School of Electrical Engineering and Automaton, Harbin Institute of Technology, Harbin 150001, China.
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
J Healthc Eng. 2018 Mar 29;2018:7609713. doi: 10.1155/2018/7609713. eCollection 2018.
The performance of functional near-infrared spectroscopy (fNIRS) is sometimes degraded by the interference caused by the physical or the systemic physiological activities. Several interferences presented during fNIRS recordings are mainly induced by cardiac pulse, breathing, and spontaneous physiological low-frequency oscillations. In previous work, we introduced a multidistance measurement to reduce physiological interference based on recursive least squares (RLS) adaptive filtering. Monte Carlo simulations have been implemented to evaluate the performance of RLS adaptive filtering. However, its suitability and performance on human data still remain to be evaluated. Here, we address the issue of how to detect evoked hemodynamic response to auditory stimulus using RLS adaptive filtering method. A multidistance probe based on continuous wave fNIRS is devised to achieve the fNIRS measurement and further study the brain functional activation. This study verifies our previous findings that RLS adaptive filtering is an effective method to suppress global interference and also provides a practical way for real-time detecting brain activity based on multidistance measurement.
功能近红外光谱(fNIRS)的性能有时会因物理或系统生理活动引起的干扰而降低。fNIRS 记录过程中出现的几种干扰主要是由心脏脉冲、呼吸和自发的生理低频振荡引起的。在以前的工作中,我们介绍了一种基于递归最小二乘(RLS)自适应滤波的多距离测量方法来减少生理干扰。已经实施了蒙特卡罗模拟来评估 RLS 自适应滤波的性能。然而,其在人体数据上的适用性和性能仍有待评估。在这里,我们解决了如何使用 RLS 自适应滤波方法检测听觉刺激诱发的血液动力学反应的问题。设计了一种基于连续波 fNIRS 的多距离探头来实现 fNIRS 测量,并进一步研究大脑的功能激活。这项研究验证了我们之前的发现,即 RLS 自适应滤波是一种有效抑制全局干扰的方法,也为基于多距离测量的实时脑活动检测提供了一种实用方法。