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基于生理信号的警觉度检测研究综述

Survey on Physiological Signal-Based Vigilance Detection

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【作者】 张飞杨樊尚春郑德智

【Author】 ZHANG Fei-yang;FAN Shang-chun;ZHENG De-zhi;School of Instrumentation and Optoelectronic Engineering, Beihang University;Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University;Key Laboratory of Quantum Sensing Technology, Ministry of Industry and Information Technology;Research Institute for Frontier Science, Beihang University;

【机构】 北京航空航天大学仪器科学与光电工程学院北京航空航天大学大数据精准医疗高精尖创新中心工业和信息化部量子传感技术重点实验室北京航空航天大学前沿科学技术创新研究院

【摘要】 警觉度反映了大脑的警惕状态。在航空航天、车辆驾驶、医疗军事等领域检测操作员的警觉度对减少事故概率具有重要意义。综述了近10年在基于生理信号的警觉度检测领域的研究进展,将其分为基于脑电、心电、脑血红蛋白浓度、其他生理信号和多生理信号五类,分析了各类方法的现状和发展趋势,发现目前使用的生理信号中,脑电最为常用,心电、眼电、脑血红蛋白浓度次之。且绝大多数研究仅对清醒和困倦这两种警觉水平进行判断,分类数较低。目前研究一方面趋向于通过寻找新的敏感特征、改进检测算法、结合其他生理信号等来提高准确率;另一方面趋向于开发穿戴式、无线化的生理信号传感器以推进警觉度检测实用化。

【Abstract】 Vigilance represents the state of brain alertness.Detecting operators’ vigilance is of great significance to reduce the probability of accidents in aerospace, vehicle driving, medical and military fields.The research progress in the field of vigilance detection based on physiological signals in recent ten years is reviewed, which is divided into five categories based on electroencephalogram(EEG),electrocardiogram(ECG),cerebral hemoglobin concentration(CHC),other physiological signals and multiple physiological signals.The present situation and development trend of five kinds of methods are analyzed.It is found that among the physiological signals used, EEG is the most commonly used, followed by ECG,EOG,and CHC.Most studies classified two levels of vigilance including wakefulness and drowsiness.On the one hand, the current research tends to improve accuracy by finding new sensitive features, improving detection algorithms, and combining other physiological signals; on the other hand, it tends to develop wearable, wireless sensors of physiological signals to promote the practicality of vigilance detection.

【基金】 北京航空航天大学校级一流本科课程建设项目(42020076);北京航空航天大学“凡舟”教育基金(54531737);北京高等教育“本科教学改革创新项目”(重点项目)(ZF211B2002);
  • 【文献出处】 测控技术 ,Measurement & Control Technology , 编辑部邮箱 ,2021年11期
  • 【分类号】R318;TN911.7
  • 【下载频次】297
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