Identification of scalp blood flow in NIRS data based on Granger causality
Identification of scalp blood flow in NIRS data based on Granger causality
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DOI：
10.1109/bibe.2013.6701566
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发表时间：
2013-11
期刊：
影响因子：
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通讯作者：
M. Sugai;M. Adachi
中科院分区：
文献类型：
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作者：
M. Sugai;M. Adachi
近红外光谱(NIR)是一种非侵入性地评估脑活动引起的血红蛋白浓度动态变化的光谱设备。有人说，近红外光谱数据反映了大脑皮质表面的活动。最近有报道称，近红外光谱数据不仅能反映大脑皮质的血流量，还能反映头皮的血流量。为了讨论这一问题，我们应用Granger因果关系对NIRS数据进行检测，以检测运动执行中头皮和皮质血流量之间的关系。五名健康的受试者参加了这项实验。我们使用高密度探针架同时测量头皮血流量和常规近红外光谱数据。结果，在五个受试者中的四个中，我们从头皮血流数据到常规的近红外光谱数据中检测到了很强的格兰杰因果关系。该方法可用于量化包含在常规近红外光谱数据中的头皮血流分量。
NIRS (Near infra-red spectroscopy) is a spectroscopic device to assess the dynamic changes in the hemoglobin concentration evoked by brain activity non-invasively. It has been said that NIRS data reflects brain activities of cortical surface. Recently, it is reported that NIRS data reflects not only cortex blood flow but also the scalp blood flow. To discuss about this matter, we applied Granger causality for the NIRS data to detect the relationship between scalp and cortex blood flows in motor execution. Five healthy subjects took part in the experiment. We measured scalp blood flow and conventional NIRS data simultaneously using a high density probe holder. As a result, in four of five subjects, we detected the Granger causality strongly from the scalp blood flow data to the conventional NIRS data. This method can be useful to quantify the scalp blood flow component included in the conventional NIRS data.