防止警戒下降的声音唤醒与预警机制——基于模拟监控研究

The problem of the vigilance decrement has not been solved for nearly a hundred years. New researches are now focusing on the state of vigilance, namely how to keep the awakening-sleep of the moderate level to prevent vigilance decrement，thus forestall work failure. Electroencephalography (EEG) is a new technology to monitor the status of human brain activity, EEG and ERP can reflect the arousal level of human brain as well as cognitive processing. In order to carry out the experimental study of monitoring arousal level and arousal regulating technology，we designed our experiment based on computer simulated monitoring task. Our main assignment is to examine the vigilance performance, the cause of EEG spectral power fluctuation，as well as ERP and arousal level changing. Then, we will analyze their characteristics, relationship and mechanism under the task conditions of warning sound or background music for long time monitoring operation in lower event rate. Our purposes are as follows: Firstly，the project will investigate in the interaction among workload, brain EEG and ERP activity, arousal level and vigilance performance to obtain the condition of best performance, the optimal arousal level and the layered parameters of arousal model. Secondly, the project will explore the mechanism of sound warning and arousing, and the music awaking effect. Simultaneously，we will attempt to find the way to keep the optimal level of arousal which helps acquire the best performance on monitoring. Finally, our purpose is to construct arousal and early warning BCI model upon the level of arousal to prevent vigilance decrement. The strong significance of this model, which monitors the operator's arousal level by auto-machine and sense feedback, is that it could be applied to the design of other terminal monitoring tasks.

近百年的研究尚未解决警戒下降的难题。新的领域聚焦于人的警觉状态，即如何使监控者保持适度的觉醒水平以避免警戒下降与失误。脑电（EEG）是监测人脑工作状态的新技术，EEG和ERP可以反映人脑的觉醒水平和认知加工。此项目将以计算机模拟监控作业，开展觉醒水平监控与唤醒调节技术的实验研究。通过测量与分析告警声音和音乐等条件对低事件率负荷下的长时间监控作业绩效的影响及其引起的EEG小波、ERP和觉醒水平变化的特性、机理，将：（1）探索监控绩效、负荷、脑电变化与觉醒水平之间的关系及其变化的规律，以及获得不同监控绩效的不同觉醒水平及其觉醒水平分层EEG小波包特征模型；（2）探明声音的告警机制，以及声音和音乐的唤醒机理；（3）探索保持适合监控作业的觉醒水平的方法；（4）构建基于觉醒水平的唤醒与预警机制的脑机接口模型。此模型将适用于多种终端监控作业设计，以及对监控者的觉醒水平的自动化监控和唤醒反馈。

近百年的研究尚未解决警戒下降的难题。新的领域聚焦于人的警觉状态，即如何使监控者保持适度的觉醒水平以避免警戒下降与失误。脑电（EEG）是监测人脑工作状态的新技术，EEG和ERP可以反映人脑的觉醒水平和认知加工。此项目以计算机模拟监控作业，开展觉醒水平监控与唤醒调节技术的实验研究。通过测量与分析告警声音和音乐等条件对低事件率负荷下的长时间监控作业绩效的影响及其引起的EEG小波、ERP和觉醒水平变化的特性、机理。完成了：（1）探索了监控绩效、负荷、脑电变化与觉醒水平之间的关系及其变化的规律，以及获得不同监控绩效的不同觉醒水平及其觉醒水平分层EEG小波包特征模型；（2）探明了声音的告警机制，以及声音和音乐的唤醒机理；（3）探索了保持适合监控作业的觉醒水平的方法；（4）构建了基于觉醒水平的唤醒与预警机制的脑机接口模型。此模型将适用于多种终端监控作业设计，以及对监控者的觉醒水平的自动化监控和唤醒反馈。