Browsing by Author "Cheng, Chung-Kuan"

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An Interdigitated Non-Contact ECG Electrode for Impedance Compensation and Signal Restoration
(2015-01-01)
Lin, Jeng-Hau
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Liu, Hao
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Liu, Chia-Hung
;
Lam, Phillip
;
Pan, Gung-Yu
This paper presents a non-contact electrocardiogram (ECG) measurement platform that compensates for motion-induced impedance changes via interdigitated electrode channels in concert with software reconstruction algorithms. Specifically, the impedance of the non-contact electrode is non-invasively acquired in real-time by exploiting a custom electrode designed with two independent channels featuring independent transfer functions that are used to reconstruct motion-compensated ECG waveforms. The developed platform is validated on human subjects, illustrating up to a 76.3% improvement over conventional approaches, paving the path towards comfortable, convenient, and robust non-contact electrophysiological sensing.
Cell-phone Based Drowsiness Monitoring and Management System
(2012)
Wang, Yu-Te
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Cheng, Chung-Kuan
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Huang, Kuan-Chih
;
Lin, Chin-Teng
;
Wang, Yijun
In recent years, driving fatigue and cognitive lapses have gained increasing attentions in the fields of public security, especially regarding the safe manipulation of vehicles. Studies have explored the relation between electroencephalogram (EEG) and driving behavior and several of them further proposed effective approaches (e. g., auditory feedback) to arouse subjects from drowsiness. However, these studies were performed under laboratory-oriented configurations using tethered, ponderous EEG equipment. In real environments, the setup of bulky cognitive monitoring equipment with a long-prep time is not feasible. Therefore, this study extends previous laboratory work by developing an on-line Drowsiness Monitoring and Management (DMM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. The DMM system can continuously observe EEG dynamics, deliver arousing feedback to users experiencing momentary cognitive lapses, and assess the efficacy of the feedback in near real-time.
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
;
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.