论文标题
使用联合神经影像学的嗜睡检测：概述和挑战
Drowsiness detection using combined neuroimaging: Overview and Challenges
论文作者
论文摘要
脑部计算机界面（BCIS）收集，分析和转换为指令，并将其发送到检测系统。在某些条件下，例如基于注意力的任务，BCI在脑部不足活动中变得越来越流行。研究人员最近使用了诸如EEG+FNIRS和EEG+FMRI之类的联合神经影像学技术来解决许多现实世界中的问题。嗜睡检测或睡眠惯性是联合神经影像技术的中心研究领域之一。本文旨在调查最新的基于神经影像学的BCI在嗜睡检测或睡眠惯性上的应用。为此，这是基于神经成像的嗜睡检测系统的唯一概述论文。
Brain-computer interfaces (BCIs) collect, analyze, and convert brain activity into instructions and send it to the detection system. BCI is becoming popular in under-brain activities in certain conditions such as attention-based tasks. Researchers have recently used combined neuroimaging techniques such as EEG+fNIRS and EEG+fMRI to solve many real-world problems. Drowsiness detection or sleep inertia is one of the central research areas for the combined neuroimaging techniques. This paper aims to investigate the recent application of combined neuroimaging-based BCI on drowsiness detection or sleep inertia. To this end, this is the only overview paper of the combined neuroimaging-based drowsiness detection system.
