• 대한한의진단학회지
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• 제10권2호
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• pp.104-120
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• 2006

Background : Pulse-respiration ratio has been used for estimating subject's status in oriental medicine. Pulse and respiration is strongly associated with autonomic nerve system. But there is no research about correlation between pulse-respiration ratio and autonomic nerve system. Objectives : We performed this study to know correlation between pulse-respiration ratio and HRV(heart rate variability) that shows autonomic nerve system status well and to clarify clinical meaning of pulse-respiration ratio. Methods : After subject's 10 minutes rest, we measured subject's ECG, respiration pattern and HRV. In this research, subject's number is 95(Male 50/Female 45). We calculated pulse-respiration ratio from ECG and respiration pattern. Then, we analyzed correlation between pulse-respiration ratio and HRV parameters in all subjects, 2 group divided by Wan-Maek(P-R ratio 4.28). We tried to compare HRV parameters among Wan-Maek, Sak-Maek and Ji-Maek group. Correlation analysis between pulse-respiration Ratio and Pulse rate, respiration rate is performed. Finally correlation analysis between Respiration and HRV parameters in all subjects, 2 group divided by Wan-Maek(4.28) is studied. Results : 1. Mean pulse-respiration is 4.10${\pm}$0.67, Mean pulse rate is 68.06${\pm}$7.82bpm, Mean respiration rate is 16.81${\pm}$2.72 times per minute in all subjects. 2. Correlation analysis between pulse-respiration ratio and HRV parameters of high pulse-respiration ratio group is not significant. But, in low pulse-respiration ratio group, HFnorm(correlation coefficient 0.306, p= 0.018), lnHF (0.308, p=0.002) is significantly correlated with pulse-respiration ratio. 3. Comparison of HRV parameters among Wan-Maek, Sak-Maek and Ji-Maek Group is not significant. 4. Pulse-respiration ratio is more affected by respiration rate(correlation coefficient-0.17, p=0.000) than pulse rate (correlation coefficient 0.396, p=0.000). 5. Correlation analysis between respiration rate and HRV parameters of high pulse-respiration ratio group is not significant. But, in low pulse-respiration ratio group, HFnorm (correlation coefficient -0.327, p=0.011), LF/HF(0.346, p=0.007), lnHF (-0.355, p=0.006) are significantly correlated with respiration rate. Conclusion : Pulse-respiration ratio and parasympathetic index has positive correlation. The closer Wan-Maek, The higher parasympathetic index in low pulse-respiration ratio group. Respiration rate is more related with pulse-respiration ratio than pulse rate. Respiration is negatively correlated with autonomic parameters. And the slower respiration, the higher parasympathetic index in low pulse-respiration ratio group.

• 생물환경조절학회지
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• 제9권4호
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• pp.185-192
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• 2000

본연구는 시설내 다양한 환경조건하에서 오이의 호흡속도에 관한 수리적 모형을 개발하고자 실시하였다. 개개 오이 식물에 대한 총광합성속도의 8.55%가 호흡에 사용되었다. 생장호흡계수는 0.0935로 추정되었고 유지호흡속도는 24$^{\circ}C$ 온도에서 0.00158g C$H_2O$.g$^{-1}$.h$^{-1}$로 추정되었다. 그리고 그것은 온도상승에 따라 지수적으로 증가하였다. 호흡속도는 저장 탄수화물량이 낮아짐에 따라 비례적으로 감소했고 뿌리의 이온흡수호흡속도는 0.6648g C$H_2O$.(gN)$^{-1}$로 추정되었다.

• 한국멀티미디어학회논문지
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• 제20권9호
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• pp.1491-1501
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• 2017

In this paper, we propose a method to measure respiration rate by dividing the respiration related region in depth image using level set method. In the conventional method, the respiration related region was separated using the pre-defined region designated by the user. We separate the respiration related region using level set method combining shape prior knowledge. Median filter and clipping are performed as a preprocessing method for noise reduction in the depth image. As a feasibility test, respiration activity was recorded using depth camera in various environments with arm movements or body movements during breathing. Respiration activity was also measured simultaneously using a chest belt to verify the accuracy of calculated respiration rate. Experimental results show that our proposed method shows good performance for respiration rate estimation in various situation compared with the conventional method.

