IEEE Trans Biomed Circuits Syst. 2010 Aug;4(4):214-22. doi: 10.1109/TBCAS.2010.2046415.
A real-time wireless electroencephalogram (EEG)-based brain-computer interface (BCI) system for drowsiness detection has been proposed. Drowsy driving has been implicated as a causal factor in many accidents. Therefore, real-time drowsiness monitoring can prevent traffic accidents effectively. However, current BCI systems are usually large and have to transmit an EEG signal to a back-end personal computer to process the EEG signal. In this study, a novel BCI system was developed to monitor the human cognitive state and provide biofeedback to the driver when drowsy state occurs. The proposed system consists of a wireless physiological signal-acquisition module and an embedded signal-processing module. Here, the physiological signal-acquisition module and embedded signal-processing module were designed for long-term EEG monitoring and real-time drowsiness detection, respectively. The advantages of low owner consumption and small volume of the proposed system are suitable for car applications. Moreover, a real-time drowsiness detection algorithm was also developed and implemented in this system. The experiment results demonstrated the feasibility of our proposed BCI system in a practical driving application.
已经提出了一种基于实时无线脑电图（EEG）的脑机接口（BCI）系统来检测困倦。昏昏欲睡的驾驶已被牵连为许多事故的一个原因。因此，实时困倦监测可以有效地防止交通事故。然而，目前的 BCI 系统通常较大，并且必须将 EEG 信号传输到后端个人计算机以处理 EEG 信号。在这项研究中，开发了一种新颖的 BCI 系统来监测人类认知状态，并在出现困倦状态时向驾驶员提供生物反馈。所提出的系统包括无线生理信号采集模块和嵌入式信号处理模块。在这里，生理信号采集模块和嵌入式信号处理模块分别设计用于长期 EEG 监测和实时困倦检测。该系统的低所有者消耗和小体积的优点适用于汽车应用。此外，还开发并在该系统中实现了一种实时困倦检测算法。实验结果证明了我们提出的 BCI 系统在实际驾驶应用中的可行性。
