• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.544-553
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• 2023

The purpose of this study was to reveal the thermal comfort and physiological and psychological effects of spending time in broad-leaved forests in suumer. Thirty-one university students (with an average age of 21.4 ± 2.1 years) participated in the study, and a within-subjects experimental design methodology was used. The participants moved to an experimental site (with a crown closure of 76.6%) or a control site (25.9%), sat on a chair to eliminate the impact of movement, and rested for 5 minutes with closed eyes. At this time, thermal comfort, heart rate variability, heart rate, and forehead temperature were continuously measured. After that, blood pressure and pulse rate were measured, and a subjective evaluation was conducted. As a result, spending time at an experimental site showed a statistically significant decrease in the predicted mean vote and the percentage of dissatisfied values, enhancement of parasympathetic nerve activity, decrease of forehead temperature, diastolic blood pressure, heart rate, pulse rate, and improvement of personal thermal sensation (thermal sensation vote and comfort sensation vote). In conclusion, it was found that a forest with high crown closure reduces thermal stress and induces physiological and psychological relaxation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1303-1310
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• 2010

Recently, researches related with automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for SpO2 sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, SpO2 and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the SpO2 and ECG signals. HRV (Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.1
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• pp.76-85
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• 2010

In general, anesthetic depth is evaluated by experience of anesthesiologist based on the changes of blood pressure and pulse rate. So it is difficult to guarantee the accuracy in evaluation of anesthetic depth. The efforts to develop the objective index for evaluation of anesthetic depth were continued but there was few progression in this area. Heart rate variability provides much information of autonomic activity of cardiovascular system and almost all anesthetics depress the autonomic activity. Novel monitoring system which can simply and exactly analyze the autonomic activity of cardiovascular system will provide important information for evaluation of anesthetic depth. We investigated the anesthetic depth as following 7 stages. These are pre-anesthesia, induction, skin incision, before extubation, after extubation, Post-anesthesia. In this study, temporal, frequency and chaos analysis method were used to analyze the HRV time series from electrocardiogram signal. There were NN10-NN50, mean, SDNN and RMS parameter in the temporal method. In the frequency method, there are LF and HF and LF/HF ratio, 1/f noise, alphal and alpha2 of DFA analysis parameter. In the chaos analysis, there are CD, entropy and LPE. Chaos analysis method was valuable to estimate the anesthetic depth compared with temporal and frequency method. Because human body was involved the choastic character.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.545-548
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• 2009

Recently, researches related to automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for $SpO_2$ sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, $SpO_2$ and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the $SpO_2$ and ECG signals. HRV(Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• Journal of Naturopathy
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• v.11 no.2
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• pp.116-122
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• 2022

Background: Studies on the effect of abdominal or thoracic breathing therapy on sleep or blood oxygen concentration are still scarce. Purpose: This study was to examine the effect on blood oxygen saturation and pulse variability, changes in the severity of insomnia, changes in wakefulness before sleep, and dysfunctional beliefs and attitudes toward the Korean version of sleep in women in their 50s after healing with abdominal breathing and thoracic breathing. We investigated the effect. Methods: Subjects were investigated before and after the change of breathing (breathing) therapy for 12 weeks, 3 times a week, and 36 breaths perweek. Results: It wa evaluated respiratory healing as having no significance in the pulse rate change. However, oxygen saturation was significant in the experimental group, increasing to 93.60 SpO₂% before the respiratory rally and 96.5 SpO₂% after respiratory recovery (p < .002). In addition, the insomnia severity scale and dysfunctional beliefs about sleep significantly decreased after respiratory rally than before (p < .000). Conclusions: It evaluated that respiratory therapy for the subjects is beneficial to health as it is effective for insomnia, pulse, and oxygen saturation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.493-498
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• 2016

Heart Rate Variability (HRV) represents beat-to-beat fluctuations of R-R intervals in Electrocardiogram (ECG). On of the clinical applications of HRV is to assess the mental-stress state by evaluating its power spectral density distribution. This study aims at finding new discriminative role of the coupled-oscillating coupling constants, Cs and Cp in the Integral Pulse Frequency Modulation (IPFM) model. Based on comparing with power spectral density of HRV in terms of the relative ratio of the low and high-frequency power component, we can conclude the fact that the coupling parameters Cs and Cp can replace the role of HRV power spectrum interpretation for judging the mental-stress state.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3233-3235
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• 2000

