標題: | The effects of different fatigue levels on brain-behavior relationships in driving |
作者: | Huang, Kuan-Chih Chuang, Chun-Hsiang Wang, Yu-kai Hsieh, Chi-Yuan King, Jung-Tai Lin, Chin-Teng 電機工程學系 腦科學研究中心 Department of Electrical and Computer Engineering Brain Research Center |
關鍵字: | brain dynamics;electroencephalograms;fatigue;longitudinal assessment |
公開日期: | 1-一月-1970 |
摘要: | Background In the past decade, fatigue has been regarded as one of the main factors impairing task performance and increasing behavioral lapses during driving, even leading to fatal car crashes. Although previous studies have explored the impact of acute fatigue through electroencephalography (EEG) signals, it is still unclear how different fatigue levels affect brain-behavior relationships. Methods A longitudinal study was performed to investigate the brain dynamics and behavioral changes in individuals under different fatigue levels by a sustained attention task. This study used questionnaires in combination with actigraphy, a noninvasive means of monitoring human physiological activity cycles, to conduct longitudinal assessment and tracking of the objective and subjective fatigue levels of recruited participants. In this study, degrees of effectiveness score (fatigue rating) are divided into three levels (normal, reduced, and high risk) by the SAFTE fatigue model. Results Results showed that those objective and subjective indicators were negatively correlated to behavioral performance. In addition, increased response times were accompanied by increased alpha and theta power in most brain regions, especially the posterior regions. In particular, the theta and alpha power dramatically increased in the high-fatigue (high-risk) group. Additionally, the alpha power of the occipital regions showed an inverted U-shaped change. Conclusion Our results help to explain the inconsistent findings among existing studies, which considered the effects of only acute fatigue on driving performance while ignoring different levels of resident fatigue, and potentially lead to practical and precise biomathematical models to better predict the performance of human operators. |
URI: | http://dx.doi.org/10.1002/brb3.1379 http://hdl.handle.net/11536/153096 |
ISSN: | 2162-3279 |
DOI: | 10.1002/brb3.1379 |
期刊: | BRAIN AND BEHAVIOR |
起始頁: | 0 |
結束頁: | 0 |
顯示於類別: | 期刊論文 |