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웨어러블 디바이스의 생리 신호 기반 온열 쾌적감 예측모델 개발
이윤희(Lee, Yoonhee),전정윤(Chun, Chungyoon) 대한건축학회 2021 대한건축학회논문집 Vol.37 No.10
Thermal comfort is essential to maintain a stress-free environment in a building. This study investigated the thermal environment to develop a thermal comfort prediction model based on physiological signals and thermal comfort-related responses obtained from a wearable device. Field experiments conducted in an office during cooling and heating seasons enabled the collection of real-time thermal comfort responses and physiological signals, such as skin temperature, heart rate, and electrodermal activity of the occupant using the wearable device. We analyzed the relationships between the thermal comfort responses, physiological factors, and thermal environment to develop an accurate thermal comfort prediction model. While the skin temperature and electrodermal activity exhibited a significant relationship with the thermal state, a low heart rate was observed in a more comfortable state. Moreover, machine learning classifiers predicted the thermal comfort state achieved an accuracy of 80% in both seasons using only physiological data. Thus, the feature importance of the random forest classifier verified that physiological factors aid the prediction of thermal states significantly. The proposed prediction model can be potentially applied in heating, ventilation, and air conditioning (HVAC) control. The high performance confirmed the use of wearable devices in identifying the thermal status of building occupants.
웨어러블 디바이스를 이용한 사무실 근무자 각성 상태 예측
이윤희(Yoonhee Lee),전정윤(Chungyoon Chun) 한국생활환경학회 2021 한국생활환경학회지 Vol.28 No.5
Through physiological signals, detecting the changes of occupants’ physical and psychological aspects is possible, and wearable devices have enabled measurement in daily life. In this study, to see whether the wearable device could be used to interpret the office workers’ alert state, a field experiment was conducted. A wearable device was applied for monitoring the occupant, and productivity responses were collected inside a real office. As a result, when the productivity and alertness decreased, the room temperature was high, and the skin temperature and electrodermal activity were increased. A comparison between the group of alert and drowsy states was made, along with the prediction of alert and drowsy state of the workers using the machine learning algorithms. The results showed the insight of understanding the occupants’ alert state through wearable device measured data. Physiological factors were shown to provide sufficient accuracy when predicting the alert state of the office workers. The results of this study confirmed the possibility of using physiological signals from the wearable device to more accurately identify the alert status of office occupants.
인체생리모델에 기반한 탑승자 온열쾌적감 예측방법의 개발
윤서연(Seoyeon Yun),전정윤(Chungyoon Chun),배운룡(Yunlong Pei),염혜원(Hyewon Yeom),박준석(J. S. Park),서석원(Seokwon Seo),권춘규(Chunkyu Kwon) 한국자동차공학회 2017 한국자동차공학회 부문종합 학술대회 Vol.2017 No.5
In this study, we have developed HMC(Hyundai Motor Company) comfort model that predicts drivers’ thermal comfort in vehicle cabin. HMC comfort model is based on the subject experiment. To develop this model, two different kinds of experiments were conducted. One is in the experiment climatic chamber, and the other is in the car on the rooftop. In both experiments, drivers’ body temperatures and psychological comfort votes were measured with indoor environment. The experiments in the climatic chamber were conducted under the two identical conditions(hot and cold). The experiments on the rooftop were conducted for 8 months (except on rainy days) from July to February which is summer (7~8), autumn (10~12), and winter (1~2). The car was on top of the roof in the consideration of solar radiation. Total 195 male subjects who has normal body fat ratio (10-20%,±3%) participated in this experiment; subjects for valid data were total 187(33 for chamber experiment and 154 for rooftop experiment). Experimental clothing that the subjects wore was 0.41clo(summer), 0.57clo(autumn), 0.74clo(winter) for each season. This paper suggests the basic concept of the HMC comfort model, and its development conditions, partial results and future plans.
곽지영(Jiyoung Kwak),윤서연(Seoyeon Yun),전정윤(Chungyoon Chun),최희원(Heewon Choi),박준석(J.S. Park),서석원(Seokwon Seo),권춘규(Chunkyu Kwon) 한국자동차공학회 2019 한국자동차공학회 부문종합 학술대회 Vol.2019 No.5
With the recent development of self-driving cars, vehicles are not just a means of transportation but becomes a living space. Thus, it is important to provide a comfortable indoor environment to passengers in the vehicle. To achieve this, HMC Comfort Model ver.1, which predicts the thermal comfort of passengers, was developed in 2017. However, since this model was developed for Korean males in their 2-30s, it is difficult to apply it to females where different physiological and psychological responses are shown. Therefore, in this study, the data to develop comfort model specialized for gender were obtained and analyzed. Experiments were conducted on Korean females in their 2-30s in actual vehicles located in climate chambers with hot and cold conditions. During the experiment, skin temperature was measured and thermal comfort of subjects was evaluated. The results were compared with previous results of Korean males and necessity of specialized comfort model for women was confirmed through differences between two results.