利用静息态EEG预测事件相关潜在拼写能力
Prediction of Event Related Potential Speller Performance Using Resting-State EEG
摘要：
事件相关电位（ERP）拼写器可用于闭锁或严重受伤患者的设备控制和通信。然而，诸如学科间绩效不稳定和ERP文盲等问题仍然没有得到解决。因此，有必要在执行ERP拼写器之前预测分类性能，以便有效地使用它。在这项研究中，我们调查了ERP拼写前的休息状态与ERP拼写成绩的相关性。具体而言，我们使用了四个大脑区域和五个频段的频谱功率和功能连接。因此，额叶的δ功率和δ、α、γ波段的功能连接与ERP拼写者的成绩显著相关。此外，我们预测ERP拼写性能使用EEG特征在休息状态。这些发现可能有助于调查ERP文盲，并考虑为每个用户的适当的替代品。
英文摘要：
Event-related potential (ERP) speller can be utilized in device control and communication for locked-in or severely injured patients. However, problems such as inter-subject performance instability and ERP-illiteracy are still unresolved. Therefore, it is necessary to predict classification performance before performing an ERP speller in order to use it efficiently. In this study, we investigated the correlations with ERP speller performance using a resting-state before an ERP speller. In specific, we used spectral power and functional connectivity according to four brain regions and five frequency bands. As a result, the delta power in the frontal region and functional connectivity in the delta, alpha, gamma bands are significantly correlated with the ERP speller performance. Also, we predicted the ERP speller performance using EEG features in the resting-state. These findings may contribute to investigating the ERP-illiteracy and considering the appropriate alternatives for each user.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
