Browsing by Author "Chang, Che-Jui"

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A Real-Time Wireless Brain-Computer Interface System for Drowsiness Detection
(2010-08-01)
Lin, Chin-Teng
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Chang, Che-Jui
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Lin, Bor-Shyh
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Hung, Shao-Hang
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Chao, Chih-Feng
A real-time wireless electroencephalogram (EEG)-based brain-computer interface (BCI) system for drowsiness detection has been proposed. Drowsy driving has been implicated as a causal factor in many accidents. Therefore, real-time drowsiness monitoring can prevent traffic accidents effectively. However, current BCI systems are usually large and have to transmit an EEG signal to a back-end personal computer to process the EEG signal. In this study, a novel BCI system was developed to monitor the human cognitive state and provide biofeedback to the driver when drowsy state occurs. The proposed system consists of a wireless physiological signal-acquisition module and an embedded signal-processing module. Here, the physiological signal-acquisition module and embedded signal-processing module were designed for long-term EEG monitoring and real-time drowsiness detection, respectively. The advantages of low ower consumption and small volume of the proposed system are suitable for car applications. Moreover, a real-time drowsiness detection algorithm was also developed and implemented in this system. The experiment results demonstrated the feasibility of our proposed BCI system in a practical driving application.
Brain Computer Interface-Based Smart Living Environmental Auto-Adjustment Control System in UPnP Home Networking
(2014-06-01)
Lin, Chin-Teng
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Lin, Bor-Shyh
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Lin, Fu-Chang
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Chang, Che-Jui
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影像與生醫光電研究所
A brain computer interface-based smart living environmental auto-adjustment control system (BSLEACS) is proposed in this paper. Recently, many environmental control systems have been proposed to improve human quality of life. However, little research has focused on environmental control directly using the human physiological state. Based on the advantage of our technique on brain computer interface (BCI), we integrated the BCI technique with universal plug and play (UPnP) home networking for smart house applications. BSLEACS mainly consists of a wireless physiological signal acquisition module, an embedded signal processing module, a simple control protocol/power line communication environmental controller, and a host system. Here, the physiological signal acquisition module and embedded signal processing module were designed for long-term electroencephalogram (EEG) monitoring and backend analysis, respectively. The advantages of low power consumption and small volume of the above modules are suitable for smart house applications in daily life. Moreover, different from other BCI systems, the property of using only a single EEG channel to monitor cognitive state also makes BSLEACS become more practicable. BSLEACS has been verified in a practical demo room, and the environmental adjustment can be automatically controlled by the change of the user\'s cognitive state. BSLEACS provides a novel system prototype for environmental control, and can be simply extended and integrated with the UPnP home networking for other applications.
Development of Real-time Wireless Brain Computer Interface for Drowsiness Detection
(2010)
Hung, Shao-Hang
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Chang, Che-Jui
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Chao, Chih-Feng
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Wang, I-Jan
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Lin, Chin-Teng
In this study, a real-time wireless embedded EEG-based brain computer interface (BCI) system was developed for drowsiness detection in a realistic driving task. Accidents caused by driver's drowsiness behind the steering wheel have a high fatality rate because of the marked decline in the driver's abilities of perception, recognition, and vehicle control abilities while sleepy. Therefore, real-time drowsiness monitoring is important to avoid traffic accidents. In this study, an embedded EEG-based BCI system which includes a wireless physiological signal acquisition module and an embedded signal processing module was designed, and a real-time drowsiness detection algorithm based on our unsupervised approach was implemented in the embedded signal processing module. EEG signal would be monitored and analyzed by the embedded signal processing module, and the warning tone would be triggered to prevent traffic accidents when the drowsiness condition occurred.
Human Cognitive Application by Using Wearable Mobile Brain Computer Interface
(2010)
Liao, Lun-De
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Wang, I-Jan
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Chang, Che-Jui
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Lin, Bor-Shyh
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Lin, Chin-Teng
In this study, we demonstrated a Wearable Mobile Electroencephalogram (EEG)-based Brain Computer Interface System (WMEBCIS) with foam-based dry electrodes embedded. According to the previous studies, many kinds of BCI systems have been proposed and target the applications on sensors and information techniques. For daily life EEG monitoring by using the BCI systems, the sensors have employ a key technique for ensuring the data quality. In view of this, a novel dry foam electrode was designed and applied for the wearable EEG acquisition device in our WMEBCIS. The developed dry electrodes can achieve the quick-placement and high signals quality under no skin preparation and without gels applied. Most importantly, due to its softness advantage, the developed electrodes can fit properly on the skin surface to maintain low skin-electrode impedance and reduce motion artifacts under movement. By using the specific mechanism of our wearable EEG acquisition device, it can be worn conveniently and can maintain the electrode-scalp contact area to acquire good EEG signal quality effectively. Therefore, the wearable EEG acquisition device is suitable for long-term EEG monitoring in daily life. In words, our WMEBCIS was also demonstrated for a cognitive application on drowsiness detection.
Use of Ultrafast Time-Resolved Spectroscopy to Demonstrate the Effect of Annealing on the Performance of P3HT:PCBM Solar Cells
(2015-03-04)
Wang, Yu-Ting
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Chen, Mei-Hsin
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Lin, Chao-Ting
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Fang, Jian-Jhih
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Chang, Che-Jui
The organic solar cells of heterojunction system, ITO/PEDOT:PSS/P3HT:PCBM/Al, with a thermal annealing after deposition of Al exhibit better performance than those with an annealing process before deposition of Al. In this study, ultrafast time-resolved spectroscopy is employed to reveal the underlying mechanism of annealing effects on the performance of P3HT:PCBM solar cell devices. The analyses of all decomposed relaxation processes show that the postannealed devices exhibit an increase in charge transfer, in the number of separated polarons and a reduction in the amount of recombination between excited carriers. Moreover, the longer lifetime for the excited carriers in postannealed devices indicates it is more likely to be dissociated into photocarriers and result in a larger value for photocurrent, which demonstrates the physical mechanism for increased device performance.
Wearable and Wireless Brain-Computer Interface and Its Applications
(2009)
Lin, Chin-Teng
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Ko, Li-Wei
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Chang, Che-Jui
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Wang, Yu-Te
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Chung, Chia-Hsin
This study extends our previous work on mobile & wireless EEG acquisition to a truly wearable and wireless human-machine interface, NCTU Brain-Computer-Interface-headband,(BCI-headband), featuring: (1) dry Micro-Electro-Mechanical System (MEMS) EEG electrodes with 400 ganged contacts for acquiring signals from non-hairy sites without use Of gel or skin preparation; (2) a miniature data acquisition circuitry, (3) wireless telemetry and (4) online signal processing on a commercially available cell phone or a lightweight, wearable digital signal processing module. The applicability of the NCTU BCI headband to EEG monitoring in real-world environments was demonstrated in a sample study: cognitive-state monitoring and management of participants performing normal tasks.