Neuroscience Research Institute, National Institute of Advanced Industrial Science and Technology, AIST Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan.
J Biomed Opt. 2009 Nov-Dec;14(6):064025. doi: 10.1117/1.3275466.
The performance of near-infrared spectroscopy is sometimes degraded by the systemic physiological interference in the extracerebral layer. There is some systemic interference, which is highly correlated with the functional response evoked by a task execution. This kind of interference is difficult to remove by using ordinary techniques. A multidistance measurement method is one of the possible solutions for this problem. The multidistance measurement method requires estimation parameters derived from partial pathlength values of tissue layers to calculate an absorption coefficient change from a temporal absorbance change. Because partial path lengths are difficult to obtain, experimentally, we estimated them by a Monte Carlo simulation based on a five-layered slab model of a human adult head. Model parameters such as thickness and the transport scattering coefficient of each layer depend on a subject and a measurement position; thus, we assumed that these parameters obey normal distributions around standard parameter values. We determined the estimation parameters that provide a good separation performance in average for the model parameter distribution. The obtained weighting is robust to model parameter deviation and provides smaller errors on average compared to the parameters, which are determined without considering parameter distribution.
近红外光谱技术的性能有时会受到脑外组织层的系统性生理干扰的影响。存在一些与任务执行引起的功能响应高度相关的系统性干扰。这种干扰很难通过普通技术去除。多距离测量方法是解决这个问题的一种可能方法。多距离测量方法需要从组织层的部分路径长度值推导出估计参数，以计算吸收系数随时间吸光度变化的变化。由于部分路径长度难以在实验中获得，我们通过基于人体成年头部五层平板模型的蒙特卡罗模拟来估计它们。例如，每层的厚度和输运散射系数取决于主体和测量位置；因此，我们假设这些参数在标准参数值周围服从正态分布。我们确定了在模型参数分布的平均值中提供良好分离性能的估计参数。与不考虑参数分布而确定的参数相比，所获得的加权值对模型参数偏差具有鲁棒性，并且平均误差较小。
