EEG Band Power for Driver Mental Workload Monitoring
Drivers mental overload is one of the most important contributors in road fatalities in recent years. Our group, aiming to provide a new human-machine interface for improving traffic safety using brain signals, has conducted a number of researches for the driver mental workload monitoring based on Electroencephalography (EEG). This article presents a broad investigation of various EEG Band Power parameters which could be the underlying candidates for driver mental workload assessment. Therefore a simulated driving task -the Lane Change Task (LCT) -combined with a secondary auditory task-the Paced Auditory Addition Serial Task (PASAT) -was adopted. In a first step, a single task (LCT) was used. The task load levels were investigated by manipulating the speed settings (low, moderate, high). For increasing the task load of the LCT the secondary task paradigm PASAT was added. We conclude that in this multiple task setting different task load levels should be induced by different paces of PASAT (a slow and a fast PASAT). Five frequency bands (i.e., delta, theta, alpha, beta, and gamma) and four band power ratios (i.e. theta/beta, theta/alpha, alpha/beta, and fro-theta/par-alpha) were extracted. The analysis of band power activity revealed that there were no obvious changes in band power activity when the task load varied with the speed levels in the single task condition. However, quite different results were obtained in the dual task condition. An increase of delta, decrease of beta and decrease of parietal alpha were found as the overall task load increased. In addition, the ratios of theta/beta, theta/alpha, and fro-theta/par-alpha consistently exhibited a considerable increase when the task load changed in the dual task condition.
Shengguang Lei Sebastian Welke Matthias Roetting
Chair of Human-Machine Systems, Berlin Institute of Technology, Berlin, Germany Chair of Human-Machine Systems, Berlin Institute of Technology, Berlin, Germany Center of Human-Mach Chair of Human-Machine Systems, Berlin Institute of Technology, Berlin, Germany Center of Human-Mach
国际会议
17th World Congress on Ergonomics(第十七届国际人类工效学大会)
北京
英文
1-7
2009-08-09（万方平台首次上网日期，不代表论文的发表时间）