基于联合对角化算法的非接触心率估计

基于成像光电容积脉搏波描记法(iPPG)和盲源分离(BSS)理论,提出一种非接触估计心率方法。利用网络摄像头在自然光中录制人脸视频图像,将视频图像中检测的人脸区域分离为RGB三通道分量,对一定数量RGB数据做归一化、球化等预处理,再经独立分量分析(ICA)理论和联合对角化(JADE)算法,利用频谱分析估计心率。利用Bland-Altman理论分析估计结果与商用脉搏血氧仪测试结果的一致性,估计结果中均方根误差为2.06次/min,表明本方法能够实现非接触心率测量,同时可以作为远程、非接触多生理参数测量的研究基础。     

非接触式心率测量研究初步

基于Matlab软件平台,通过图像光电容积脉搏波描记法(iPPG),提取心率波信号。结合人脸检测与跟踪技术,选取脸部三角区域作为感兴趣区域 (ROI),从中分析提取iPPG信号,然后采用快速傅里叶变换计算出心率。通过对20名志愿者的实验,结果显示在不同颜色通道(R、G、B)提取出的心率信号的信噪比不同,其中G通道的心率信号最强。分析数据显示,与医用心电测量仪相比,该方法测量的平均误差为1.73 beat/min。采用光容积成像技术检测方法,可进一步实现血液灌注三维可视化,能检测动脉血氧饱和度、呼吸率、神经系统的生理活动和新生儿监护,甚至能应用于家庭移动医疗、运动检测等大众场合,提高便捷性,降低医疗成本。     

基于指端脉搏波视频信号的心率稳定检测算法

目的:研究一种基于脉搏波的稳定检测心率的算法。 方法:提出一种基于快速独立成分分析（FastICA）算法处理指端脉搏波视频信号。首先通过手机摄像头采集手指视频,在每帧图片中提取感兴趣区域（ROI）,根据每个区域中像素灰度值的变化得到血液容积变化的时序曲线;然后通过对ROI进行RGB通道分离和FastICA后,分别选取红、绿色分量与盲源分离后的估计信号进行相关性分析,筛选出相关性最大的作为后续提取心率的信号,并与波峰法测得的心率进行对比,得到一种稳定的心率检测算法,并利用SPSS软件做相关性分析。 结果:选取R、G通道信号的一致性在95%以上,基于FastICA的算法与统计波峰法获取心率的一致性在95%以上。 结论:FastICA算法能够有效地提高心率测量的稳定性,实验结果验证了该方法的可行性和有效性,对于基于脉搏波的人体生理参数获取具有重要意义。     

自主呼吸状态下光电容积脉搏波法对 健康人群心率变异性的分析

目的 分析自主呼吸状态下光电容积脉搏波法对健康人群心率变异性。方法 选取2016年10月~2018年9月我校本科生健康志愿者64名,所有志愿者均行心电图（ECG）及光电容积脉搏波法（PPG）检测,比较3 min的ECG与PPG检测HRV时的RR间期标准差（SDNN）、RR间期差值均方根值（RMSSD）、低频功率与标准化高频功率的比值（LF/HF）,并分析ECG与PPG检测的心率变异性参数的相关性与一致性。结果 64例志愿者3 min的ECG与PPG心率变异性参数比较,差异无统计学意义（P＞0.05）。经Pearson相关性分析发现,PPG检测SDNN、RMSSD、LF/HF与ECG各指标呈正相关（SDNN:r=0.999,P＜0.001;RMSSD:r=0.998,P＜0.001;LF/HF:r=0.998,P＜0.001）;经可靠性分析发现,PPG用于检测健康人群心率变异性与ECG一致性较高（ICC=0.915,95% CI:0.878~0.943,P＜0.001）。结论 健康人群自主呼吸状态下光电容积脉搏波法可用于心率变异性的检测,临床上有较好的应用价值。     

脉搏血氧饱和度检测中自适应滤波消除运动伪差的方法研究

目的研究脉搏血氧饱和度检测系统中运动伪差的消除方法,以提高脉搏血氧仪检测性能。方法通过脉搏血氧仪中的双光束构造噪声参考信号,利用最小均方自适应滤波法消除运动伪差干扰的影响。结果建立了脉搏血氧饱和度检测中消除运动伪差的计算方法,可成功地从运动伪差中提取正常光电容积脉搏波信号作为计算氧饱和度的依据。结论该计算方法简单,可用于实时处理,且测量结果可靠,为进一步抑制脉搏血氧仪噪声奠定了基础。     

