脑-机接口
运动表象
计算机科学
任务(项目管理)
接口(物质)
诱发电位
人工智能
视觉诱发电位
力矩(物理)
可视化
脑电图
语音识别
计算机视觉
心理学
神经科学
工程类
物理
系统工程
气泡
经典力学
最大气泡压力法
并行计算
作者
Jiaxin Li,Jing Zhao,Yuankai Shi
标识
DOI:10.1109/wrcsara57040.2022.9903988
摘要
Hybrid brain-computer interfaces have the advantage of higher accuracy and more commands. This paper presents a hybrid brain-computer interface (BCI) paradigm based on steady-state visual evoked potentials (SSVEP) and motor imagery(MI).The subject started the first SSVEP task, and 2 seconds later the subject was asked to perform the second MI task and keep both tasks running simultaneously. The moment when the second task was joined was defined as the moment of switching. The performance of SSVEP was improved after the switch. Five healthy subjects participated in the experiment. The experimental results demonstrated the improvement of SSVEP classification accuracy, in addition to demonstrating that the performance of most of the subject MI was not affected in the paradigm.
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