Experimental study of fatigue degree quantification for multi-feature fusion identification

• 作 者: 孙伟 Zhu Jiandong Zhang Xiaorui He Jun Zhang Weigong
• 机 构: School of Information and Control,Nanjing University of Information Science & Technology,School of E
• 出 处: High Technology Letters
• 发表日期: 2014年02期
• 关键词: fatigue quantification subjective traffic scene BPNN multivariate quantization c

A comprehensive quantification method of fatigue degree is proposed concerning subjective and objective quantifications.Using the fatigue degree test software,fatigue degree is objectively quantified by analyzing the reaction and operation abilities of drivers about traffic signals.By comparison experiment with that EEG signal based,multivariate statistical analysis and fusion identification based on BP neural network(BPNN) results show that the experimental procedure is simple and practical,and the proposed method can reveal the correlation between fatigue feature parameters and fatigue degree in theory,and also can achieve accurate and reliable quantification of fatigue degree,especially under the associated action of multiple fatigue feature parameters.

A comprehensive quantification method of fatigue degree is intended concerning subjective and objective quantifications. Using the fatigue degree test software, fatigue degree is objectively quantified by analyzing the reaction and operation abilities of drivers about traffic signals. BY rat experiment with that EEG signal based, multivariate statistical analysis and fusion identification based on BP neural network (BPNN) results show that the experimental procedure is simple and practical, and the proposed method can reveal the correlation between fatigue feature parameters and fatigue degree in theory, and also can achieve accurate and reliable quantification of fatigue degree, especially under the associated action of multiple fatigue feature parameters.