• 한국전자통신학회논문지
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• 제8권6호
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• pp.949-954
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• 2013

본 논문에서는 인간의 졸음에 대한 특성을 관찰하기 위해 뇌파를 계측 및 분석하였다. 인간으로부터 발생되는 뇌파 즉 EEG신호를 계측하여 주파수 대역에 따라 분석하는 것을 기본적인 방법으로 한다. 흔히 각성, 폐안 및 수면에 접어들 때와 관련이 있는 뇌파는 알파파로 알려져 있다. 따라서 본 논문에서는 졸음과 관련된 분석 주파수대역을 알파파대역으로 한정하여, 알파파대역 중에서도 어떤 주파수성분이 졸음과 더 밀접한 관련이 있는지 파워 스펙트럼 분석법을 이용하여 관측한 결과를 제시하였다.

• 한국환경보건학회지
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• 제32권5호
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• pp.412-417
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• 2006

A self-administrated non-malignant respiratory symptoms questionnaire was sent to 1,099 citizens who take subway running in Seoul city. Symptom prevalence rate was high: 70.6% of subjects reported 'chest tightness', 43.4%, 'dysphnea'; 76.2%, 'dry cough'; 49.5%, 'runny nose'; 94.4%, 'drowsiness' when they take subway. The groups responding significant higher respiratory and drowsiness symptoms were 'young passengers' (vs elderly passengers), 'the female' (vs male), 'using subway everyday' (vs often), 'using subway for rush-hour time' (vs other than rush-hour), 'using transfer subway' (no transfer), 'using underground track' (vs ground track). Logistic. regression model was employed to find personal and subway characteristics affecting non-malignant respiratory symptoms. This study concluded that respiratory diseases history such as asthma, rhinitis, sinusitis, hypersensitivity pneumonitis significantly affect 'dry cough' and 'runny nose'. Thus, passengers with respiratory diseases history shows 2.8 times greater 'dry cough' than and 3.4 times greater 'runny nose' than those passengers without respiratory diseases history felt. This results indicated that several measures have to take to protect sensitive groups such as passengers with respiratory diseases, children and elderly people. Also passenger who use to transfer shows 1.7 times higher runny nose symptoms than that passenger who do not transfer felt.

• 설비공학논문집
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• 제29권3호
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• pp.134-141
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• 2017

The purpose of this study was to analyze physiological changes via a cold air reaction experiment to generate basic data that are useful for the development of an automobile active air conditioning system to prevent drowsiness. The $CO_2$ concentration causing drowsiness in vehicle operation was kept below a certain level. Air was blown to the driver's face by using an indoor air cooling apparatus. Sleepiness and the arousal state of the driver in cold wind were measured by physiological signals. It was evident in the EEG that alpha waves decreased and beta waves increased, caused by cold air stimulation. The ${\alpha}/{\beta}$ ratio was reduced by about 52.9% and an alert state confirmed. In the electrocardiogram analysis, the efficiency of cold air stimulation was confirmed by the mean heart rate interval change. The R-R interval had a delay time of about one minute compared to the EEG response. The findings confirmed an arousal effect from sleepiness due to cold air stimulation.

• International Journal of Internet, Broadcasting and Communication
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• 제15권4호
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• pp.142-148
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• 2023

In Modern days, Self-driving for modern people is an absolute necessity for transportation and many other reasons. Additionally, after the outbreak of COVID-19, driving by oneself is preferred over other means of transportation for the prevention of infection. However, due to the constant exposure to stressful situations and chronic fatigue one experiences from the work or the traffic to and from it, modern drivers often drive under drowsiness which can lead to serious accidents and fatality. To address this problem, we propose a drowsy driving prevention learning model which detects a driver's state of drowsiness. Furthermore, a method to sound a warning message after drowsiness detection is also presented. This is to use MoveNet to quickly and accurately extract the keypoints of the body of the driver and Dense Neural Network(DNN) to train on real-time driving behaviors, which then immediately warns if an abnormal drowsy posture is detected. With this method, we expect reduction in traffic accident and enhancement in overall traffic safety.

