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A typical time series in functional magnetic resonance imaging (fMRI) exhibits autocorrelation, that is, the samples of the time series are dependent. In addition, temporal filtering, one of the crucial steps in preprocessing of functional magnetic resonance images, induces its own autocorrelation. While performing connectivity analysis in fMRI, the impact of the autocorrelation is largely ignored. Recently, autocorrelation has been addressed by variance correction approaches, which are sensitive to the sampling rate. In this article, we aim to investigate the impact of the sampling rate on the variance correction approaches. Toward this end, we first derived a generalized expression for the variance of the sample Pearson correlation coefficient (SPCC) in terms of the sampling rate and the filter cutoff frequency, in addition to the autocorrelation and cross‐covariance functions of the time series. Through simulations, we illustrated the importance of the variance correction for a fixed sampling rate. Using the real resting state fMRI data sets, we demonstrated that the data sets with higher sampling rates were more prone to false positives, in agreement with the existing empirical reports. We further demonstrated with single subject results that for the data sets with higher sampling rates, the variance correction strategy restored the integrity of true connectivity. 相似文献
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《Clinical neurophysiology》2020,131(4):951-957
ObjectiveTo establish a noninvasive method to measure the neuromagnetic fields of the median nerve at the carpal tunnel after electrical digital nerve stimulation and evaluate peripheral nerve function.MethodsUsing a vector-type biomagnetometer system with a superconducting quantum interference device, neuromagnetic fields at the carpal tunnel were recorded after electrical stimulation of the index or middle digital nerve in five healthy volunteers. A novel technique for removing stimulus-induced artifacts was applied, and current distributions were calculated using a spatial filter algorithm and superimposed on X-ray.ResultsA neuromagnetic field propagating from the palm to the carpal tunnel was observed in all participants. Current distributions estimated from the magnetic fields had five components: leading and trailing components parallel to the conduction pathway, outward current preceding the leading component, inward currents between the leading and trailing components, and outward current following the trailing component. The conduction velocity and peak latency of the inward current agreed well with those of sensory nerve action potentials.ConclusionRemoving stimulus-induced artifacts enabled magnetoneurography to noninvasively visualize with high spatial resolution the electrophysiological neural activity from the palm to the carpal tunnel.SignificanceThis is the first report of using magnetoneurography to visualize electrophysiological nerve activity at the palm and carpal tunnel. 相似文献
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近年来,近红外光谱技术(mear infrared spectrometry,NIRS)在脑科学研究领域倍受青睐。为了更好地满足参数的后续使用并提取出有效特征信号,前期尝试了多种常用滤波方法,为了解决滤后信号易失真以及不能有效滤除低频或者高频噪声的问题,提出了基于高频中值滤波的小波滤波,并采用高度还原真实信号特点的仿真信号以及利用脑血流动力学参数采集系统获得的真实光电容积脉搏波(photoplethysmography,PPG)信号,基于中值滤波的小波滤波进行分析。将实验测试数据与其他滤波方法的特征信号提取效果进行对比,并对处理数据进行信噪比和频谱分析。结果表明,采用中值滤波与小波滤波相结合的滤波方式,对脑动脉色素浓度谱特征信号进行滤波处理,能获得有效、精准的脑血流动力学参数,为后续的测量精度打下基础。该方法有效结合了中值滤波能够剔除粗差的特性和小波滤波在光电容积脉搏波中有效滤除高斯信号的特性,改善了采用单一方式的局限性,提供了一种新的PPG滤波的思路,对比传统方法更加优化。 相似文献
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目的血氧饱和度是人体的重要参数,为适应无线监护系统的需要,针对无线血氧测量节点内存小、运算速度慢的特点,本文设计了一套递推型快速处理算法。方法该算法充分利用递推方式和形态滤波算法过程的中间结果,加速滤波算法的处理速度,提取出测量和控制的关键数据,保证了数据的快速处理和测量系统的实时控制。结果通过分析采样数据和模拟处理过程发现,该算法可有效消除基线漂移、抖动等干扰,保证测量的稳定可靠。结论该算法计算量小,抗干扰能力强,适合无线血氧测量节点实时测量的需求。 相似文献
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In this paper, the influence of the variation in transformer oil temperature on the accuracy of the all-acoustic non-iterative method for partial discharge location in a power transformer is researched. The research can improve power transformers’ testing and monitoring, particularly given the large transformer oil temperature variations during real-time monitoring. The research is based on quantifying the contribution of oil temperature to the standard combined measurement uncertainty of the non-iterative algorithm by using analytical, statistical, and Monte Carlo methods. The contribution can be quantified and controlled. The contribution varied significantly with different mutual placements of partial discharge and acoustic sensors. The correlation between the contribution and the mean distance between partial discharge and acoustic sensors was observed. Based on these findings, the procedure to quantify and control the contribution in practice was proposed. The procedure considers the specificity of the method’s mathematical model (the assumption that the oil temperature is constant), the non-iterative algorithm’s nonlinearity, and the large variations in transformer oil temperature. Existing studies did not consider the significant effect of the oil temperature on the combined measurement uncertainty of partial discharge location influenced by those phenomena. The research is limited to partial discharge located in the transformer oil. 相似文献
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【摘要】目的:解决计算机辅助精子质量分析系统缺乏显微图像滤波算法性能客观评价指标的问题。方法:首先对精子跟踪轨迹连续性、滤波图像直方图、滤波算法性能三者之间的相关性进行研究,然后对不同噪声密度下的相关性进行量化计算,最后建立结构保持因子数学计算模型。结果:滤波算法的结构保持因子越大,精子跟踪轨迹连续性等级越高,证明结构保持因子作为显微图像滤波性能衡量的有效性。结论:结构保持因子克服了显微图像滤波算法性能评价的主观性,该指标可为精子显微图像滤波算法的选取提供理论指导,从计算机图像处理角度为计算机精子质量检测系统提供质控依据。 相似文献