项目名称: 基于非线性动力分析的脑力疲劳评估和预测应用基础研究
项目编号: No.61201124
项目类型: 青年科学基金项目
立项/批准年度: 2013
项目学科: 电子学与信息系统
项目作者: 陈兰岚
作者单位: 华东理工大学
项目金额: 25万元
中文摘要: 随着生活节奏的加快和工作压力的加大,脑力疲劳日益成为影响人们身心健康和工作效率的最大负面因素之一。脑力疲劳的传统评估方法如主观量表和行为学测试存在信度低且需要被试者主动配合等局限性。近年来,一些电生理指标已经介入脑力疲劳的研究中,但由于电生理信号源于非线性、时变、非平稳的复杂系统,故而传统信号处理方法存在很大的局限性。考虑到大脑系统的非线性动力学特性和单一研究方法存在的局限性,本项目提出运用非线性动力学理论结合经典信号处理方法来研究脑电、心电等多种电生理信号,旨在揭示脑力疲劳的非线性本质和更好地洞察人体的节律。在电生理指标研究基础上,本课题将进一步融合主观量表和行为学指标,利用机器智能学习方法来系统、综合、定量地对脑力疲劳进行风险评估和早期预警研究。本课题的研究成果将为多参数信号脑力疲劳实时监测技术提供理论基础,更为降低因脑力疲劳造成的交通事故、操作故障、人员伤亡提供理论依据和有效手段。
中文关键词: 脑力疲劳;电生理信号;非线性动力特征;多信息融合;定量评估
英文摘要: With the accelerated pace of life and increased work pressure, mental fatigue is increasingly becoming one of the biggest negative factors which affect human's mental health and work efficiency. Traditional assessment methods for mental fatigue such as subjective scales and behavioral testing show low reliability and require subjects to take the initiative to the experiments. In recent years, a number of electrophysiological parameters have been applied into the research of mental fatigue.Usually,electrophysiological signals are acquired from nonlinear, time-varying and non-stationary complex systems. Therefore,traditional analytical methods such as power spectrum analysis have significant limitations to analyze such signals. Taking into account the nonlinear dynamics of human brain system and the limitations of a single method, this project proposes the application of nonlinear dynamics theory combined with traditional signal processing methods to study the EEG, ECG, and other electrophysiological signals, designed to reveal the nonlinear nature of mental fatigue and have a better insight into the rhythm of human body.A systematic evaluation based on subjective questionnaires, behavioral assessment and electrophysiological indicators are proposed. This evaluation system can provide a comprehensive evaluation fo
英文关键词: mental fatigue;electrophysiological signals;nonlinear dynamics;multi-information fusion;quantitative evaluation