• 생물정신의학
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• 제6권2호
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• pp.246-252
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• 1999

Objectives : Daytime drowsiness or sedation and changes in night sleep are commonly seen in patients treated with clozapine. There is, however, very limited information on their degree and nature during the course of treatment. The purpose of this study was to understand the sleep patterns in chronic schizophrenic patients with clozapine treatment over a period of 24 weeks. Method : The sleep pattern was evaluated using a set of 5-point scale questionnaire, to record subjective impressions of the night sleep induction, maintenance and quality, and daytime drowsiness and fatigue. In addition, unusual experiences associated with night sleep were recorded. The sleep questionnaire was repeatedly administered at baseline and at 1, 2, 4, 8, 12 and 24 weeks of drug treatment. At present, data on 12 patients has been collected. Results : All the components of night sleep were significantly improved in the 1st through the 12th week after treatment with clozapine. Daytime drowsiness was significantly higher in the 1st to the 2nd week after the treatment and fatigue was also significantly higher in the 1st to the 4th week after the treatment. Eight patients experienced noticeable increases in salivation during night sleep, and of these, one also reported frequent nocturnal urination and even enuresis. However, all these adverse factors did not affect the major sleep patterns. Conclusions : These findings suggest that the beneficial effects of clozapine on night sleep might last much longer than the undesirable effect of daytime drowsiness and fatigue. In other words, tolerance of the hypnotic action of clozapine might develop late and tolerance of the daytime drowsiness and fatigue might be evident earlier.

• 전기학회논문지
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• 제63권12호
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• pp.1667-1670
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• 2014

This paper describes a method for detecting the pupil region and identification of the eye status for driver drowsiness detection system. This program detects a driver's face and eyes using viola-jones face detection algorithm and extracts the pupil area by utilizing mean values of each row and column on the eye area. The proposed method uses binary images and the number of black pixels to identify the eye status. Experimental results showed that the accuracy of classification eye status(open/close) was above 90%.

• 센서학회지
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• 제23권2호
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• pp.142-147
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• 2014

Real time driver's respiration monitoring method for detecting driver's drowsiness is investigated. The sensor to obtain driver's respiration signal was a piezoelectric pressure sensor attached at the abdominal region of the seat belt. The resistance of the pressure sensor was changed according to the pressure applied to the seat belt due to the driver's respiration. Monitoring driver's respiration was carried out by driving on the virtual road in a driving simulator from Cheonan to Seoul and monitoring results were compared to the PELCLOS. Experiment results show that the driver's respiration signal can be used for detecting driver's drowsiness.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 춘계학술대회
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• pp.56-59
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• 1996

The purpose of this study is to identify the cause of driver's drowsiness and to get information about driver's drowsiness from facial image using computer vision. We measured the driver's movements of a head and shoulders in the highway arid street. We also measured the eye blink duration and yawning duration of normal and drowsy drivers. from the results, we confirmed that the measurement of eye blink and yawning might be a way of drowsy detection.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.153-154
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• 2019

실제로 잠을 자는 것이 허용되지 않는 많은 일자리가 있습니다. 졸음운전은 현대 사회에서 가장 큰 문제 중 하나입니다. 이 논문에서는 깊은 학습 (YOLO)을 사용하여 눈을 검사하고 졸음을 확인한 다음 수중 총을 제어하는 시스템을 제안한다.

• 한국산학기술학회논문지
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• 제15권4호
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• pp.2265-2275
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• 2014

본 연구는 S특별시와 K도에 소재한 3개의 치과의원에서 교정치료를 받고 있는 환자 181명을 대상으로 스트레스에 따른 수면의 질의 관련요인 파악하고자 수행된 조사연구이다. 자료로는 일반적 특성을 포함한 스트레스와 주간 졸음의 양, 수면의 질을 측정할 수 있는 구조적 도구를 사용하여 SPSS WIN 18.0 program을 이용하여 분석하였다. 본 연구의 결과, 대상자가 인식하는 스트레스의 정도는 평균 $40.51{\pm}20.43$점, 주간 졸음의 양은 $11.06{\pm}5.42$점, 수면의 질은 $13.24{\pm}9.72$점으로 측정되었으며, 교정 치료 환자의 스트레스와 주간 졸음의 양. 수면의 질 모두에서 통계적으로 유의한 상관관계가 있음을 확인하였다.