empirically biased time constant estimates because of significant deviations of the pressure decay from exponentiality. We systematically analyzed the regression residua of these pressure decays in isolated ejecting rat, guinea pig, and ferret hearts. A four-parametric logistic (tangens hyperbolicus) function, together with a superimposed acustomechanic oscillation, yields normally distributed residua with standard regression error typically less than one per cent of the initial pressure; this is the first model with proved unbiased and statistically complete regressive extraction of the information provided by the time course of pressure decay. Equal values of the lusitropic parameters (logistic time constant and pressure asymptote) were estimated even after the oscillatory component was removed from the regression model. Reliable estimates of the frequency, but not of the amplitude, can be obtained by fitting the oscillation model to the residua provided by the logistic; this two-step method is statistically weaker than the full one-step model, but it reduces computational effort. In conclusion, the four-parametric logistic, but not a three-parametric exponential or logistic model, suffices to obtain unbiased lusitropic parameters characterizing the left ventricular isovolumic pressure decay of small animal hearts.     

Reduction of somatosensory evoked fields in the primary somatosensory cortex in a one-back task

In the present study, responses of the somatosensory cortex to sensory input of ten human volunteers were investigated during a one-back task with different conditions of attention. During an condition of attention subjects were requested to detect a predefined sequence of tactile stimuli applied to two different fingers of the dominant hand while a series of visual stimuli was presented simultaneously with an asynchronous stimulus-onset to the tactile stimuli. During an condition of distraction subjects received the identical series of visual and tactile stimuli like in the condition of attention but were now requested to detect a predefined stimulus sequence within the visual stimulus domain. In both conditions, somatosensory evoked magnetic fields (SEFs) to the tactile stimuli were recorded by means of a 31-channel magnetoencephalograph (MEG) from subjects‘ contralateral primary somatosensory cortex. The mean global field power, the dipole strength, the maximum current density, and the first component of the singular value decomposition (SVD) of magnetic fields were used to compare early components of the SEF in the conditions of attention versus distraction. Surprisingly, results revealed significant decreases of measures of all four parameters during the condition of attention as compared to the condition of distraction indicating that early responses of the primary somatosensory cortex became significantly reduced in the condition of attention. We hypothesize that changes in the centre-periphery-relationship of receptive fields in the primary somatosensory cortex may account for this unexpected result.     

MRI超短回波时间成像序列结合T2*映射技术用于在体耳软骨无创检测

提出使用磁共振图像(MRI)超短回波时间(UTE)成像序列结合T2*映射技术, 对耳软骨T2*值进行在体无创检测, 探究既能对耳软骨进行非侵入性成像又能定量评估在体耳软骨生物成分的方法, 为耳软骨再造和修复整形手术评价的标准化提供新思路。首先, 使用1个UTE和5个短回波时间(TE)的成像组合序列采集30名志愿者右侧外耳的MRI图像;然后, 利用采集到的每名志愿者的图像进行组内刚性配准及手动分割耳软骨与外耳轮廓(包含耳软骨及周围组织, 如皮肤、脂肪和其他软组织)的预处理;接下来, 分别运用单指数和双指数衰减模型在分割出来的耳软骨和外耳区域进行T2*值测量;最后, 分别使用这两种模型拟合耳软骨信号强度随回波时间变化的衰减曲线, 并比较拟合模型的准确性。结果显示, 在30例右耳的单成分分析(单指数模型)实验中, 外耳的T2*_m平均值为(49.269±16.979)ms, 耳软骨的T2*_m平均值为(23.799±9.629)ms。在双成分分析(双指数模型)中, 外耳的短成分T2*_s平均值为(11.713±3.111)ms, 长成分T2*_l平均值为(65.128±13.132)ms, 耳软骨的短成分T2*_s平均值为(5.577±1.830)ms, 长成分T2*_l平均值为(30.628±8.413)ms。统计分析显示, 单成分分析计算得到的T2*_m, 和双成分分析计算得到的T2*_s、T2*_l, 在外耳和耳软骨区域均存在显著差异(P <0.05)。在曲线拟合中, 双指数模型优于单指数模型(R²[bi]=0.999±0.001 vs R²[mono]=0.905±0.014, P<0.05)。实验结果表明, 超短回波时间成像序列结合T2*映射技术对在体耳软骨进行T2*值无创检测具备可行性, 有望为软骨组织工程和3D生物打印技术制作的耳软骨-支架复合物应用在耳廓修复和再造中提供医学影像学的支撑, 也为小耳畸形外科整形手术术后定量评估耳软骨提供一种可行性方案。     

