Fractal analysis of spontaneous fluctuations in human cerebral hemoglobin content and its oxygenation level recorded by NIRS.
Fractal analysis of spontaneous fluctuations in human cerebral hemoglobin content and its oxygenation level recorded by NIRS.
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NIRS 记录的人脑血红蛋白含量及其氧合水平自发波动的分形分析。
DOI：
10.1007/978-1-4615-4717-4_7
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发表时间：
1999
影响因子：
--
通讯作者：
Hermán,P
中科院分区：
文献类型：
--
作者：
Eke,A;Hermán,P
NIRS技术提供了一种非侵入性工具来监测人脑皮质的血流动力学（Jobsis 1977; Wyatt等人，1986年）。我们最近的兴趣已经转向研究利用这项技术，在了解复杂的血液动力学在人类大脑中捕获的高分辨率血红蛋白时间序列。在我们的定义中，时间序列或信号是复杂的，当它很难识别一个模式，如它是稳定的或周期性的结构。复杂信号不能通过描述性统计测量（例如其平均值、标准偏差等）来充分表征，或者通过其频谱来确定，因为通过这样做，这些信号中存在的其它相关信息被丢弃或不被揭示。因此，需要确定适当的模型和方法，以便对这些信号进行整体表征。类似于我们先前对从大鼠大脑皮层获得的红细胞流量时间序列的研究（Eke et al.，1997），我们已经应用了分形模型的功率谱密度（PSD）和缩放窗口方差（SWV）的方法在人类大脑皮层血红蛋白信号的分析，试图评估其时间模式的组合。
The NIRS technology provides a non-invasive tool to monitor hemodynamics from the human brain cortex (Jobsis 1977; Wyatt et aI., 1986). Our interest recently has turned toward studies utilizing this technology in understanding the complexity of hemodynamics in the human brain as captured in high resolution hemoglobin time series. In our definition a time series or signal is complex when it is difficult to recognize a pattern such as it is being stable or periodic in its structuring. A complex signal cannot be adequately characterized by descriptive statistical measures such as its mean, standard deviation, etc., or by its frequency spectrum because by doing so other relevant information that is present in these signals are discarded or not revealed. Hence, adequate models, and methods need to be identified for such signals to be characterized in their entirety. Similar to our previous study on red blood cell flux time series acquired from the brain cortex of the rat (Eke et aI., 1997) we have applied the fractal model as implemented in a combination of the power spectral density (PSD) and the scaled windowed variance (SWV) methods in the analysis of human cerebrocortical hemoglobin signals in an attempt to assess their temporal pattern.