Diffusing wave spectroscopy (DWS) is a well-known set of methods to measure the temporal dynamics of dynamic samples. In DWS, dynamic samples scatter the incident coherent light, and the information of the temporal dynamics is encoded in the scattered light. To record and analyze the light signal, there exist two types of methods—temporal sampling methods and speckle ensemble methods. Temporal sampling methods, including diffuse correlation spectroscopy, use one or multiple large bandwidth detectors to sample well and analyze the temporal light signal to infer the sample temporal dynamics. Speckle ensemble methods, including speckle visibility spectroscopy, use a high-pixel-count camera sensor to capture a speckle pattern and use the speckle contrast to infer sample temporal dynamics. In this paper, we theoretically and experimentally demonstrate that the decorrelation time (τ) measurement accuracy or signal-to-noise ratio (SNR) of the two types of methods has a unified and similar fundamental expression based on the number of independent observables (NIO) and the photon flux. Given a time measurement duration, the NIO in temporal sampling methods is constrained by the measurement duration, while speckle ensemble methods can outperform by using simultaneous sampling channels to scale up the NIO significantly. In the case of optical brain monitoring, the interplay of these factors favors speckle ensemble methods. We illustrate that this important engineering consideration is consistent with the previous research on blood pulsatile flow measurements, where a speckle ensemble method operating at 100-fold lower photon flux than a conventional temporal sampling system can achieve a comparable SNR.

中文翻译：

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扩散波谱：时间采样和散斑合奏方法的统一处理

扩散波谱（DWS）是一组用于测量动态样本的时间动态变化的众所周知的方法。在DWS中，动态样本会散射入射的相干光，并且时间动态信息会被编码在散射光中。为了记录和分析光信号，存在两种类型的方法-时间采样方法和散斑合奏方法。时间采样方法（包括漫射相关光谱法）使用一个或多个大带宽检测器对样品进行采样，并分析时间光信号以推断采样的时间动态。散斑合奏方法（包括散斑可见度光谱法）使用高像素数摄像头传感器捕获散斑图案，并使用散斑对比度来推断样本时间动态。在本文中，τ）的测量精度或这两种类型的方法中的信噪比（SNR）已基于独立观测（的NIO）的数量和光子通量统一和类似的基本表达。在给定时间测量持续时间的情况下，时间采样方法中的NIO受测量持续时间的限制，而散斑合奏方法可以通过使用同时采样通道显着放大NIO来胜任。在光学大脑监控的情况下，这些因素的相互作用有利于散斑合奏方法。我们说明了这一重要的工程考虑因素与先前对血液脉动流量测量的研究相一致，在该研究中，以比传统时间采样系统低100倍的光子通量运行的散斑集成方法可以实现可比的SNR。