Multi-Parameter Physiological State Monitoring in Target Detection Under Real-World Settings

Yang Chang, Congying He, Bo Yu Tsai, Li-Wei Ko*

*此作品的通信作者

研究成果: Article同行評審

3 引文 斯高帕斯(Scopus)

摘要

Mental state changes induced by stimuli under experimental settings or by daily events in real life affect task performance and are entwined with physical and mental health. In this study, we developed a physiological state indicator with five parameters that reflect the subject’s real-time physiological states based on online EEG signal processing. These five parameters are attention, fatigue, stress, and the brain activity shifts of the left and right hemispheres. We designed a target detection experiment modified by a cognitive attention network test for validating the effectiveness of the proposed indicator, as such conditions would better approximate a real chaotic environment. Results demonstrated that attention levels while performing the target detection task were significantly higher than during rest periods, but also exhibited a decay over time. In contrast, the fatigue level increased gradually and plateaued by the third rest period. Similar to attention levels, the stress level decreased as the experiment proceeded. These parameters are therefore shown to be highly correlated to different stages of the experiment, suggesting their usage as primary factors in passive brain-computer interfaces (BCI). In addition, the left and right brain activity indexes reveal the EEG neural modulations of the corresponding hemispheres, which set a feasible reference of activation for an active BCI control system, such as one executing motor imagery tasks. The proposed indicator is applicable to potential passive and active BCI applications for monitoring the subject’s physiological state change in real-time, along with providing a means of evaluating the associated signal quality to enhance the BCI performance.

原文English
文章編號785562
頁(從 - 到)1-13
頁數13
期刊Frontiers in Human Neuroscience
15
DOIs
出版狀態Published - 22 12月 2021

指紋

深入研究「Multi-Parameter Physiological State Monitoring in Target Detection Under Real-World Settings」主題。共同形成了獨特的指紋。

引用此