Hybrid brain-computer interface with motor imagery and error-related brain activity
Hybrid brain-computer interface with motor imagery and error-related brain activity
复制标题
具有运动想象和错误相关大脑活动的混合脑机接口
DOI：
10.1088/1741-2552/abaa9d
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发表时间：
2020
影响因子：
4
通讯作者：
de Sa, Virginia R.
中科院分区：
文献类型：
--
作者：
Mousavi, Mahta;Krol, Laurens R.;de Sa, Virginia R.
脑机接口（BCI）系统直接从大脑读取和解释大脑活动。它们可以为患有神经退行性疾病或中风的患者提供交流或运动的手段。然而，大脑活动的非平稳性限制了在校准会话期间训练的算法到实时BCI控制的可靠转移。非平稳性的一个来源是用户对BCI输出（反馈）的大脑响应，例如，BCI反馈是否被用户感知为错误。通过考虑这些来源的非平稳性，可以提高BCI的可靠性。ApproachIn this work，we demonstrate a real-time implementation of a hybrid motor imagery BCI combining the information from the motor imagery signal and the error-related brain activity simultaneously so to gain benefit from both sources.Main resultsWe show significantly improved performance in real-time BCI control across 12 participants，与传统的运动想象脑机接口相比。在分类精度、目标命中率、控制的主观感觉和信息传递率方面有显著的改善。此外，我们的离线分析记录的EEG数据显示，错误相关的大脑活动提供了一个更可靠的信息来源比电机图像signal.SignificanceThis工作表明，第一次，错误相关的大脑活动分类器相比，电机图像分类器是更一致的校准数据和测试时，在网上控制。这可能解释了为什么提出的混合BCI允许为有需要的患者提供更可靠的通信或康复手段。
ObjectiveBrain-computer interface (BCI) systems read and interpret brain activity directly from the brain. They can provide a means of communication or locomotion for patients suffering from neurodegenerative diseases or stroke. However, non-stationarity of brain activity limits the reliable transfer of the algorithms that were trained during a calibration session to real-time BCI control. One source of non-stationarity is the user's brain response to the BCI output (feedback), for instance, whether the BCI feedback is perceived as an error by the user or not. By taking such sources of non-stationarity into account, the reliability of the BCI can be improved.ApproachIn this work, we demonstrate a real-time implementation of a hybrid motor imagery BCI combining the information from the motor imagery signal and the error-related brain activity simultaneously so as to gain benefit from both sources.Main resultsWe show significantly improved performance in real-time BCI control across 12 participants, compared to a conventional motor imagery BCI. The significant improvement is in terms of classification accuracy, target hit rate, subjective perception of control and information-transfer rate. Moreover, our offline analyses of the recorded EEG data show that the error-related brain activity provides a more reliable source of information than the motor imagery signal.SignificanceThis work shows, for the first time, that the error-related brain activity classifier compared to the motor imagery classifier is more consistent when trained on calibration data and tested during online control. This likely explains why the proposed hybrid BCI allows for a more reliable means of communication or rehabilitation for patients in need.
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影响因子：
3.7
作者：
Spüler M;Rosenstiel W;Bogdan M
通讯作者：
Bogdan M
DOI：
10.1080/2326263x.2019.1671040
发表时间：
2019
期刊：
Brain computer interfaces (Abingdon, England)
影响因子：
--
作者：
Mousavi M;de Sa VR
通讯作者：
de Sa VR
提高主动 BCI 中的信息传输率
DOI：
--
发表时间：
2017
期刊：
Graz Brain-Computer Interface Conference
影响因子：
--
作者：
V. D. Sa
通讯作者：
V. D. Sa
DOI：
--
发表时间：
2013
期刊：
影响因子：
--
作者：
A. S. Koerner
通讯作者：
A. S. Koerner
影响因子：
4.7
作者：
Spueler, Martin;Bensch, Michael;Kuebler, Andrea
通讯作者：
Kuebler, Andrea