脑-机接口
深度学习
接口(物质)
计算机科学
人机交互
人工智能
信号(编程语言)
神经科学
心理学
脑电图
最大气泡压力法
气泡
并行计算
程序设计语言
作者
Xiang Zhang,Lina Yao,Xianzhi Wang,Jessica J. M. Monaghan,David McAlpine
出处
期刊:Cornell University - arXiv
日期:2019-05-10
被引量:14
摘要
Brain-Computer Interface (BCI) bridges the human's neural world and the outer physical world by decoding individuals' brain signals into commands recognizable by computer devices. Deep learning has lifted the performance of brain-computer interface systems significantly in recent years. In this article, we systematically investigate brain signal types for BCI and related deep learning concepts for brain signal analysis. We then present a comprehensive survey of deep learning techniques used for BCI, by summarizing over 230 contributions most published in the past five years. Finally, we discuss the applied areas, opening challenges, and future directions for deep learning-based BCI.
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