A brain-computer interface (BCI) for the locked-in:: comparison of different EEG classifications for the thought translation device
A brain-computer interface (BCI) for the locked-in:: comparison of different EEG classifications for the thought translation device
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DOI：
10.1016/s1388-2457(02)00411-x
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发表时间：
2003-03-01
影响因子：
4.7
通讯作者：
Birbaumer, N
中科院分区：
文献类型：
--
作者：
Hinterberger, T;Kübler, A;Birbaumer, N
目的：研制用于脑-机交互的思维翻译装置（TTD），使完全瘫痪的患者能够进行交流。患者通过反馈训练自愿调节皮层慢电位（SCP）来选择字母。本研究报告的比较不同的方法脑电图（EEG）分析，以提高拼写准确性与TTD上的一个严重瘫痪patient.Methods的6650试验的数据集：选择的字母发生超过一定的SCP振幅阈值。为了增强患者对额外事件相关皮层电位的控制，开发了具有两个滤波器特性（“混合滤波器”）的滤波器并在线应用。为了提高离线性能，阈值相关决策的标准是不同的。不同类型的判别分析被施加到EEG数据集，以及小波变换的EEG data.Results：的混合滤波条件增加了患者的性能在线相比，单独的SCP滤波器。基于所需选择和拒绝之间的比率的阈值导致离线的进一步改进。判别分析的时间序列SCP数据和小波变换的数据增加了病人的正确响应率off-line.Conclusions：它是可能的沟通与事件相关电位使用混合滤波反馈方法。由于小波变换后的数据在试验结束前不能在线反馈，因此只有在脑机接口（BCI）不需要立即反馈时才适用。对于未来的BCI，小波变换的数据应该服务于BCI，而无需立即反馈。逐步小波变换甚至允许立即反馈。(C)2003爱思唯尔科学爱尔兰有限公司保留所有权利。
Objective: The Thought Translation Device (TTD) for brain-computer interaction was developed to enable totally paralyzed patients to communicate. Patients learn to regulate slow cortical potentials (SCPs) voluntarily with feedback training to select letters. This study reports the comparison of different methods of electroencephalographic (EEG) analysis to improve spelling accuracy with the TTD on a data set of 6650 trials of a severely paralyzed patient.Methods: Selections of letters occurred by exceeding a certain SCP amplitude threshold. To enhance the patient's control of an additional event-related cortical potential, a filter with two filter characteristics ('mixed filter') was developed and applied on-line. To improve performance off-line the criterion for threshold-related decisions was varied. Different types of discriminant analysis were applied to the EEG data set as well as on wavelet transformed EEG data.Results: The mixed filter condition increased the patients' performance on-line compared to the SCP filter alone. A threshold, based on the ratio between required selections and rejections, resulted in a further improvement off-line. Discriminant analysis of both time-series SCP data and wavelet transformed data increased the patient's correct response rate off-line.Conclusions: It is possible to communicate with event-related potentials using the mixed filter feedback method. As wavelet transformed data cannot be fed back on-line before the end of a trial, they are applicable only if immediate feedback is not necessary for a brain-computer interface (BCI). For future BCIs, wavelet transformed data should serve for BCIs without immediate feedback. A stepwise wavelet transformation would even allow immediate feedback. (C) 2003 Elsevier Science Ireland Ltd. All rights reserved.