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Real-time system for extracting and monitoring the cerebral functional component during fNIRS measurements

机译:用于在FNIRS测量期间提取和监测脑功能组分的实时系统

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Functional near-infrared spectroscopy (fNIRS) can non-invasively detect hemodynamic changes associated with cerebral neural activation in human subjects. However, its signal is often affected by changes in the optical characteristics of tissues in the head other than brain. To conduct fNIRS measurements precisely and efficiently, the extraction and realtime monitoring of the cerebral functional component is crucial. We previously developed methods for extracting the cerebral functional component-the multidistance optode arrangement (MD) method and the hemodynamic modality separation (HMS) method. In this study, we implemented these methods in a software used with the fNIRS system OEG-17APD (Spectratech, Japan), and realized a real-time display of the extracted results. When using this system for human subject experiments, the baselines obtained with the MD and HMS methods were highly stabilized, whereas originally, the fNIRS signal fluctuated significantly when the subject moved. Through a functional experiment with repetitive single-sided hand clasping tasks, the extracted signals showed distinctively higher reproducibility than that obtained in the conventional measurements.
机译:功能近红外光谱(FNIR)可以非侵入地检测与人类受试者中的脑神经激活相关的血流动力学变化。然而,它的信号通常受到脑外的脑袋中组织的光学特性的变化的影响。精确有效地进行FNIR测量,脑功能组分的提取和实时监测至关重要。我们以前开发了提取脑功能组件 - 多陀光电装置(MD)方法和血流动力学模式分离(HMS)方法的方法。在本研究中,我们在与FNIR系统OEG-17APD(SpectraTech,Japan)一起使用的软件中实施了这些方法,并实现了提取结果的实时显示。当使用该系统进行人类对象实验时,用MD和HMS方法获得的基线高度稳定,而最初,当受试者移动时,FNIR信号显着波动。通过具有重复的单面手扣除任务的功能实验,提取的信号显示出比传统测量中获得的重复性明显更高。

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