Sweeney Kevin T, Ayaz Hasan, Ward Tomás E, Izzetoglu Meltem, McLoone Seán F, Onaral Banu
Department of Electronic Engineering, National University of Ireland Maynooth, Co Kildare, Ireland.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:4943-6. doi: 10.1109/IEMBS.2011.6091225.
fNIRS recordings are increasingly utilized to monitor brain activity in both clinical and connected health settings. These optical recordings provide a convenient measurement of cerebral hemodynamic changes which can be linked to motor and cognitive performance. Such measurements are of clinical utility in a broad range of conditions ranging from dementia to movement rehabilitation therapy. For such applications fNIRS is increasingly deployed outside the clinic for patient monitoring in the home. However, such a measurement environment is poorly controlled and motion, in particular, is a major source of artifacts in the signal, leading to poor signal quality for subsequent clinical interpretation. Artifact removal techniques are increasingly being employed with an aim of reducing the effect of the noise in the desired signal. Currently no methodology is available to accurately determine the efficacy of a given artifact removal technique due to the lack of a true reference for the uncontaminated signal. In this paper we propose a novel methodology for fNIRS data collection allowing for effective validation of artifact removal techniques. This methodology describes the use of two fNIRS channels in close proximity allowing them to sample the same measurement location; allowing for the introducing of motion artifact to only one channel while having the other free of contamination. Through use of this methodology, for each motion artifact epoch, a true reference for the uncontaminated signal becomes available for use in the development and performance evaluation of signal processing strategies. The advantage of the described methodology is demonstrated using a simple artifact removal technique with an accelerometer based reference.
功能近红外光谱（fNIRS）记录越来越多地用于监测临床和互联健康环境中的大脑活动。这些光学记录提供了一种方便的测量脑血流动力学变化的方法，而这种变化可与运动和认知表现相关联。此类测量在从痴呆到运动康复治疗等广泛病症中都具有临床效用。对于此类应用，fNIRS越来越多地在诊所外用于家庭中的患者监测。然而，这样的测量环境控制不佳，尤其是运动是信号中伪迹的主要来源，导致后续临床解读的信号质量较差。伪迹去除技术正越来越多地被采用，目的是减少噪声对期望信号的影响。由于缺乏未受污染信号的真实参考，目前尚无方法可准确确定给定伪迹去除技术的功效。在本文中，我们提出了一种用于fNIRS数据收集的新方法，可有效验证伪迹去除技术。该方法描述了使用两个紧邻的fNIRS通道，使它们能够对同一测量位置进行采样；这样在一个通道引入运动伪迹的同时，另一个通道不受污染。通过使用这种方法，对于每个运动伪迹时段，可获得未受污染信号的真实参考，用于信号处理策略的开发和性能评估。使用基于加速度计参考的简单伪迹去除技术证明了所描述方法的优势。
