<link rel="stylesheet" href="styles.cf390c6bfbe7555f.css">

學術出版;;Publications

Permanent URI for this communityhdl:11536/1

收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

Browse

🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Huang, Teng-YiHas files: No

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item type:Item,
    An EEG-Based Fatigue Detection and Mitigation System
    (2016-06)
    Huang, Kuan-Chih
    ;
    Huang, Teng-Yi
    ;
    Chuang, Chun-Hsiang
    ;
    King, Jung-Tai
    ;
    Wang, Yu-Kai
    Research has indicated that fatigue is a critical factor in cognitive lapses because it negatively affects an individual\'s internal state, which is then manifested physiologically. This study explores neurophysiological changes, measured by electroencephalogram (EEG), due to fatigue. This study further demonstrates the feasibility of an online closed-loop EEG-based fatigue detection and mitigation system that detects physiological change and can thereby prevent fatigue-related cognitive lapses. More importantly, this work compares the efficacy of fatigue detection and mitigation between the EEG-based and a nonEEG-based random method. Twelve healthy subjects participated in a sustained-attention driving experiment. Each participant\'s EEG signal was monitored continuously and a warning was delivered in real-time to participants once the EEG signature of fatigue was detected. Study results indicate suppression of the alpha-and theta-power of an occipital component and improved behavioral performance following a warning signal; these findings are in line with those in previous studies. However, study results also showed reduced warning efficacy (i.e. increased response times (RTs) to lane deviations) accompanied by increased alpha-power due to the fluctuation of warnings over time. Furthermore, a comparison of EEG-based and nonEEG-based random approaches clearly demonstrated the necessity of adaptive fatigue-mitigation systems, based on a subject\'s cognitive level, to deliver warnings. Analytical results clearly demonstrate and validate the efficacy of this online closed-loop EEG-based fatigue detection and mitigation mechanism to identify cognitive lapses that may lead to catastrophic incidents in countless operational environments.
  • Thumbnail Image
    Item type:Item,
    ASSESSING EFFECTIVENESS OF VARIOUS AUDITORY WARNING SIGNALS IN MAINTAINING DRIVERS' ATTENTION IN VIRTUAL REALITY-BASED DRIVING ENVIRONMENTS
    (2009-06-01)
    Lin, Chin-Teng
    ;
    Chiu, Tien-Ting
    ;
    Huang, Teng-Yi
    ;
    Chao, Chih-Feng
    ;
    Liang, Wen-Chieh
    Drivers' fatigue contributes to traffic accidents, so drivers must maintain adequate alertness. The effectiveness of audio alarms in maintaining driving performance and characteristics of alarms was studied in a virtural reality-based driving environment. Response time to the car's drifting was measured under seven conditions: with no warnings and with continuous warning tones (500 Hz, 1750 Hz, and 3000 Hz), and with tone bursts at 500 Hz, 1750 Hz, and 3000 Hz. Analyses showed the audio warning signals significantly improved driving. Further, the tones' spectral characteristics significantly influenced the effectiveness of the warning.