人体血氧饱和度检测中消除脉搏波信号高频噪声的方法

基于光电容积脉搏波的方法可以用于人体血氧饱和度的无创检测,基于光电容积脉搏波测量时,由于信号采集过程中随机噪声等干扰,脉搏波信号中存在高频噪声,影响最终的血氧饱和度测量精度。提出采用基于连续均方误差(CMSE)准则的经验模态分解(EMD)法消除脉搏波信号中的高频噪声。利用自行研制的光电容积脉搏波采集装置采集脉搏波信号,应用该方法消除信号中高频噪声,并采用信号的频谱进行效果评价。结果表明：该方法有效消除了高频噪声,这将有利于人体血氧饱和度无创检测精度的提高。     

动态光谱检测中的相移波形误差分析

动态光谱提取自光电容积脉搏波,是与动脉血液信息高度相关的近红外光谱,可应用于动脉血液成分的无创检测,具有很好的临床应用价值。文章依据动态光谱检测理论,对检测过程中的相移波形误差进行了分析。人体正常生理活动可导致光电容积脉搏波的周期、幅值和基线的不稳定。同时在动态光谱时域检测过程中,不同波长下检测到的脉搏波间存在一定的相位延迟。以上两个因素将导致不同波长对应的脉搏波之间存在一定的波形差异,从而使其频谱发生改变,在动态光谱中引入相移波形误差。文章对该相移波形误差进行了量化分析。结果表明,该误差与截取脉搏周期的矩形窗位置相关。通过精选矩形窗位置,可以将相移波形误差降低一个数量级。     

一种光电容积脉搏信号的峰值点自动识别方法

光电容积脉搏信号的峰值点自动识别直接关系到无创血氧饱和度测量与脉搏波峰-峰间期提取的准确率。提出一种小波联合识别方法：基于小波多分辨率分析原理校正影响脉搏波峰值点幅值的基线干扰,再利用二次样条小波模极大算法自动识别峰值点。将该方法应用到自行研制的光电容积脉搏波测量系统中,对采集的信号进行了校正与峰值点识别,通过在信号中增加随机噪声以评价方法的稳定性与可靠性,然后利用10组实测数据,对比本方法与传统差分阈值法的峰值点识别准确率,进一步评价方法的有效性。结果表明：本方法在较好地消除了基线干扰的基础上,在染噪的信号中仍然会较精确地检测出脉搏波主波峰,具有较好的抗干扰能力,有利于提高血氧饱和度检测及峰-峰间期提取的准确性,从而有助于后期人体呼吸功能评价与心率变异性分析。     

利用近红外光谱检测多层组织血氧饱和度的研究

利用近红外光谱无创检测生物组织血氧饱和状态,是一种极富研究和应用前景的检测技术,在临床检测中被广泛应用.但常规临床检测应用于指端仅反映局部血氧饱和度信息,在使用中具有局限性,信号的可信度也存在质疑.该文提出了一种采用反射式脉搏血氧饱和度检测技术检测生物多层组织氧合状况的新方法,该方法通过调节入射光强以适应解剖学中生物组织多层结构的检测.应用该方法针对手指结构的实验结果表明,随着入射光强的改变,反映血氧饱和状态的光电脉搏波信号有显著变化.结合手指解剖学分析表明,光电脉搏波信号的变化与手指的多层面组织结构相对应,反映不同层面血氧饱和状态.这一特点表明,通过此法可以针对生物组织的多层结构进行测量.     

频域近红外光谱方法定量测量组织氧饱和度

通过精确测量光子密度波的相位延迟和幅度衰减,借助于一个光学参数已知的校准模型,可以定量检测组织的光学吸收参数和约化散射系数.通过测量多个波长下组织的吸收系数,就可以进一步求解出人体局部组织的血氧饱和度.血液－酵母溶液仿真模型和前臂动脉阻断实验的结果都表明该三波长的频域近红外光谱系统可以实时定量地检测组织氧饱和度的动态变化情况.     

基于运动方向估计的管道滤波算法

管道滤波算法提出了从时域角度解决弱小目标检测问题的思路,对于红外强起伏天空背景中弱点目标的检测问题,管道内强噪音的干扰以及低信噪比的条件会导致检测概率降低的情况出现.本文提出了一种运动方向估计的管道滤波算法,分析了红外弱点目标的运动特性,依据弱点目标在相邻帧间位置具有连贯性的特征,建立了弱点目标的运动方向估计模型.在模型中利用弱点目标逐帧检测的先验位置信息,估计弱点目标的运动方向和轨迹,根据估计结果去除管道内噪音对弱点目标的干扰.仿真结果表明,该方法能够很好地抑制管道内噪音的影响,提高弱点目标的检测概率,增强弱点目标抗管道内噪音干扰的能力.     