• 한국멀티미디어학회논문지
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• 제21권9호
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• pp.1076-1089
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• 2018

Respiration is the process of moving air into and out of the lung. Respiration changes the temperature in the chamber while exchanging energy. Especially the temperature of the face. Respiration monitoring using an infrared camera measures the temperature change caused by breathing. The conventional method assumes that motion is not considered and measures respiration. These assumptions can not accurately measure the respiration rate when breathing moves. In addition, the respiration rate measurement is performed by counting the number of peaks of the breathing waveform by displaying the position of the peak in a specific window, and there is a disadvantage that the breathing rate can not be measured accurately. In this paper, we use KLT tracking and block matching to calibrate limited weak movements during breathing and extract respiration waveform. In order to increase the accuracy of the respiration rate, the position of the peak used in the breath calculation is calculated by converting from a single point to a high resolution. Through this process, the respiration signal could be extracted even in weak motion, and the respiration rate could be measured robustly even in various time windows.

• 대한의용생체공학회:의공학회지
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• 제28권4호
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• pp.503-511
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• 2007

Heart rate variability(HRV) is the clinical consequence of various influences of the autonomic nervous system(ANS) on heart beat. HRV can estimate the potential physiologic rhythm from the interval between consecutive beats(RR interval or HRV data), but cardiovascular system governed by ANS is in relation to respiration and autonomic regulation. It is known as RSA representing respiration-related HR rhythmic oscillation. Because the mechanism linking the variability of HR to respiration is complex, it has so far been unknown well. In this paper, we tried to evaluate 5-min RR interval segments under control of respiration in order to find out a proper respiration rate that can estimate the ANS function. 10 healthy volunteers were included to evaluate 5-min HRV data under 4 different respiration-controlled environments; 0.03Hz, 0.1Hz, 0.2Hz, and 0.4Hz respiration. HRV data were analyzed both in the frequency and the time domain, with cross-correlation coefficient(cross-coeff.) for HRV and respiration signal. The results showed maximum cross-coeff. of 0.84 at 0.1 Hz and minimum that of 0.16 at 0.4Hz respiration. Cross-coeff was decreased at a faster rate from 0.1Hz respiration. All mean SDNN, RMSSD, and pNN50 of time domain measures were 108.7ms, 71.85ms, and 28.47%, respectively, and LF, HF, and TP of frequency domain measures were $12,722ms^2,\;658.8ms^2$, and $7,836.64ms^2$ at 0.1Hz respiration, respectively. In conclusion, 0.1Hz respiration was observed to be very meaningful from time domain and frequency domain analysis in relation to respiration and autonomic regulation of the heart.

• Journal of Ecology and Environment
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• 제42권4호
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• pp.155-162
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• 2018

Background: In ecosystem carbon cycle studies, distinguishing between $CO_2$ emitted by roots and by microbes remains very difficult because it is mixed before being released into the atmosphere. Currently, no method for quantifying root and microbial respiration is effective. Therefore, this study investigated the relationship between soil respiration and underground root biomass at varying distances from the tree and tested possibilities for measuring root and microbial respiration. Methods: Soil respiration was measured by the closed chamber method, in which acrylic collars were placed at regular intervals from the tree base. Measurements were made irregularly during one season, including high temperatures in summer and low temperatures in autumn; the soil's temperature and moisture content were also collected. After measurements, roots of each plot were collected, and their dry matter biomass measured to analyze relationships between root biomass and soil respiration. Results: Apart from root biomass, which affects soil's temperature and moisture, no other factors affecting soil respiration showed significant differences between measuring points. At each point, soil respiration showed clear seasonal variations and high exponential correlation with increasing soil temperatures. The root biomass decreased exponentially with increasing distance from the tree. The rate of soil respiration was also highly correlated exponentially with root biomass. Based on these results, the average rate of root respiration in the soil was estimated to be 34.4% (26.6~43.1%). Conclusions: In this study, attempts were made to differentiate the root respiration rate by analyzing the distribution of root biomass and resulting changes in soil respiration. As distance from the tree increased, root biomass and soil respiration values were shown to strongly decrease exponentially. Root biomass increased logarithmically with increases in soil respiration. In addition, soil respiration and underground root biomass were logarithmically related; the calculated root-breathing rate was around 44%. This study method is applicable for determining root and microbial respiration in forest ecosystem carbon cycle research. However, more data should be collected on the distribution of root biomass and the correlated soil respiration.