两种计算正常成年人短时心率变异性方法的比较研究

目的利用光电容积脉搏波法分析心率变异性,为通过心率变异性(heart rate variability,HRV)参数表征自主神经系统的变化提供新的研究方法。方法对46个健康成年受试者分别同步采集自主呼吸状态下的心电信号和光电容积脉搏波信号,利用二阶差分极大值提取心电图的RR间期,搜索脉搏波极大值提取脉搏波主波波峰间期PP,然后计算通用HRV参数SDNN、RMSSD和LF/HF,并利用回归的统计学方法结合Bland-Altman随机分析法对这两种方法获取的HRV结果进行比较。结果两种方法计算得到的心率变异性参数结果的Pearson相关系数分别为0.998、0.995和0.992,均显著相关(P0.01),Bland-Altman分布图也均在一致性区间内,说明这两种方法在计算心率变异性上具有一致性。结论利用光电容积脉搏波法分析心率变异具有可行性。     

基于脉搏波传导时间变异性的冠心病识别方法

为提高冠心病识别的准确性,提出基于脉搏波传导时间变异性(PTTV)的冠心病识别方法。采用同步心电和脉搏信号提取PTTV信号,计算PTTV信号的均值、标准差等时域特征、庞加莱散点图特征以及信息熵特征,对这些特征参数在主成分分析基础上,选取7组主成分作为PTTV信号的综合特征,用于冠心病的分类识别。实验结果表明基于PTTV信号的综合特征对冠心病的分类识别准确率达到98.77%,其有望作为冠心病早期诊断方法。     

反射式血氧饱和度检测系统研制

反射式血氧仪可以有效避免使用范围受限,但反射式脉搏血氧信号十分微弱,容易受噪声干扰使血氧参数的提取难度加大。为获得高质量有效的反射式容积脉搏波,系统设计中提出一种基于集成芯片AFE4490的脉搏血氧信号检测方案,对比几种基于小波变换的滤波算法去噪效果,完成对血氧信号较优的去噪处理。系统样机经调试后,基本实现反射方式对脉搏血氧饱和度的检测功能。     

基于脉搏-心电的便携式血压仪的研制

设计一种体积小巧,测量过程无任何束缚的基于脉搏波传导时间(pulse wave transit time,PWTT)的血压仪。从反射式容积脉搏波(photoplethysmography,PPG)和心电波形(electrocardiogram,ECG)中提取脉搏波传导时间,再综合心率、每搏输出量和外周阻力对血压的影响,通过回归分析建立血压模型,最终实现血压测量。应用样机对20名志愿者进行血压测量,同时以传统水银血压计的测量结果作为标准,结果显示收缩压和舒张压的95%一致性界限分别为(-8.3,11.6),(-9.9,12.7),说明两种方法所测的血压值有较好的一致性。血压仪样机实体小巧,使用方便,使用过程没有任何束缚,同时在理论上对基于脉搏波传导时间的血压测量方法进行优化,实现了收缩压和舒张压的测量。     

基于光电容积脉搏波波形分析的运动负荷评价

目的能量消耗是衡量运动负荷最直接的指标。本文的研究目的是利用脉搏波波形来衡量运动负荷,从而为基于可穿戴设备的运动负荷评价技术提供基础。方法招募32名年龄为18~60岁的正常人作为受试者,采用指夹式光电容积脉搏波传感器对受试者的脉搏波进行采集,使用K4b2心肺功能测试仪获取的能量消耗作为金标准进行功率自行车实验,从而获得脉搏波波形特征与能量消耗之间的关系。结果在静息状态下,脉搏波周期、主波峰值、脉搏波面积的数值较为稳定;而在功率车运动状态下,脉搏波波形周期平均值、主波峰值、脉搏波面积的平均值变小,三者标准差则增大。实验结果表明,脉搏波波形幅值对时间的积分J与能量消耗E在静止、功率车运动状态下皆呈线性关系,两者拟合直线的斜率之比为常数。结论使用光电容积脉搏波波形对运动负荷进行评估是可行的。利用脉搏波波形特征,可以较为准确地拟合出运动中的能量消耗,从而评价运动负荷。     