基于运动方向估计的管道滤波算法

管道滤波算法提出了从时域角度解决弱小目标检测问题的思路,对于红外强起伏天空背景中弱点目标的检测问题,管道内强噪音的干扰以及低信噪比的条件会导致检测概率降低的情况出现.本文提出了一种运动方向估计的管道滤波算法,分析了红外弱点目标的运动特性,依据弱点目标在相邻帧间位置具有连贯性的特征,建立了弱点目标的运动方向估计模型,在模型中利用弱点目标逐帧检测的先验位置信息,估计弱点目标的运动方向和轨迹,根据估计结果去除管道内噪音对弱点目标的干扰.仿真结果表明,该方法能够很好地抑制管道内噪音的影响,提高弱点目标的检测概率,增强弱点目标抗管道内噪音干扰的能力.     

示波器实验的教学改革

示波器的原理和使用是大学物理实验教学的一个基础实验项目.传统的教学仅限于向学生介绍示波器显示波形的原理,测量信号电压、频率和周期等参数,以及采用利萨如图形测量待测信号频率等内容.随着科技的进步,传统的模拟示波器已经逐步被数字示波器所替代,一些高校实验项目也做了相应的调整.本课题探讨数字示波器的实验拓展,即结合压电传感器采集人体不同部位的脉搏信号,并通过对采集多组信号的数据分析,讨论脉搏信号特征与人体部位、性别以及时间段的关联性.     

浅海双基地有源探测调频信号直达波消除

双基地有源探测常采用长脉宽探测信号以获取更高的时间增益,容易导致回波弱信号被强直达波信号掩蔽而影响回波检测.针对长调频信号直达波的干扰,提出基于分数阶傅里叶变换(FrFT)的直达波消除方法.该方法利用调频信号在时频分布上的稀疏性,通过对接收信号进行分数阶傅里叶变换分离直达波和回波信号然后在变换域对直达波信号进行去除.远...     

Elimination of Anti-spiral Waves by Local Inhomogeneity in Oscillatory Systems

采用系统中的局部不均匀性消除振荡系统中的反螺旋波. 该不均匀性在系统中成为一个波源,不断产生稳定的相波. 研究结果发现,不均匀性的尺寸大小存在一个临界值,如果低于此临界值,则系统将无法激发任何相波. 根据不均匀性形状的不同,系统分别产生靶波和行波. 此外,实验还发现靶波与反螺旋波之间以及行波与反螺旋波之间存在着不同的动态竞争. 数值计算表明,对于行波,无论是低频行波还是高频行波,都可以成功地消除系统中的反螺旋波;而对于靶波,只有低频靶波才可以消除反螺旋波. 此控制方法简单易行,且同样适用于消除向外传播的螺旋波     

Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment

Rett syndrome is a disease that involves acute cognitive impairment and, consequently, a complex and varied symptomatology. This study evaluates the EEG signals of twenty-nine patients and classify them according to the level of movement artifact. The main goal is to achieve an artifact rejection strategy that performs well in all signals, regardless of the artifact level. Two different methods have been studied: one based on the data distribution and the other based on the energy function, with entropy as its main component. The method based on the data distribution shows poor performance with signals containing high amplitude outliers. On the contrary, the method based on the energy function is more robust to outliers. As it does not depend on the data distribution, it is not affected by artifactual events. A double rejection strategy has been chosen, first on a motion signal (accelerometer or EEG low-pass filtered between 1 and 10 Hz) and then on the EEG signal. The results showed a higher performance when working combining both artifact rejection methods. The energy-based method, to isolate motion artifacts, and the data-distribution-based method, to eliminate the remaining lower amplitude artifacts were used. In conclusion, a new method that proves to be robust for all types of signals is designed.     

