Optical EEG (OEEG): A novel technique toward plug-and-play non-invasive brain imaging and human-machine interfacing

E. Kamrani, S. Hahn, S. H. Andy Yun
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引用次数: 6

Abstract

Summary form only given. The human brain dynamics can be studied based on the fast-neuronal and slow-hemodynamic signals. Referring to the available brain imaging techniques, the electroencephalography (EEG) and Magnetoencephalography (MEG) can only measure the fast-neuronal signal. Positron-emission tomography (PET) and Functional-magnetic-resonance-imaging (tMRI) also can measure only the slowhemodynamic signal. However, the functional-near-infrared spectroscopy (fNIRS) is the only imaging system capable of detecting both fast-neuronal and slow-hemodynamic signals. In this research we have first implemented a miniaturized low-power fNIRS front-end using standard CMOS technology for monitoring the hemodynamic signals (HbO & HbR) in continuous wave (CW) and time-correlated single photon counting (TCSPC) modes of operation. A new on-chip implemented system (called Optical EEG: OEEG) is also proposed to estimate the neural activities based on the acquired optical data using fNIRS. This is the first proposed wholly optical system capable of monitoring neuronal and hemodynamic signals and it is the first step towards introducing an optical alternative system for EEG. In order to develop a real-time system, we have proposed detecting the stable, controllable and observable hemodynamic states of the brain, based on the continuous-discrete extended-Kalman-filter and bifurcation analysis of the balloon-model. It extracts and validates the states and verifies their stability, controllability and observability. The stable, controllable and observable states are used for further processing. In contrast to the other available complex techniques, the complexity of the proposed Algorithm is moderate and its implementation requires only raw data) extracted directly from a continuous-wave fNIRS-channel. The results confirm the efficiency of the proposed technique in dealing with noise and movement-artifacts. It increases the signal-to-noise-ratio (SNR) and the speed.
光学脑电图(OEEG):即插即用无创脑成像和人机接口的新技术
只提供摘要形式。基于快神经元和慢血流动力学信号可以研究人脑动力学。参考现有的脑成像技术,脑电图(EEG)和脑磁图(MEG)只能测量快速神经元信号。正电子发射断层扫描(PET)和功能磁共振成像(tMRI)也只能测量慢血流动力学信号。然而,功能近红外光谱(fNIRS)是唯一能够同时检测快速神经元和慢速血流动力学信号的成像系统。在这项研究中,我们首先实现了一个小型化的低功率fNIRS前端,使用标准的CMOS技术来监测连续波(CW)和时间相关单光子计数(TCSPC)模式下的血流动力学信号(HbO和HbR)。本文还提出了一种新的片上实现系统(称为光学脑电图:OEEG),该系统利用近红外光谱(fNIRS)获取的光学数据来估计神经活动。这是第一个能够监测神经元和血液动力学信号的全光学系统,也是引入脑电图光学替代系统的第一步。为了开发一个实时系统,我们提出了基于连续离散扩展卡尔曼滤波和气球模型的分岔分析来检测大脑的稳定、可控和可观察的血流动力学状态。对状态进行提取和验证,验证状态的稳定性、可控性和可观察性。利用稳定、可控和可观察的状态进行进一步处理。与其他可用的复杂技术相比,该算法的复杂性适中,其实现只需要直接从连续波fnirs信道中提取原始数据。实验结果证实了该方法在处理噪声和运动伪影方面的有效性。它提高了信噪比(SNR)和速度。
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