Use of a simulation model for estimating cardiac output from aortic pressure curves

A method for calculating cardiac output from aortic pressure curves is presented. The method is based on a simulation model of the human cardiovascular system. The aortic compliance is calculated from the pulse transmission time in the aorta. The method has been tested against standard cardiac output measurements in 61 instances in 39 persons. 40 measurements have been performed at rest, while 21 have been performed during various changes in the cardiovascular state. The mean difference between the pulse method and the standard cardiac output determination was found to be 9% with a standard error of the difference of 7%. The correlation coefficient was r=0·96. The largest differences were found in patients suffering from atrial fibrillation, where changes in pressure in the aorta made compliance estimates based on pulse transmission time difficult. Using a servosystem, the model is capable of following changes in the cardiovascular state within a few beats. This method should therefore be useful for calculating cardiac output in the intensive-care situation.     

Recovery of macular pigment spectrum in vivo using hyperspectral image analysis

We investigated the feasibility of a novel method for hyperspectral mapping of macular pigment (MP) in vivo. Six healthy subjects were recruited for noninvasive imaging using a snapshot hyperspectral system. The three-dimensional full spatial-spectral data cube was analyzed using non-negative matrix factorization (NMF), wherein the data was decomposed to give spectral signatures and spatial distribution, in search for the MP absorbance spectrum. The NMF was initialized with the in vitro MP spectrum and rank 4 spectral signature decomposition was used to recover the MP spectrum and optical density in vivo. The recovered MP spectra showed two peaks in the blue spectrum, characteristic of MP, giving a detailed in vivo demonstration of these absorbance peaks. The peak MP optical densities ranged from 0.08 to 0.22 (mean 0.15+∕-0.05) and became spatially negligible at diameters 1100 to 1760 μm (4 to 6 deg) in the normal subjects. This objective method was able to exploit prior knowledge (the in vitro MP spectrum) in order to extract an accurate in vivo spectral analysis and full MP spatial profile, while separating the MP spectra from other ocular absorbers. Snapshot hyperspectral imaging in combination with advanced mathematical analysis provides a simple cost-effective approach for MP mapping in vivo.     

基于心电信号的脉搏波形特征点提取

为寻求一种精确的脉搏波特征提取方法,提取更多的脉搏波形特征,揭示心电脉搏在时域上的相关性,使用MP425数据采集卡和LabVIEW构成的数据采集系统同步采集ECG信号和脉搏波信号,对ECG信号和脉搏波信号进行分析和处理,采用能量算子法检测心电信号R波;基于同步采集的ECG和脉搏波信号,提出一种应用ECG信号的R波和T波来提取Pulse wave的重搏波和峰值的方法.经过分析与实验验证,该方法能准确找到脉搏波波峰和重搏波位置,并具有较强的抗干扰能力,为研究心电脉搏之间的关系提供了一种新的方法.     

基于PCA多导联的癫痫脑电信号分类及致痫灶定位研究

为了更好的对致痫灶进行准确定位,提出了一种基于PCA(主成分分析)的定位方法.针对非线性动力学方法从不同角度提取癫痫脑电信号特征,首先采用主成分分析对高维特征向量进行降维处理,用随机森林进行分类;随后利用医学参考值范围找出各导联的差异变化,进而实现对致痫灶的初步定位.     

Statistical test for peri-stimulus time histograms in assessing motor neuron activity

The peri-stimulus time histogram is a valuable tool for evaluating neural connections in humans. To detect the degree to which a conditioning stimulus to a sensory nerve modulates motor neuron activity, a histogram of motor unit spike intervals after a conditioning stimulus is measured. This histogram allows the effect of the conditioning stimulus to be visualised. By comparison with a reference histogram of motor unit spike intervals after a sham stimulus, the noise caused by spontaneous firing sway can be removed. However, no valid statistical test has yet been developed to separate the physiological effect from the spontaneous sway and statistical noise. A computational method has been proposed to detect modulation caused by a conditioning stimulus. To clarify the effect of a conditioning stimulus, this new method used reference histograms to calculate a confidence interval. A simulated experiment demonstrated that about 2000 re-samplings were sufficient to estimate a confidence interval for a histogram with 1 ms bin width constructed from 300 triggers. Testing of the experimental data, measured from the tibialis anterior muscles during the elicitation of the excitatory spinal reflex, confirmed that significant peaks were produced at 30, 34, 35 and 38 ms after the conditioning stimulus. These correspond appropriately to the delay of the spinal reflex.     

