摘要
脑-机接口技术旨在大脑与外部环境之间建立一种全新的不依赖于外周神经和肌肉的交流与控制通道。基于稳态视觉诱发电位的脑-机接口是目前信息传输率最高的无创脑-机接口范式,但是仍低于传统的交互方式。提出一种结合表面肌电与稳态视觉诱发电位的混合脑-机接口,以进一步提高系统的信息传输率。通过不同频率的高频稳态视觉诱发电位结合sEMG编码,实现二者混合脑-机接口系统。利用典型相关分析方法对SSVEP信号进行频率识别,sEMG的检测则采用频域分析方法。来自8名健康受试者的离线结果表明该系统能够获得84.28%的平均准确率,平均信息传输率为72.63 bits/min。这些结果为结合表面肌电与稳态视觉诱发电位的混合脑-机接口研究奠定了基础。
Brain-computer interface(BCI)technology aims to establish a new communication and control channel between the brain and the external environment that does not depend on peripheral nerves and muscles.The steady-state visual evoked potential(SSVEP)based brain-computer interface(BCI)is currently the non-invasive BCI paradigm with the highest information transmission rate,but it is still lower than the traditional interaction mode.In this paper,a hybrid brain-computer interface(BCI)combining surface electromyography(sEMG)and steady-state visual evoked potentials is proposed to further improve the information transmission rate of the system.A hybrid BCI system was realized by combining the SSVEP encoding at different frequencies with sEMG.The canonical correlation analysis method is used to identify the frequency of SSVEP signal,and the frequency domain analysis method is used to detect sEMG signal.Offline results from 8 healthy subjects show that the system can achieve an average accuracy of 84.28%and an average information transfer rate of 72.63 bits/min.These results lay the foundation for hybrid brain-computer interface studies combining surface EMG and steady-state visual evoked potentials.
作者
冯莉
Feng Li(Institute of Biomedical Engineering,Chinese Academy of Medical Sciences and Peking Union Medical College,Tianjin 300192,China)
出处
《电子测量技术》
北大核心
2023年第18期1-5,共5页
Electronic Measurement Technology
关键词
脑-机接口
稳态视觉诱发电位
表面肌电
典型相关分析
brain-computer interface
steady-state visual evoked potential
surface electromyography
canonical correlation analysis
