• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.14-20
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• 2015

It is important to understand psychological and physiological responses of occupants who seated in a chair in order to shape a comfortable indoor official environment. So it is needed to find out optimal seated conditions. The purpose of this study was to explore optimal condition of seat air conditioning control based on psychological or subjective responses (perceived temperature and comfort sensation) and physiological responses (heartrate variability; HRV). To do this, experimental conditions were designed by the difference of indoor temperature and seat air conditioning temperature. In the experiment 1, seven experimental conditions were designed with one control condition which was not used seat air conditioning system, and six experimental conditions which the difference of indoor temperature and seat air conditioning temperature ($-1^{\circ}C{\sim}-6^{\circ}C$). In the experiment 2, four experimental conditions were designed with one control condition and three experimental conditions ($-3^{\circ}C{\sim}-5^{\circ}C$). In addition, participants' psychological or subjective response was measured by CSV (comfort sensation vote) and PTS (perceived temperature sensitivity) as a psychological or subjective response, and heartrate variability was measured as a physiological response. As a result, in the experiment 1, it was reported that the optimal conditions of seat air conditioning control based on participants' psychological or subjective comfort were from $-3^{\circ}C$ to $-5^{\circ}C$ experimental conditions. In addition, in the experiment 2, it was reported that the optimal condition of seat air conditioning control based on participants' physiological comfort was $-4^{\circ}C$ experimental condition. These results suggested that seat air conditioning could affected to comfort sensation of occupants in an appropriate range, rather than unconditionally.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.15-22
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• 2000

The analysis of power spectrum based on linear AR model is applied widely to quantize the response of autonomic nerve noninvasively, In this paper, we estimate the power spectrum density for heartrate variability of the electrocadiogram and pulse wave for short term data(less than two minute), The time series of heart rate variability is obtained from the time interval(RRI, PPI) between the feature point of the electrocadiogram and pulse wave for normal person, The generated time series reconstructed into new time series through polynomial interpolation to apply to the AR mode. The power spectrum density for AR model is calculated by Burg algorithm, After applying AR model, the power spectrum density for heart rate variability of the electrocadiogram and the pulse wave is shown smooth spectrum power at the region of low frequence and high frequence, and that the power spectrum density of electrocadiogram and pulse wave has similar form for same subject.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.2008-2016
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• 2014

With the increased attention about health care and management of heart diseases, ubiquitous healthcare services and related devices have been actively developed recently. In this paper we developed a mobile healthcare system which consists of smartphone and patch-type ECG measuring device. This system is capable of monitoring, storing, and sending bio signals such as ECG, heart rate, heart rate variability as well as exercise management functions through heart rate zones. With monitoring bio signal continuously by mobile healthcare system and wearable device like us, people can prevent chronic disease and maintain good health. Here we report our implementation results on real platforms.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.450-457
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• 2022

The construction industry is demanding, dynamic, and complex making it difficult for workers to recognize hazards. The nature of construction tasks exposes workers to several critical risk factors, such as a high rate of exertion and fatigue. Recent studies suggest that fatigue may impact hazard recognition in the construction industry. However, most studies rely on subjective measures when assessing the relationship between physical fatigue and hazard recognition, limiting such studies' efficacy. Thus, this study examined the relationship between physical fatigue and hazard recognition using a controlled experiment. Worker fatigue levels were captured using physiological data and a subjective exertion scale. The findings confirmed that physical exertion plays a significant role in hazard recognition skills (p < 0.05). This research contributes to theory and practice by providing a process for objectively assessing the influence of physical fatigue on worker safety and providing construction professionals with some critical insight needed to improve workplace safety.