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P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
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基于点击的电皮质学脑计算机接口使长期高性能开关扫描拼写成为可能.

Daniel N Candrea1, Samyak Shah2, Shiyu Luo3

  • 1Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. dcandre3@jh.edu.

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概括

大脑-计算机接口 (BCI) 能够帮助残疾人进行沟通. 一个单一的命令点击检测器,训练使用最小的数据,显示了强大的,长期的性能,以文字为基础的通信.

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科学领域:

  • 神经科学是一个神经科学.
  • 生物医学工程 生物医学工程
  • 康复技术 康复技术 康复技术

背景情况:

  • 大脑-计算机接口 (BCI) 为严重运动和语言障碍的人提供通信恢复.
  • 单个命令点击检测器代表了一个基本但有效的BCI能力.

研究的目的:

  • 在人类临床试验中使用电皮质谱 (ECoG) 评估点击解码系统的性能和长期稳定性.
  • 为了评估训练BCI点击探测器的可行性,使用有限的数据和最小的再培训.

主要方法:

  • 植入了一个高密度的ECoG BCI系统,覆盖了患有肌缩性侧面硬化症的参与者的感觉运动皮质.
  • 点击探测器在4天内使用不到44分钟的数据进行训练,在BCI使用前最多21天,并且在没有重新训练的情况下进行了90天的测试.

主要成果:

  • 参与者通过使用带有开关扫描拼写器的点击检测器实现了每分钟10.2个字符的中位拼写率.
  • 尽管信号功率的短暂波动,一个新训练的点击探测器表现出与更少的训练数据 (<15分钟) 相似的性能.

结论:

  • 一个点击探测器可以有效地使用一个小的ECoG数据集进行训练,在长时间内保持强大的性能.
  • 这表明了带有点击检测器的BCI为用户提供功能性,基于文本的通信的潜力.