A driver fatigue recognition model based on information fusion and dynamic Bayesian network

被引：243

作者：

Yang, Guosheng ^{[2
]}

Lin, Yingzi ^{[1
]}

Bhattacharya, Prabir ^{[3
]}

机构：

[1] Northeastern Univ, Dept Mech & Ind Engn, Boston, MA 02115 USA

[2] Minzu Univ China, Sch Informat Engn, Beijing 475001, Peoples R China

[3] Univ Cincinnati, Dept Comp Sci, Cincinnati, OH 45221 USA

来源：

INFORMATION SCIENCES | 2010年 / 180卷 / 10期

基金：

加拿大自然科学与工程研究理事会; 美国国家科学基金会;

关键词：

Driver fatigue recognition; Dynamic Bayesian network; Contextual features; Physiological features; Information fusion;

D O I：

10.1016/j.ins.2010.01.011

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a driver fatigue recognition model based on the dynamic Bayesian network, information fusion and multiple contextual and physiological features. We include features such as the contact physiological features (e.g., ECG and EEG), and apply the first-order Hidden Markov Model to compute the dynamics of the Bayesian network at different time slices. The experimental validation shows the effectiveness of the proposed system; also it indicates that the contact physiological features (especially ECG and EEG) are significant factors for inferring the fatigue state of a driver. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：1942 / 1954

页数：13

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