基于功能性近红外光谱的脑机接口综述

Functional Near-Infrared Spectroscopy-Based Brain-Computer Interface

脑机接口(BCI)技术通过解码分析大脑的神经活动来实现人脑与计算机等外部设备的直接交互,可作为信息交流和恢复运动功能的手段,已被应用于通信、智能机器人控制、生物医学和神经康复等诸多领域。功能性近红外光谱(fNIRS)是一种可用于探测大脑皮层血红蛋白浓度变化的光学成像技术,近些年被用于无创BCI的发展。本文系统、详细地综述了fNIRS-BCI的发展历程、组成原理、涉及的关键技术、未来的发展趋势以及局限性和待解决的问题,重点对特征分类算法进行了全面统计,并将结果与前人的部分统计数据进行对比分析,归纳出一些有价值的结论与观点。本文旨在让有兴趣探索fNIRS-BCI的研究人员对其有一个全面而具体的了解,甚至为他们提供一定的参考和指导。

The brain-computer interface(BCI)technology enables direct interaction between the human brain and computers or other external devices by analyzing and decoding neural activity.It can be used as a means of information exchange or the restoration of motor functions and has been applied in communications,intelligent robot control,biomedicine,and neurorehabilitation,etc.Functional near-infrared spectroscopy(fNIRS),an optical imaging technique that can be used to detect changes in hemoglobin concentration within the cerebral cortex,has been employed recently in the development of noninvasive BCI.The development history,composition principles,key technologies,future development trends,limitations,and problems of fNIRS-BCI are reviewed systematically and in detail.Particularly,the feature-classification algorithm was analyzed comprehensively,and the result was compared with statistical data from its predecessors to summarize several valuable conclusions and opinions.This review is designed to provide a comprehensive and specific understanding of fNIRS-BCI and references and guidance.