MP-PCNN超声多普勒血流信号声谱图降噪去斑方法

为有效抑制超声多普勒血流信号声谱图中的背景噪声和多普勒斑点,提出了Matching Pursuit(MP)及单向衰减阈值脉冲耦合神经网络(MP-PCNN)模型。首先将分段的多普勒超声信号进行MP循环分解,分离噪声与信号,然后用单向衰减阈值PCNN模型计算声谱图在各个灰度等级上的点火时刻图并定位斑点,用中值滤波器抑制斑点。通过对各种信噪比的仿真超声多普勒血流信号处理,实验结果表明,MP-PCNN方法可有效地滤除声谱图中的噪声与斑点,并较好地保持边缘与细节信息,在主观及客观性能比较上优于同类降噪去斑方法。     

Recovering dipole sources from scalp-recorded event-related-potentials using component analysis: principal component analysis and independent component analysis.

Principal component analysis (PCA) and independent component analysis (ICA) were examined in their ability to recover dipole sources from simulated data. Datasets of EEG segments were generated that contained cortical sources that were temporally overlapping or non-overlapping, and dipole sources with varying degree of spatial orthogonality. For temporal overlapping sources, both PCA and ICA resulted in components that required multiple-source equivalent current dipole models. The spatially overlapping sources affected the PCA method more than ICA, resulting in single PCA components in which all non-orthogonal sources were represented. For both PCA and ICA, dipole models with fixed-location dipoles successfully accounted for most of the variance in the component weights, even when the spatial or temporal overlap of the generating sources required multiple-dipole models.     

结合二维灰度直方图与PCNN的医学图像多类分割

针对医学图像中对组织器官多类分割的要求,提出一种结合二维灰度直方图的脉冲耦合神经网络（pulse coupled neural networks,PCNN）图像多类分割算法.首先根据PCNN模型的局部连接作用和阈值衰减特性对图像进行多类分割,然后利用基于类内最小离散度的二维直方图算法计算出PCNN网络迭代时的最佳门限值,从而实现医学图像的多类分割.通过对仿真的正常颅脑和非正常的颅脑核磁共振图像进行测试,结果显示本PCNN图像多类分割算法能够有效地分割出核磁共振颅脑图像中不同脑组织.因此,本文算法具有应用于医学图像的多类分割的可行性,并提高计算机辅助分割医学图像的准确性.     

一种基于图像分割的医学图像融合方法

提出一种新的图像融合算法 ,用于临床治疗计划设计时对病灶的确定。文中采用改进的Canny算子对病灶边缘提取方法进行了研究 ,根据局部直方图计算对非目标轮廓进行抑制。通过对图像配准建立空间映射关系 ,将一种图像中的病灶边缘特征与其它相应的图像进行叠加 ,获得具有病灶边缘和解剖结构特征的融合图像。本文的融合算法简单、直观 ,临床实用性强     

A Construction Method of Personalized ECG Template and Its Application in Premature Ventricular Contraction Recognition for ECG Mobile Phones

Premature ventricular contraction(PVC) is the most frequent arrhythmia encountered in clinical practice. PVC may occur in health subjects, which is not imminently life-threatening but may require therapies to prevent further problems. So,the timely PVC recognition becomes very important for the analysis of electrocardiogram(ECG), especially for the remote ECG monitoring using mobile phones. In this paper,a construction method of personalized ECG template and a PVC recognition method based on template matching were studied. Firstly, we selected 43 ECG recordings from the MIT-BIH arrhythmia database. All recordings were divided into two datasets(DS1for training and DS2 for testing) and each dataset approximately contained the same proportion of PVC beats. Subsequently, for each recording(30 min) in DS1, the first5 min recordings were used to construct the personalized ECG template and the last25 min recordings were used for the R-wave peaks detection and PVC recognition,where the template matching method were used. The validity of the proposed methods was tested using DS2. The results showed that: 1) high beat detection accuracy was achieved for both PVC beats and non-PVC beats; 2) the sensitivity and specificity of PVC recognition were 99.11% and 99.96% for the first 5 min recordings respectively,99.17% and 99.43% for the last 25 min recordings respectively. All the proposed methods can be real-time performed, which show a promising prospect for the application of ECG mobile phones.