Estimation of skin blood flow artefacts on NIRS signals during a verbal fluency task.
Estimation of skin blood flow artefacts on NIRS signals during a verbal fluency task.
复制标题
在语言流畅性任务期间估计 NIRS 信号上的皮肤血流伪影。
DOI：
10.1007/978-1-4939-3023-4_41
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Takayama N.
中科院分区：
文献类型：
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作者：
Seiyama A;Higaki K;Takeuchi N;Uehara M;Takayama N.
这项研究的目的是阐明在语言流利性任务中皮肤(头皮)血流对功能性近红外光谱(FNIRS)的影响。为探讨皮肤血流量对近红外光谱信号的影响，我们对19名健康志愿者(平均年龄39.9 ± 13.1a，男11例，女8例)进行了检测。我们使用多模式的fNIRS系统同时测量了fNIRS信号、皮肤血流量(即，流量、速度和红细胞数量)和脉搏波率。我们发现，皮肤血流对近红外光谱信号的影响在不同受试者之间有很大的差异。此外，利用上述生理参数，我们评估了Molgedey和Schuster提出的独立分量分析算法(MS-ICA)在去除fNIRS信号中皮肤血流伪影方面的应用。
The aim of this study was to clarify effects of skin (scalp) blood flow on functional near infrared spectroscopy (fNIRS) during a verbal fluency task. In the present study, to estimate the influence of skin blood flow on fNIRS signals, we conducted examinations on 19 healthy volunteers (39.9 ± 13.1 years, 11 male and 8 female subjects). We simultaneously measured the fNIRS signals, skin blood flow (i.e., flow, velocity, and number of red blood cells [RBC]), and pulse wave rates using a multimodal fNIRS system. We found that the effects of skin blood flow, measured by the degree of interference of the flow, velocity, and number of RBCs, and pulse wave rates, on NIRS signals varied considerably across subjects. Further, by using the above physiological parameters, we evaluated application of the independent component analysis algorithm proposed by Molgedey and Schuster (MS-ICA) to remove skin blood flow artefacts from fNIRS signals.