• Journal of Biomedical Engineering Research
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• v.28 no.4
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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.

• The Journal of Korean Medicine
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• v.18 no.1
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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.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.10 no.2
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• pp.132-150
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• 2006

Objectives : The objective is that we measure and analyze Pulse-Respiration Ratio and Body Composition Analysis to study the correlation between both. Methods : First, after subjects take a rest over 10 minutes, we measure their electrocardiogram and respiration pattern through which we take average peak interval to calculate an average pulse cycle and a respiration cycle. An average respiration cycle divided by an average Pulse Rate gives Pulse-Respiration Ratio. Next, we draw out 22 Body Composition Analysis indicators by using In-Body 720 model. Last, we analyze and take statistics on them by using SPSS 13.0 program. Results : Negative is the correlation between P/R Ratio and Body Composition Analysis indicator like fatness degree, body fat volume, body fat rate, abdominal fatness, BMI. Conclusions : 1. The higher P/R Ratio the more likely to be thin, the lower P/R Ratio the more likely to be fat. 2. We separately analyze P/R Ratio depending on each breathing frequency and pulse frequency to find out that breathing frequency has great influence and that breathing frequency decides the fatness degree. 3. In study on the correlation between P/R Ratio and Body Composition Analysis, fatness degree, in-body fat volume, in-body fat rate, BMI are the related indicators, which shows the connection with the fatness indicators. 4. In study on the correlation between Han-Yeol [寒熱] grade and Body Composition Analysis indicators, the result is that Han[寒] has no connection and that only Yeol[熱] grade has something to do with it, which means the higher heat symptom subjects have, the more basic metabolism volume and muscular build they have.

• Journal of the Ergonomics Society of Korea
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• v.27 no.4
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• pp.95-101
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• 2008

This research is to develop PPG filtering method for respiration measurement in U-Health Care system. Respiration rate was determined by filtering PPG and analyzing its spectrum. Optimal filter of PPG has been selected to get respiration by testing 120 sets of experiment data using 700 filtering cases. As a result, 2nd order Bessel-filter that used band-pass cutoff frequency at 0.175~0.4Hz with second order was good at developing respiration signal. Respiration signal in time domain could be continuously analyzed by converting frequency domain using spectrum analysis. 24 seconds has been found to be optimal time duration of collecting PPG data for determining respiration. Therefore, this study was successful of getting not only heart activity but also respiration by only PPG. Minimal invasive measurement obtaining multi-bio information by one sensor can be expected to apply to U-Health Care and human computer interaction.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.733-740
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• 2004

In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) is proposed. The whole system consists of two-lead electrocardiogram acquisition (lead Ⅰ and Ⅱ), baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problem of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we proposed a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 subjects, and we could obtain satisfactory respiration signals that shows high correlation (r>0.9) with the signal acquired from the chest-belt respiration sensor.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.220-223
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• 2011

Respiration signal of the vital signs is an important parameter in clinical parts. To extract the respiration signal from PPG signal for mobile healthcare system is difficult because the bands of the motion artifacts and respiration in the frequency domain are overlapped. This study to improve this problem suggested a respiration extraction method using the independent component analysis and evaluated its performances. In results of evaluation, the ICA method showed better performance than LPF suggested recently.

• Journal of Biomedical Engineering Research
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• v.38 no.5
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• pp.264-270
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• 2017

A Doppler radar sensor was applied to detect respirations and heartbeats of persons who were lying on a bed. This study is preliminary study aiming at non-contact and non-intrusive respiration and heart rate monitoring during sleep in daily life. For the experiments, 10GHz Doppler radar with patch-type antenna was used and installed on the upper right and the distance between the body and the antenna was 1 m. The results show that each signal of respiration and heartbeat is observed in each frequency band however the frequency band and the waveform vary according to the subjects and the posture. The results show that the heartbeats can be detected with the peak detection in some frequency band. This study shows the feasibility of applying the Doppler radar to detection of heartbeat and respiration during sleep and further studies about heartbeat detection algorithm are required.

• Journal of Biomedical Engineering Research
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• v.26 no.6
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• pp.373-381
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• 2005

The respiratory and heart beat signals are the fundamental physiological signals for sleep monitoring in the home. Using the air mattress sensor system, the respiration and heart beat movements can be measured without any harness or sensor on the subject's body which makes long term measurement difficult and troublesome. The differential measurement technique between two air cells is adopted to enhance the sensitivity. The concept of the balancing tube between two air cells is suggested to increase the robustness against postural changes during the measurement period. With this balancing tube, the meaningful frequency range could be selected by the pneumatic filter method. The mathematical model for the air mattress and balancing tube was suggested and the validation experiments were performed for step and sinusoidal input. The results show that the balancing tube can eliminate the low frequency component between two cells effectively. This technique was applied to measure the respiration and heart beat on the bed, which shows the potential applications for sleep monitoring device in home. With the analysis of the waveform, respiration intervals and heart beat intervals were calculated and compared with the signal from conventional methods. The results show that the measurement from air mattress with balancing tube can be used for monitoring respiration and heart beat in various situations.

• Fire Science and Engineering
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• v.33 no.4
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• pp.83-88
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• 2019

This study examined the concentration of combustion gases while considering low ventilation and respiration frequency. A one-quarter-size ISO 9705 room corner test was performed. The concentrations of carbon monoxide and oxygen were measured in each case with the continuous inhalation of combustion gas with low ventilation (2, 6, and 10 LPM) and different respiration frequencies (2 s, 5 s, and infinity). The combustion of a gasoline pool fire in the compartment had a theoretical heat release rate of 5.34 kW. The results show that the deviation of the gas concentrations becomes higher as the low ventilation increases compared to the respiration frequency. In addition, as the respiration frequency increases, the variation in the minimum oxygen concentration is larger than the average value, while in the case of carbon monoxide, the variation in the average value is larger than the maximum value. These results show that the inhalation characteristics of refugees should be considered to investigate fires.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.15 no.1
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• pp.95-110
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• 2011

Objectives: The aim of the present study is to define breath-holding in spontaneous respiration and to observe the difference of respiratory variables, EEG and HRV. Methods: 46 healthy young volunteers (M:F=31:15) were recruited in the study. By measuring and analysing respiration, EEG and HRV in the spontaneous respiration. We segment subjects by 100% of coefficient of variation in the breath-holding. Results & Conclusions: 1. There is a period of breath-holding after expiration and before endeavored inspiration, in the course of respiration. The greater coefficient of variation in the breath-holding, longer respiration period mean, inspiration period mean and breath-holding mean in respiratory variable. 2. There was no significant difference between HRV parameters. 3. The greater coefficient of variation in the breath-holding, the higher ${\beta}$ frequency and ${\gamma}$ frequency in the left prefrontal lobe.