Browsing by Author "Huang, Teng-Yi"

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Adaptive EEG-based alertness estimation system by using ICA-based fuzzy neural networks
(2006-11-01)
Lin, Chin-Teng
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Ko, Li-Wei
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Chung, I-Fang
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Huang, Teng-Yi
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Chen, Yu-Chieh
Drivers' fatigue has been implicated as a causal factor in many accidents. The development of human cognitive state monitoring system for the drivers to prevent accidents behind the steering wheel has become a major focus in the field of safety driving. It requires a technique that can continuously monitor and estimate the alertness level of drivers. The difficulties in developing such a system are lack of significant index for detecting drowsiness and the interference of, the complicated noise in a realistic and dynamic driving environment. An adaptive alertness estimation methodology based on electroencephalogram, power spectrum analysis, independent component analysis (ICA), and fuzzy neural network (FNNs) models is proposed in this paper or continuously monitoring driver's drowsiness level with concurrent changes in the alertness level. A novel adaptive feature selection mechanism is developed for automatically selecting effective frequency bands of ICA components for realizing an on-line alertness monitoring system based on the, correlation analysis between the time-frequency power spectra of ICA components and the driving errors defined as the deviation between the center of the vehicle and the cruising lane in the virtual-reality driving environment. The mechanism also provides effective and efficient features that can be fed into ICA-mixture-model-based self-constructing FNN to indirectly estimate driver's drowsiness level expressed by approximately and predicting the driving error.
An EEG-Based Fatigue Detection and Mitigation System
(2016-06)
Huang, Kuan-Chih
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Huang, Teng-Yi
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Chuang, Chun-Hsiang
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King, Jung-Tai
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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.
ASSESSING EFFECTIVENESS OF VARIOUS AUDITORY WARNING SIGNALS IN MAINTAINING DRIVERS' ATTENTION IN VIRTUAL REALITY-BASED DRIVING ENVIRONMENTS
(2009-06-01)
Lin, Chin-Teng
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Chiu, Tien-Ting
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Huang, Teng-Yi
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Chao, Chih-Feng
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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.
Developing an EEG-based on-line closed-loop lapse detection and mitigation system
(2014-10-13)
Wang, Yu-Te
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Huang, Kuan-Chih
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Wei, Chun-Shu
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Huang, Teng-Yi
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Ke, Li-Wei
In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects\' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.
Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning
(2008-05-01)
Lin, Chin-Teng
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Chen, Yu-Chieh
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Huang, Teng-Yi
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Chiu, Tien-Ting
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Ko, Li-Wei
Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.
Driving style classification by analyzing EEG responses to unexpected obstacle dodging tasks
(2006)
Lin, Chin-Teng
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Liang, Sheng-Fu
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Chao, Wen-Hung
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Ko, Li-Wei
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Chao, Chih-Feng
Driving safely has received increasing attention of the publics due to the growing number of traffic accidents that the driver's driving style is highly correlated to many accidents. The purpose of this study is to investigate the relationship between driver's driving style and driver's ERP response. In our research, a virtual reality (VR) driving environment is developed to provide stimuli to subjects. Independent component analysis (ICA) is used to decompose the electroencephalogram (EEG) data. The power spectrum analysis of ICA components and correlation analysis are employed to investigate the EEG activities related to driving style. Experimental results demonstrate that we may classify the drivers into aggressive or gentle styles based on the observed ERP difference corresponding to the proposed unexpected obstacle dodging tasks.
Gender differences in wayfinding in virtual environments with global or local landmarks
(2012-06-01)
Lin, Chin-Teng
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Huang, Teng-Yi
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Lin, Wen-Jing
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Chang, Shu-Yen
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Lin, Yin-Hung
This study assesses gender differences in wayfinding in environments with global or local landmarks by analyzing both overall and fine-grained measures of performance. Both female and male participants were required to locate targets in grid-like virtual environments with local or global landmarks. Interestingly, the results of the two overall measures did not converge: although females spent more time than males in locating targets, both genders were generally equivalent in terms of corrected travel path. Fine-grained measures account for different aspects of wayfinding behavior and provide additional information that explains the divergence in overall measures; females spent less time traveling away from the target location, a higher proportion of time not traversing, and made more rotations when stopping than males did. Rather than unequivocally supporting male superiority in wayfinding tasks, both the overall and fine-grained measures partially indicate that males and females are differentially superior when using global and local landmark information, respectively. To summarize, males moved faster than females but did not necessarily navigate the spatial surroundings more efficiently. Each gender showed different strengths related to wayfinding; these differences require the application of both overall and fine-grained measures for accurate assessment. (C) 2012 Elsevier Ltd. All rights reserved.
Homologous response regulators KvgA, KvbA and KvhR regulate the synthesis of capsular polysaccharide in Klebsiella pneumoniae CG43 in a coordinated manner
(2006-09-01)
Lin, Ching-Ting
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Huang, Teng-Yi
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Liang, Wan-Chun
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Peng, Hwei-Ling
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生物科技學系
On the basis of phenotypic analysis, the Klebsiella pneumoniae CG43 derived mutants with deletions of the gene encoding respectively the response regulators KvgA, KvhA, and KvhR were classified into two groups. Group I bacteria carrying either kvgA(-) or kvhR(-) exhibited less mucoidy, lower level of capsular polysaccharide (CPS) synthesis and higher LD50 than the parental strain. No apparent change of the group II, including kvhA(-) and hvhA(-)kvhR(-) mutants, was observed. However, the mucoidy of kvhA(-)kvhR(-) mutant was found to be diminished after introducing into a kvhA(-) expressing plasmid. Via promoter-lacZ fusion analysis, kvhA deletion was found to reduce kvhR expression. A regulatory role of KvhA for the expression of kvhR was supported further by EMSA showing a specific binding of KvhA to the putative promoter of kvhR. The promoter activity measurement and EMSA also revealed that KvgA acted as an autoregulator and an activator for the expression of kvhAS and kvhR. In addition, deletion of kvgA suppressed slightly the promoter activity of the cps-orf16-17, and the expression of all three cps transcripts orf1-2, orf3-15, and orf16-17 were reduced in the kvhR(-) mutant. These suggest that the three homologous response regulators interact to control, in coordination, the bacterial cps expression.
One-Pot Strategies for the Synthesis of the Tetrasaccharide Linkage Region of Proteoglycans
(2011-03-18)
Huang, Teng-Yi
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Zulueta, Medel Manuel L.
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Hung, Shang-Cheng
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應用化學系
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Department of Applied Chemistry
A linker-attached tetrasaccharide corresponding to the linkage region of proteoglycans was synthesized via one-pot procedures from the silylated monosaccharide derivatives. Regioselective one-pot protection protocols were applied in generating the requisite monosaccharide building blocks whereas stereoselective one-pot glycosylation approaches were utilized to assemble the tetrasaccharide skeleton.