Evaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Driving.
Evaluation of a Dry EEG System for Application of Passive Brain-Computer Interfaces in Autonomous Driving.
复制标题
干式脑电图系统在自动驾驶中应用被动脑机接口的评估。
DOI：
10.3389/fnhum.2017.00078
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发表时间：
2017
影响因子：
2.9
通讯作者：
Gramann K
中科院分区：
文献类型：
--
作者：
Zander TO;Andreessen LM;Berg A;Bleuel M;Pawlitzki J;Zawallich L;Krol LR;Gramann K
我们测试了16通道干脑电图（EEG）系统在实验室环境中的适用性和信号质量，并在受控的，现实的条件下，在汽车。我们调查的目的是估计被动脑机接口（pBCI）在自动驾驶场景中的工作情况。评价考虑了未经培训人员自我适用性的速度和准确性、记录的EEG数据的质量、驾驶相关运动后头部电极位置的变化、可用性和系统复杂性以及随时间推移的佩戴舒适度。一个实验在一辆静止的车内和车外进行，车内有发动机、空调和静音收音机。信号质量足以在时域和频域中进行标准EEG分析以及用于pBCI。虽然车辆引起的干扰对数据质量的影响微不足道，但驾驶相关的运动导致电极位置发生强烈变化。一般而言，所使用的EEG系统允许帽和电极的快速自适用性。系统的可用性评估仍然是可接受的，而佩戴舒适度随着时间的推移由于摩擦和头部压力而大幅下降。从这些结果中，我们得出结论，评估的系统应该提供在自动驾驶环境中的应用程序的基本要求。尽管如此，建议进一步改进以减少由于身体运动而引起的系统移位，并增加耳机的可用性和佩戴舒适性。
We tested the applicability and signal quality of a 16 channel dry electroencephalography (EEG) system in a laboratory environment and in a car under controlled, realistic conditions. The aim of our investigation was an estimation how well a passive Brain-Computer Interface (pBCI) can work in an autonomous driving scenario. The evaluation considered speed and accuracy of self-applicability by an untrained person, quality of recorded EEG data, shifts of electrode positions on the head after driving-related movements, usability, and complexity of the system as such and wearing comfort over time. An experiment was conducted inside and outside of a stationary vehicle with running engine, air-conditioning, and muted radio. Signal quality was sufficient for standard EEG analysis in the time and frequency domain as well as for the use in pBCIs. While the influence of vehicle-induced interferences to data quality was insignificant, driving-related movements led to strong shifts in electrode positions. In general, the EEG system used allowed for a fast self-applicability of cap and electrodes. The assessed usability of the system was still acceptable while the wearing comfort decreased strongly over time due to friction and pressure to the head. From these results we conclude that the evaluated system should provide the essential requirements for an application in an autonomous driving context. Nevertheless, further refinement is suggested to reduce shifts of the system due to body movements and increase the headset's usability and wearing comfort.