功能近红外光谱（fNIRS）测量对头部运动的敏感性：智能手机在实验室中的实际应用。
Sensitivity of fNIRS measurement to head motion: an applied use of smartphones in the lab.
作者信息
Cui Xu, Baker Joseph M, Liu Ning, Reiss Allan L
机构信息
Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine.
Department of Radiology, Stanford University School of Medicine.
出版信息
J Neurosci Methods. 2015 Apr 30;245:37-43. doi: 10.1016/j.jneumeth.2015.02.006. Epub 2015 Feb 14.
BACKGROUND
Powerful computing capabilities in small, easy to use hand-held devices have made smart technologies such as smartphones and tablets ubiquitous in today's society. The capabilities of these devices provide scientists with many tools that can be used to improve the scientific method.
METHOD
Here, we demonstrate how smartphones may be used to quantify the sensitivity of functional near-infrared spectroscopy (fNIRS) signal to head motion. By attaching a smartphone to participants' heads during the fNIRS scan, we were able to capture data describing the degree of head motion.
RESULTS
Our results demonstrate that data recorded from an off-the-shelf smartphone accelerometer may be used to identify correlations between head-movement and fNIRS signal change. Furthermore, our results identify correlations between the magnitudes of head-movement and signal artifact, as well as a relationship between the direction of head movement and the location of the resulting signal noise.
CONCLUSIONS
These data provide a valuable proof-of-concept for the use of off-the-shelf smart technologies in neuroimaging applications.
背景
小型、易于使用的手持设备中强大的计算能力使智能手机和平板电脑等智能技术在当今社会无处不在。这些设备的功能为科学家提供了许多可用于改进科学方法的工具。
方法
在此，我们展示了智能手机如何用于量化功能性近红外光谱（fNIRS）信号对头部运动的敏感性。通过在fNIRS扫描期间将智能手机连接到参与者头部，我们能够捕获描述头部运动程度的数据。
结果
我们的结果表明，从现成的智能手机加速度计记录的数据可用于识别头部运动与fNIRS信号变化之间的相关性。此外，我们的结果还识别了头部运动幅度与信号伪影之间的相关性，以及头部运动方向与产生的信号噪声位置之间的关系。
结论
这些数据为在神经成像应用中使用现成的智能技术提供了有价值的概念验证。
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