Improved reduction of motion artifacts in diffusion imaging using navigator echoes and velocity compensation

Navigator echoes provide a means with which to remove motion artifacts from diffusion-weighted images obtained using any multishot imaging technique. However, residual motion artifact is often present in the corrected images rendering the technique unreliable. It is shown that velocity-compensated diffusion sensitization when used in tandem with a navigator echo further reduces the degree of residual motion artifacts present in the corrected images and improves the reliability and clinical utility of the technique. This is demonstrated by applying a method for quantification of motion artifact to brain images of healthy volunteers scanned using both conventional (Stejskal-Tanner) and velocity-compensated gradient sensitization. Other factors affecting the efficacy of the navigator echo technique, such as brain pulsatile motion, gradient b factor, and navigator echo signal-to-noise ratio, are also discussed.     

Motion artifact reduction technique for dual-contrast FSE imaging

There is considerable similarity between proton density-weighted (PDw) and T2-weighted (T2w) images acquired by dual-contrast fast spin-echo (FSE) sequences. The similarity manifests itself in image space as consistency between the phases of PDw and T2w images and in k-space as correspondence between PDw and T2w k-space data. A method for motion artifact reduction for dual-contrast FSE imaging has been developed. The method uses projection onto convex sets (POCS) formalism and is based on image space phase consistency and the k-space similarity between PDw and T2w images. When coupled with a modified dual-contrast FSE phase encoding scheme the method can yield considerable artifact reduction, as long as less than half of the acquired data is corrupted by motion. The feasibility and efficiency of the developed method were demonstrated using phantom and human MRI data.     

用多凹槽滤波器控制混沌系统

提出了一种施加多个凹槽滤波器反馈控制混沌系统的方法,使混沌运动转化为规则的运动.多凹槽滤波器控制是一种具有固定参数的线性反馈控制方法,它不影响原系统的参数,截断了系统从倍周期分叉通向混沌的道路.同时,用Melnikov方法进行理论分析,给出了合适的反馈控制器的参数.将多凹槽滤波器应用于典型的混沌系统,其仿真结果表明了该控制方法的有效性与可行性 关键词： 混沌 多凹槽滤波器 Melnikov方法     

Automatic correction of in-plane bulk motion artifacts in self-navigated radial MRI

Radial MRI is typically used for scans that are sensitive to unavoidable motion. While the translational motion artifact can be easily removed from the radial trajectory data by phase correction, correction of rotational motion still remains a challenge in radial MRI. We present a novel method to refocus the image corrupted by view-to-view motion in the view-interleaved radial MRI data. In this method, the error in rotational view angles was modeled as a polynomial function of the view order and the model parameters were estimated by minimizing the self-navigator image metrics such as image entropy, gradient entropy, normalized gradient squared and mean square difference. Translational motion correction was conducted by aligning the projection profiles. Simulation studies were conducted to demonstrate the robustness of both translational and rotational motion correction methods in different noise levels. The proposed method was successfully applied to correct for motion of healthy subjects. Substantial motion correction with relative error of less than 5% was achieved by using either first- or second-order model with the image metrics. This study demonstrates the potential of the method for motion-sensitive applications.     

Motion artifacts reduction in brain MRI by means of a deep residual network with densely connected multi-resolution blocks (DRN-DCMB)

Objective: Magnetic resonance imaging (MRI) acquisition is inherently sensitive to motion, and motion artifact reduction is essential for improving image quality in MRI. Methods: We developed a deep residual network with densely connected multi-resolution blocks (DRN-DCMB) model to reduce the motion artifacts in T1 weighted (T1W) spin echo images acquired on different imaging planes before and after contrast injection. The DRN-DCMB network consisted of multiple multi-resolution blocks connected with dense connections in a feedforward manner. A single residual unit was used to connect the input and output of the entire network with one shortcut connection to predict a residual image (i.e. artifact image). The model was trained with five motion-free T1W image stacks (pre-contrast axial and sagittal, and post-contrast axial, coronal, and sagittal images) with simulated motion artifacts. Results: In other 86 testing image stacks with simulated artifacts, our DRN-DCMB model outperformed other state-of-the-art deep learning models with significantly higher structural similarity index (SSIM) and improvement in signal-to-noise ratio (ISNR). The DRN-DCMB model was also applied to 121 testing image stacks appeared with various degrees of real motion artifacts. The acquired images and processed images by the DRN-DCMB model were randomly mixed, and image quality was blindly evaluated by a neuroradiologist. The DRN-DCMB model significantly improved the overall image quality, reduced the severity of the motion artifacts, and improved the image sharpness, while kept the image contrast. Conclusion: Our DRN-DCMB model provided an effective method for reducing motion artifacts and improving the overall clinical image quality of brain MRI.     