单次事件相关电位聚类分析

本文用模糊神经网络对意境欠事件相关电位进行聚类分析，并提出应用奇异值分解确定最佳聚类数的通用新方法，结果显示它们构成了提取和压缩ＳＥＲＰ动态信息的有效方法 。     

CEST signal at 2 ppm (CEST@2ppm) from Z‐spectral fitting correlates with creatine distribution in brain tumor

In general, multiple components such as water direct saturation, magnetization transfer (MT), chemical exchange saturation transfer (CEST) and aliphatic nuclear Overhauser effect (NOE) contribute to the Z‐spectrum. The conventional CEST quantification method based on asymmetrical analysis may lead to quantification errors due to the semi‐solid MT asymmetry and the aliphatic NOE located on a single side of the Z‐spectrum. Fitting individual contributors to the Z‐spectrum may improve the quantification of each component. In this study, we aim to characterize the multiple exchangeable components from an intracranial tumor model using a simplified Z‐spectral fitting method. In this method, the Z‐spectrum acquired at low saturation RF amplitude (50 Hz) was modeled as the summation of five Lorentzian functions that correspond to NOE, MT effect, bulk water, amide proton transfer (APT) effect and a CEST peak located at +2 ppm, called CEST@2ppm. With the pixel‐wise fitting, the regional variations of these five components in the brain tumor and the normal brain tissue were quantified and summarized. Increased APT effect, decreased NOE and reduced CEST@2ppm were observed in the brain tumor compared with the normal brain tissue. Additionally, CEST@2ppm decreased with tumor progression. CEST@2ppm was found to correlate with the creatine concentration quantified with proton MRS. Based on the correlation curve, the creatine contribution to CEST@2ppm was quantified. The CEST@2ppm signal could be a novel imaging surrogate for in vivo creatine, the important bioenergetics marker. Given its noninvasive nature, this CEST MRI method may have broad applications in cancer bioenergetics. Copyright © 2014 John Wiley & Sons, Ltd.     

脑干听觉诱发电位测试中的曲线拟合与参数估计方法

脑干听觉诱发电位是声觉器官受刺激后产生的一种生物电，反映了相应感觉通路及神经元群的活动，可用作听力阈值的客观判断，以及对多种耳疾和脑部病变作出诊断，因而成为当今临床医学和生物医学信号处理中的一个重要课题。本文介绍了脑干听觉诱发电位潜伏期（Ｌ）与刺激声强（Ｉ）之间关系曲线的作用及其拟合建模，回归算法优化，还用实测数据对选定的拟合曲线模型进行了回归方差分析     

脑Willis环集中参数模型的参数识别算法

目的 探索3种参数识别方法（阻抗模曲线法、阻抗分量法、遗传算法）在脑Willis环11单元集中参数模型参数识别问题求解上的应用。方法 以两侧颈内动脉、椎动脉的流量和压力波形为入口条件,计算正常、两侧椎动脉狭窄情况下模型的参数值,使用Simulink建模对识别算法进行验证,最后对流量加一定噪声验证识别算法的稳定性。结果 正常情况下,阻抗模曲线法获得的近端阻力偏大,阻抗分量法求解的前交通动脉阻力偏大,遗传算法能获得比较合理的模型参数值。两侧椎动脉狭窄情况下,使用阻抗模曲线法能明显得到后循环近端阻力增加的结果,但使用阻抗分量法和遗传算法所得的结果主要是远端阻力有较大增幅。结论 3种方法识别出的参数计算出的压力数据和实际数据仍有差别,考虑为建模误差、源数据误差和计算误差。阻抗模曲线法在区分近端阻力变化上有一定效果,但是某些参数的识别上有较大误差。阻抗分量法能够进行参数识别,但方法不稳定,计算误差较大。遗传算法能获得比较好的近似解,但在区分椎动脉狭窄上存在一定问题。综合阻抗模曲线法和遗传算法可能在未来使用模型进行疾病诊断上发挥比较好的作用。     

Fetal heart rate monitoring based on independent component analysis

In this paper, an algorithm based on independent component analysis (ICA) for extracting the fetal heart rate (FHR) from maternal abdominal electrodes is presented. Three abdominal ECG channels are used to extract the FHR in three steps: first preprocessing procedures such as DC cancellation and low-pass filtering are applied to remove noise. Then the algorithm for multiple unknown source extraction (AMUSE) algorithm is fed to extract the sources from the observation signals include fetal ECG (FECG). Finally, FHR is extracted from FECG. The method is shown to be capable of completely revealing FECG R-peaks from observation leads even with a SNR=-200dB using semi-synthetic data.