• 전기학회논문지
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• 제59권6호
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• pp.1131-1135
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• 2010

The development of modern civilization result from the abundance of material. Yet modern people live with chronic mild stress. Excessive chronic mild stress leads to various diseases. From the risk of the disease in order to protect our bodies need to manage chronic mild stress. The purpose of this study is to inspection the effectiveness of detecting in chronic mild stress using the Multi-sensor system. The Multi-sensor system is designed that can be measure three kinds of vital signals of chronic mild stress for the detection. First Photoplethysmogram(PPG), second Electro Dermal Activity(EDA), third Skin Temperature(SKT). The ages and occupations exposed to chronic mild stress, people often use out of this system was applied to dairy products(Pen). In addition, vital signals that occur when the variety of noise was used to remove the accelerometer. Chronic mild stress by the analysis of measured vital signals from Multi-sensor system to the measurement information to a PC to a wireless transmission(Bluetooth). In this study, using Multi-sensor system writing conditions and a variety of situations in the movement to measure vital signals and measurement results verified the accuracy and reliability. Through this measure chronic mild stress in everyday life and managing to maintain will help more healthy lifestyle.

• 대한의용생체공학회:의공학회지
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• 제28권2호
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• pp.280-286
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• 2007

The wearable sensor glove was developed using EDA sensors and conducting fabric. EDA(Electro-dermal Activity) signal is an electric response of human skin. There are SIL(Skin Impedance Level) and SIR(Skin Impedance Response) in EDA. SIL consists mostly of a DC component while SIR consists of an AC component. The relationship between drowsiness and the EDA signal is utilized. EDA sensors were made using a conducting fabric instead of AgCl electrodes, for a more suitable, more wearable device. The EDA signal acquisition module was made by connecting the EDA sensor gloves through conductive fabric lines. Also, the EDA signal acquisition module can be connected to a PC that shows the results of the EDA signal processing analysis and gives proper feedback to the user. This system can be used in various applications to detect drowsiness and prevent accidents from drowsiness for automobile drivers.

• 전기학회논문지
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• 제56권2호
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• pp.432-435
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• 2007

In modern society, automobile is necessary vehicle. Automobile is a series of modern convenient. And the number of automobile is on the increase. But from you to year, automobile accident is on the increase, also. One of most reason that cause automobile accident is drowsiness driving. So, we plan to construct automobile system for drowsiness accident prevention for decreasing automobile accident. In this research, we built a drowsiness detecting device using EDA (Electro Dermal Activity) signal which is electric response in the human body skin. There are SIL (Skin Impedance Level) and SIR (Skin Impedance Response) in EDA. Mostly, SIL consists of DC element. On the other hand, SIL consists of AC element. We could detect the drowsiness condition with SIL and SIR signal.

• 전기학회논문지
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• 제61권6호
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• pp.891-898
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• 2012

The study for the passenger's comfortableness of vehicles and the arousal of car drivers has been done widely. On the other hand, there are few studies for the locomotive engineers. Human error means that the mistakes made by human, recently it receives attention in the field of safety engineering and human engineering. Comparing the operating condition of train with car, because of the simplification of the visual stimulus, the arousal level on the train goes down easily. The arousal level down makes judgement down, the accident risk from human error is getting bigger. In this study, we measured bio-signals(ECG, EDA, PPG, respiration and EEG) from 6 locomotive engineers to evaluate their arousal state while they operated the train. Also we recorded the 3 axes acceleration signal showing the vibration state of train. Also, the existence of tunnels were simultaneously measured. At the station section where the train speed goes down, the size of vector's sum decreases because of reduced vibration. Beta component in EEG tends to increase at the entering point of each station and tunnel. It is due to the arousal reaction and tension growth. The mean SCR(skin conductance response) was more increased in neutral section. As the button control movement (body movement) increases in the neutral section, it is appeared that SCR increase. RR interval tends to gradually increase during train operation for 1 hour 40 minutes. However, It tends to sharply decrease at the stop station because strong concentration needed to stop train on the exact point. The engineer's arousal reaction can be checked through analysing the bio-signal change during train operation. Therefore, if this analysing result is adopted to the sleepiness prevention caution system, it will be useful for the safety train operation.