Ma Xiaojie, Miao Tianchao, Xie Fawen, Zhang Jieyu, Zheng Lulu, Liu Xiang, Hai Hangrui
School of Mechanical Engineering, Henan Institute of Technology, Xinxiang 453003, China.
School of Computer Science and Technology, Henan Institute of Technology, Xinxiang 453003, China.
Micromachines (Basel). 2025 May 14;16(5):576. doi: 10.3390/mi16050576.
Functional near-infrared spectroscopy is a noninvasive neuroimaging technique that uses optical signals to monitor subtle changes in hemoglobin concentrations within the superficial tissue of the human body. This technology has widespread applications in long-term brain-computer interface monitoring within both traditional medical domains and, increasingly, domestic settings. The popularity of this approach lies in the fact that new single-channel brain oxygen sensors can be used in a variety of scenarios. Given the diverse sensor structure requirements across applications and numerous approaches to data acquisition, the accurate extraction of comprehensive brain activity information requires a multichannel near-infrared system. This study proposes a novel distributed multichannel near-infrared system that integrates two near-infrared light emissions at differing wavelengths (660 nm, 850 nm) with a photoelectric receiver. This substantially improves the accuracy of regional signal sampling. Through a basic long-time mental arithmetic paradigm, we demonstrate that the accompanying algorithm supports offline analysis and is sufficiently versatile for diverse scenarios relevant to the system's functionality.
功能近红外光谱技术是一种非侵入性神经成像技术，它利用光信号来监测人体表层组织内血红蛋白浓度的细微变化。这项技术在传统医学领域以及越来越多的家庭环境中的长期脑机接口监测方面有着广泛应用。这种方法的受欢迎之处在于新型单通道脑氧传感器可用于多种场景。鉴于不同应用对传感器结构的要求各异以及数据采集方法众多，准确提取全面的脑活动信息需要一个多通道近红外系统。本研究提出了一种新型分布式多通道近红外系统，该系统将两个不同波长（660纳米、850纳米）的近红外光发射与一个光电接收器集成在一起。这大大提高了区域信号采样的准确性。通过一个基本的长时间心算范式，我们证明了配套算法支持离线分析，并且对于与系统功能相关的各种场景具有足够的通用性。
