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一种高性能语音神经假体

Francis R Willett1, Erin M Kunz2,3, Chaofei Fan4

  • 1Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA. willett2@gmail.com.

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此摘要是机器生成的。

这项研究引入了一种新的语音脑电脑接口 (BCI),从神经信号中解码语音尝试. 这种先进的BCI显著提高了患者恢复通讯的准确性和速度.

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科学领域:

  • 神经科学
  • 生物医学工程
  • 康复技术

背景情况:

  • 大脑与计算机接口 (BCI) 为严重患者提供了潜在的沟通途径.
  • 现有的语音BCI在准确性和词汇量方面存在局限性,阻碍了有效的沟通.
  • 骨髓缩小性侧面硬化症 (ALS) 逐渐影响言语,需要先进的辅助技术.

研究的目的:

  • 开发和评估使用皮质内微电极记录的高性能语音到文本BCI.
  • 评估BCI的准确性和速度解码ALS患者的言语尝试.
  • 研究与语音BCI发展相关的神经编码原理.

主要方法:

  • 使用皮质内微电极阵列记录试图说话时的神经活动.
  • 开发了解码算法来将神经信号转化为文本.
  • 使用不同词汇大小的词误率和测量解码速度来评估性能.

主要成果:

  • 在50个单词的词汇中实现了9.1%的错误率,比以前的最先进语言提高了2.7倍.
  • 展示了第一个成功的大词汇 (125,000 字) 解码,字错误率为 23.8%.
  • 达到了每分钟62个字的解码速度, 比之前的记录快3.4倍.

结论:

  • 高分辨率的神经记录可以通过BCI进行准确和快速的语音解码.
  • 语言的神经代码包含一些功能, 即使在长期之后,
  • 这种BCI技术为非说话者恢复沟通提供了一种可行的方法.