A new method for HRV(heart rate variability} detection from the R-wave signal, based on the IPFM (integral pulse frequency modulation) model and its similarity to pulse position modulation, is presented. The proposed method exert lowpass filtering with a Kaiser window. In this paper, The proposed method presents a powerful, but simple, tool for investigation of HRV. It also guarantees real-time behavior, simplicity in design, and phase linearity. Even without the basic assumption of IPFM model, the new algorithm can still be used on-line and with higher performance. It is thoroughly proved that lowpass filtering is an ideal method for PSD (Power Spectrum Density) analysis of HRV.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.619-625
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• 2007

As low power, low cost wireless communication technology like Bluetooth, Zigbee, RFID has been put to practical use together with the wellbeing trend, the concern about ubiquitous health care has been greatly increased and u-Health is becoming one of the most important application in the sensor network field. Especially, development of the medical services to be able to cope with a state of emergency for solitary senior citizens and the aged in silver town is very meaningful itself and their needs are also expected to continuously increase with a rapid increase in an aging population. In this paper we demonstrate the feasibility of extracting accurate heart rate variability (HRV) measurements from photoelectric plethysmography(PPG) signals gathered by a ring type pulse oximeter sensor attached to the finger. For this, we made 2 types of ring sensor, that is reflective and pervious type, and developed the remote monitoring system which is able to collect HR data from ring sensor, analyze and cope with a state of emergency.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.711-723
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• 2008

In this study, Hydrologic regime alterations(magnitude, magnitude and duration of annual extreme, frequency and duration of high and low pulse, rate and frequency of water condition changes, Range of Variability Approach) were analyzed by using Indicators of Hydrologic Alterations at the 11 major multi-purpose dam. The analysis result of the magnitude of monthly water conditions during drought season, inflow was $6.38m^3/sec{\sim}39.84m^3/sec$ and outflow was $20.36m^3/sec{\sim}49.43m^3/sec$, was increased $1.84%{\sim}200.98%$. The analysis result of the magnitude of monthly water conditions during flood season, inflow was from $79.06m^3/sec{\sim}137.12m^3/sec$ and outflow was from $65.32m^3/sec{\sim}80.16m^3/sec$, was decreased from $18.19%{\sim}40.39%$. The analysis result of the magnitude and duration of annual extreme, 1-day minimum was increased $82.86%{\sim}2,950%$, but 1-day maximum was decreased $34.78%{\sim}83.96%$. The analysis result of the frequency and duration of high and low pulse, low pulse count was decreased $29.67%{\sim}99.07%$ and high pulse count was also decreased $4.6%{\sim}92.35%$ after dam operation. Hydrograph rise rate was decreased $15.84%{\sim}79.31%$ and fall rate was $1.97%{\sim}107.10%$. RVA of 1-day minimum was increased $0.60{\sim}2.67$, also RVA of 1-day maximum was decreased $0.50{\sim}1.00$.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.289-292
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• 2000

선형 자귀회귀(AR) 모델을 근거로한 HRV 파워 스펙트럼해석은 비침습적으로 자율신경의 반응을 정량화하는데 폭넓게 사용된다. 본 연구는 단구간(2분 미만)의 심전도와 맥파 신호로부터 시계열 HRV의 파워스펙트럼을 추정한다. 시계열은 정상인을 대상으로 검출한 심전도와 맥파신호의 특징점 시간간격(RRI, PPI)으로부터 구하였다. 발생된 시계열은 다항식 보간법에 의해 AR모델에 적합하게 재구성하였으며, AR모델 계수는 Burg법에 의해 계산하였다. AR모델을 적용한 단구간의 심전도와 맥파의 심박변동에 대한 파워스펙트럼밀도는 저주파수(LF)와 고주파수(HF)에서 매끄러운 스펙트럼 파워를 나타내고 있다. 또한 동일한 피험자의 심전도와 맥파의 파워스펙트럼밀도를 비교한 결과 동일한 모양을 나타내었다.