• 대한한의학회지
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• 제18권1호
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• pp.143-156
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• 1997

This report was conducted to quantify the pulse/respiration ratio and set up the normal range of wan-maeck(緩脈). In order to objectify the pulse diagnosis and use as basic clinical index of Cold-Hot diagnosis, we developed the hardware and software for detection and interpretation of pulse/respiration ratio, pulse/expiration ratio, pulse/respiration ratio, inspiration time, expiration time, respiration frequency, respiration time, duration of one pulse and pulse and pulse rate per minute, The results were as follows; pulse/respiration ratio is $4.30{\pm}1.03$ times, pulse/respiration ratio is $1.60{\pm}0.32$ times, pulse/respiration ratio is $2.37{\pm}0.75$ times, inspiration time is $1.35{\pm}0.20$ sec, expiration time is $1.89{\pm}0.39$ sec, respiration frequency is $17.16{\pm}3.49$ times/min, total respiration time is $3.63{\pm}0.71$ sec, duration of a pulse is $0.86{\pm}0.15$ sec, pulse rate is $71.51{\pm}12.30$ times/min.

• 대한임베디드공학회논문지
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• 제14권3호
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• pp.123-131
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• 2019

In recent years, a non-contact respiration and heart rates monitoring via IR-UWB radar has been paid much attention to in various applications - patient monitoring, occupancy detection, survivor exploring in disaster area, etc. In this paper, we address a novel approach of real time heart rate estimation using IR-UWB radar. We apply sine fitting and peak detection method for estimating respiration rate and heart rate, respectively. We also deploy two techniques to mitigate the error caused by wrong estimation of respiration rate: a moving average filter and finding the frequency of the highest occurrence. Experimental results show that the algorithm can estimate heart rate in real time when respiration rate is presumed to be estimated accurately.

• 한국식품저장유통학회지
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• 제1권2호
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• pp.87-92
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• 1994

For the measurement of the change of respiration rate caused by the gas content of storage atmosphere which furnishes important data for the interpretation of ULO storage, GC was used. It has been shown that the respiration rate and respiratory heat generation rate of Fuji apple is more than doubled in normal low temperature storage when compared with ULO storage, and that in ULO storage the respiration rate and respiratory heat generation rate directly proportional to the concentration of O2 in storage atmosphere as well as inversely proportional to that of CO2. It was possible to establish a functional formula for the respiratory heat generation rate of Fuji apple in all the storage conditions in terms of u=-0.7638+0.0003 O2-0.0007 log(CO2)+0.1369 log(Tb) concerning temperature and the concentration of O2 and CO2

• 센서학회지
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• 제17권6호
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• pp.447-453
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• 2008

Respiration rate is one of the important vital signs. Photo-plethysmography (PPG) measurement especially on a finger has been widely used in pulse oximetry and also used in estimating respiration rate. It is well known that PPG contains respiration-induced intensity variation (RIIV) signal. However, the accuracy of finger PPG method has been controversial. We introduced a new technique of enhancing motion artifact by respiration. This was achieved simply by measuring PPG on the thorax. We examined the accuracy of these two PPG methods by comparing with two existing methods based on thoracic volume and nostril temperature changes. PPG sensing on finger tip, which is the most common site of measurement, produced 6.1 % error. On the other hand, our method of PPG sensing on the thorax achieved 0.4 % error which was a significant improvement. Finger PPG is sensitive to motion artifact and it is difficult to recover fully small respiratory signal buried in waveform dominated by absorption due to blood volume changes. Thorax PPG is poor to represent blood volumes changes since it contains substantial motion artifact due to respiration. Ironically, this inferior quality ensures higher accuracy in terms of respiration measurement. Extreme low-cost and small-sized LED/silicon detector and non-constrained reflection measurement provide a great candidate for respiration estimation in ubiquitous or personal health monitoring.