嵌入式系统中运动想象脑-机接口编解码算法综述  

Review of Codec Algorithms for Motor Imagery Brain-Computer Interface in Embedded System

作　　者：于钦雯 周王成 戴亚康[2] 刘燕[1,2] YU Qinwen;ZHOU Wangcheng;DAI Yakang;LIU Yan(School of Intelligence and Information Engineering,Shandong University of Traditional Chinese Medicine,Jinan 250355,China;Suzhou Institute of Biomedical Engineering and Technology,Chinese Academy of Sciences,Suzhou,Jiangsu 215163,China)

机构地区：[1]山东中医药大学智能与信息工程学院,济南250355 [2]中国科学院苏州生物医学工程技术研究所,江苏苏州215163

出　　处：《计算机工程与应用》2024年第18期50-65,共16页Computer Engineering and Applications

基　　金：国家自然科学基金(62271481);江苏省重点研发计划(BE2021012-5);科技创新2030“脑科学与类脑研究”重大项目(2022ZD0208500);苏州市基础研究试点项目(SJC2022012)。

摘　　要：脑-机接口技术通过在大脑与外部设备之间建立信息传输通路,使用户能够对外部设备进行直接控制。近年来,基于运动想象范式的脑-机接口编解码算法研究在医疗健康、教育娱乐及日常生活设备中的应用范围越来越广,这些算法通常需要嵌入到硬件设备中来满足实际应用的需求。介绍了近年来嵌入式系统中运动想象脑-机接口编解码算法研究现状,从传统机器学习算法和深度学习算法两个角度指出其对应的优缺点。重点介绍四类常用嵌入式平台的代表性设备及其优缺点,并针对不同的应用场景给出相应的硬件选型建议。归纳了更适用于嵌入式脑-机接口系统的评价指标并最终总结了领域内现存的挑战与未来发展方向。Brain-machine interface technology establishes a communication pathway between the brain and external devices,enabling users to directly control these devices.In recent years,research on encoding and decoding algorithms for brain-machine interfaces based on the motor imagery paradigm has found increasing applications in healthcare,educa-tion,entertainment,and everyday life devices.These algorithms often need to be embedded into hardware devices to meet the requirements of practical applications.Therefore,this paper introduces the research status of brain-computer interface codec algorithms for motion imagination in embedded systems in recent years,and points out their advantages and disad-vantages from two perspectives of traditional machine learning algorithms and deep learning algorithms.Then,it focuses on the four types of commonly used embedded platform representative equipment and their advantages and disadvantages,and gives corresponding hardware selection suggestions for different application scenarios.In addition,this paper summa-rizes the evaluation indicators that are more suitable for embedded brain-computer interface systems,and finally summa-rizes the existing challenges and future development directions in the field.

关 键 词：脑-机接口 运动想象 脑电信号编解码算法 嵌入式系统 

分 类 号：R318[医药卫生—生物医学工程] TN911.7[医药卫生—基础医学]