Statistical spatial filtering for a P300-based BCI: Tests in able-bodied, and patients with cerebral palsy and amyotrophic lateral sclerosis
Statistical spatial filtering for a P300-based BCI: Tests in able-bodied, and patients with cerebral palsy and amyotrophic lateral sclerosis
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DOI：
10.1016/j.jneumeth.2010.11.016
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发表时间：
2011-02-15
影响因子：
3
通讯作者：
Castelo-Branco, Miguel
中科院分区：
文献类型：
--
作者：
Pires, Gabriel;Nunes, Urbano;Castelo-Branco, Miguel
在现实环境中，脑机接口（bci）的有效使用取决于令人满意的吞吐量。在基于P300的BCI中，这可以通过减少检测P300信号所需的试验次数来实现。然而，P300事件相关电位的低信噪比（SNR）阻碍了这一任务的完成。本文提出了一种基于p300标准拼字系统的高效方法，该方法既能实现对残疾人受试者的高分类准确率，又能实现对健全人受试者的高传输率。该系统在3名脑瘫（CP）患者、2名肌萎缩侧索硬化症（ALS）患者和19名健全受试者中进行了测试。本文提出了三种统计空间滤波器的应用。第一种是波束形成器，它可以最大限度地提高信号功率和噪声功率（Max-SNR）的比率。第二种是基于Fisher准则（FC）的波束形成器。第三种方法将FC波束形成器与同时满足次优两个标准（C-FMS）的最大信噪比波束形成器级联。BCI系统的校准过程采集数据大约需要5分钟，获取空间滤波器和分类模型大约需要几分钟。在线结果显示，残疾受试者的平均准确率和转移率仅略低于健全受试者。选取24个参与者中的23个，平均结果达到了每分钟4.33个符号的传输速率，准确率为91.80%，对应于每分钟19.18比特的带宽。研究表明，该方法是可行的，有效的通信速率是可以实现的。(C) 2010 Elsevier B.V.版权所有
The effective use of brain-computer interfaces (BCIs) in real-world environments depends on a satisfactory throughput. In a P300-based BCI, this can be attained by reducing the number of trials needed to detect the P300 signal. However, this task is hampered by the very low signal-to-noise-ratio (SNR) of P300 event related potentials. This paper proposes an efficient methodology that achieves high classification accuracy and high transfer rates for both disabled and able-bodied subjects in a standard P300-based speller system. The system was tested by three subjects with cerebral palsy (CP), two subjects with amyotrophic lateral sclerosis (ALS), and nineteen able-bodied subjects.The paper proposes the application of three statistical spatial filters. The first is a beamformer that maximizes the ratio of signal power and noise power (Max-SNR). The second is a beamformer based on the Fisher criterion (FC). The third approach cascades the FC beamformer with the Max-SNR beamformer satisfying simultaneously sub-optimally both criteria (C-FMS). The calibration process of the BCI system takes about 5 min to collect data and a couple of minutes to obtain spatial filters and classification models.Online results showed that subjects with disabilities have achieved, on average, an accuracy and transfer rate only slightly lower than able-bodied subjects. Taking 23 of the 24 participants, the averaged results achieved a transfer rate of 4.33 symbols per minute with a 91.80% accuracy, corresponding to a bandwidth of 19.18 bits per minute. This study shows the feasibility of the proposed methodology and that effective communication rates are achievable. (C) 2010 Elsevier B.V. All rights reserved.