A mixed waveform protocol for reduction of the cardiac motion artifact in black-blood diffusion-weighted imaging of the liver

ObjectiveDiffusion-weighted imaging (DWI) in the liver suffers from signal loss due to the cardiac motion artifact, especially in the left liver lobe. The purpose of this work was to improve the image quality of liver DWI in terms of cardiac motion artifact reduction and achievement of black-blood images in low b-value images.Material and methodsTen healthy volunteers (age 20–31 years) underwent MRI examinations at 1.5 T with a prototype DWI sequence provided by the vendor. Two diffusion encodings (i.e. waveforms), monopolar and flow-compensated, and the b-values 0, 20, 50, 100, 150, 600 and 800 s/mm² were used. Two Likert scales describing the severity of the pulsation artifact and the quality of the black-blood state were defined and evaluated by two experienced radiologists. Regions of interest (ROIs) were manually drawn in the right and left liver lobe in each slice and combined to a volume of interest (VOI). The mean and coefficient of variation were calculated for each normalized VOI-averaged signal to assess the severity of the cardiac motion artifact. The ADC was calculated using two b-values once for the monopolar data and once with mixed data, using the monopolar data for the small and the flow-compensated data for the high b-value. A Wilcoxon rank sum test was used to compare the Likert scores obtained for monopolar and flow-compensated data.ResultsAt b-values from 20 to 150 s/mm², unlike the flow-compensated diffusion encoding, the monopolar encoding yielded black blood in all images with a negligible signal loss due to the cardiac motion artifact. At the b-values 600 and 800 s/mm², the flow-compensated encoding resulted in a significantly reduced cardiac motion artifact, especially in the left liver lobe, and in a black-blood state. The ADC calculated with monopolar data was significantly higher in the left than in the right liver lobe.ConclusionIt is recommendable to use the following mixed waveform protocol: Monopolar diffusion encodings at small b-values and flow-compensated diffusion encodings at high b-values.     

联合方位-径向速度的粒子滤波目标运动分析

纯方位目标运动分析方法要求观测平台有效机动才能估计目标运动状态,针对这一问题,联合径向速度与方位角作为测量信息对目标进行运动分析,但基于卡尔曼滤波算法进行解算需要已知粗略的目标状态初始值,且收敛时间较长、误差较大,不利于目标实时跟踪.针对以上问题,提出了一种基于粒子滤波的方位径向速度联合目标运动分析方法,建立目标运动状态分析的粒子滤波算法模型,对目标位置和速度等运动要素进行估计.在目标初始状态未知的情况下,一定程度上缩短了收敛时间,减小了估计误差,海试数据处理结果显示:相同条件下,与原有方法相比,本文所提方法收敛时间从35.1 min缩短至30.0 min;跟踪精度从6.1%提高至3.8%,且无需已知目标状态初始值。      

基于动态光谱的脉搏血氧测量精度分析

脉搏血氧仪具有连续、无创、快速、准确监测人体动脉血氧饱和度和心率的功能,现已在临床上发挥重要作用.脉搏血氧饱和度检测法结合分光光度测定法和容积描记法2个基本方法,用红光和红外光同时对手指及耳垂等组织照射和检测.红外光和红光的容积描记图的波幅比值,随动脉血氧饱和程度而变化.目前使用的脉搏血氧仪基本上采用的是传统的脉搏血氧饱和度检测方法,由于其结果受到测量原理,测量条件及个体差异等多方面因素影响,精度不能令人满意.文章从动态光谱的观点出发,通过分析传统脉搏血氧测量原理中产生误差的原因,从理论上推导出实现高精度脉搏血氧测量的方法.动态光谱方法在原理上具有抑制或克服个体差异和测量条件对检测光谱影响的优点.采用该方法可以消除脉搏血氧饱和度测量的理论上的绝大部分误差.     

吸收谱交迭的双组分混合液的荧光谱校正研究

荧光内滤效应以及样品池中荧光物质对激发光的吸收分布会直接影响荧光谱的强度和谱形,共同制约荧光分析法的应用。使用吸收谱及荧光谱存在交迭的双组分混合溶液,研究一种新的基于物理吸收模型的校正方法,以校正荧光内滤效应及吸收分布对荧光强度的影响。对三聚噻吩和五聚噻吩混合液的光谱研究表明,使用所述校正方法可以达到较为理想的校正效果, 误差小于5%。