• Title, Summary, Keyword: Respiration estimation

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A Non-contact Realtime Heart Rate Estimation Using IR-UWB Radar (IR-UWB 레이더를 이용한 비접촉 실시간 심박탐지)

  • Byun, Sang-Seon
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.3
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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.

Level Set based Respiration Rate Estimation using Depth Camera (레벨 셋 기반의 깊이 카메라를 이용한 호흡수 측정)

  • Oh, Kyeong Taek;Shin, Cheung Soo;Kim, Jeongmin;Yoo, Sun Kook
    • Journal of Korea Multimedia Society
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    • v.20 no.9
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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.

Apnea Detection and Respiration Rate Estimation Using IR-UWB Radar Signals (IR-UWB 레이다 기반의 무호흡 검출 및 호흡수 측정)

  • Ko, Inchang;Park, Hyung Chul
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.28 no.10
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    • pp.802-809
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    • 2017
  • This paper presents a novel apnea detection and respiration rate estimation method using impulse-radio ultra-wideband (IR-UWB) radar. The proposed method utilizes amplitude, time of arrival, and power in the selected band. The experimental results show that respiration rate can be estimated accurately using proposed method. And, it is shown that the selectivity between apnea and respiration can be improved more than 50 dB using the proposed method.

Respiration Rate Estimation using IR-UWB Radar Signals Robust to Body-Rocking (인체 움직임에 강인한 IR-UWB 레이더 기반의 호흡속도추정)

  • Park, Hyung Chul
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.9
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    • pp.49-54
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    • 2012
  • This paper presents a novel respiration rate estimation method based on joint amplitude and time of arrival (TOA) using impulse-radio ultra-wideband (IR-UWB) radar signals. Through analysis of the affect of body-rocking, it is shown that body-rocking information does not distort the respiration rate and exists at integer multiples of the body-rocking rate from the respiration rate. Based on the analysis, the convolution of the temporal sequence of the maximum amplitude and that of the TOA is proposed. The analysis results show that the frequency components of respiration are improved more than 10dB compared with those obtained using other existing methods.

Accuracy improvement of respiration rate based on photo-plethysmography by enhancing motion artifact (광용적맥파(PPG)를 이용한 호흡수 측정에 있어서 동잡음을 이용한 정확도 향상)

  • Huh, Young-Jung;Yoon, Gil-Won
    • Journal of Sensor Science and Technology
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    • v.17 no.6
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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.

An Improved Algorithm for Respiration Signal Extraction from Electrocardiogram Using Instantaneous Frequency Estimation based on Hilbert Transform (힐버트 변환에 기반한 순간주파수 추정을 이용한 개선된 심전도 유도 호흡신호 추출 알고리즘)

  • Park Sung-Bin;Yi Kye-Hyoung;Kim Kyung-Hwan;Yoon Hyoung-Ro
    • 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.

Improvement of Dynamic Respiration Monitoring Through Sensor Fusion of Accelerometer and Gyro-sensor

  • Yoon, Ja-Woong;Noh, Yeon-Sik;Kwon, Yi-Suk;Kim, Won-Ki;Yoon, Hyung-Ro
    • Journal of Electrical Engineering and Technology
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    • v.9 no.1
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    • pp.334-343
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    • 2014
  • In this paper, we suggest a method to improve the fusion of an accelerometer and gyro sensor by using a Kalman filter to produce a more high-quality respiration signal to supplement the weakness of using a single accelerometer. To evaluate our proposed algorithm's performance, we developed a chest belt-type module. We performed experiments consisting of aerobic exercise and muscular exercises with 10 subjects. We compared the derived respiration signal from the accelerometer with that from our algorithm using the standard respiration signal from the piezoelectric sensor in the time and frequency domains during the aerobic and muscular exercises. We also analyzed the time delay to verify the synchronization between the output and standard signals. We confirmed that our algorithm improved the respiratory rate's detection accuracy by 4.6% and 9.54% for the treadmill and leg press, respectively, which are dynamic. We also confirmed a small time delay of about 0.638 s on average. We determined that real-time monitoring of the respiration signal is possible. In conclusion, our suggested algorithm can acquire a more high-quality respiration signal in a dynamic exercise environment away from a limited static environment to provide safer and more effective exercises and improve exercise sustainability.

Effect of precipitation on soil respiration in a temperate broad-leaved forest

  • Jeong, Seok-Hee;Eom, Ji-Young;Park, Joo-Yeon;Chun, Jung-Hwa;Lee, Jae-Seok
    • Journal of Ecology and Environment
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    • v.42 no.2
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    • pp.77-84
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    • 2018
  • Background: For understanding and evaluating a more realistic and accurate assessment of ecosystem carbon balance related with environmental change or difference, it is necessary to analyze the various interrelationships between soil respiration and environmental factors. However, the soil temperature is mainly used for gap filling and estimation of soil respiration (Rs) under environmental change. Under the fact that changes in precipitation patterns due to climate change are expected, the effects of soil moisture content (SMC) on soil respiration have not been well studied relative to soil temperature. In this study, we attempt to analyze relationship between precipitation and soil respiration in temperate deciduous broad-leaved forest for 2 years in Gwangneung. Results: The average soil temperature (Ts) measured at a depth of 5 cm during the full study period was $12.0^{\circ}C$. The minimum value for monthly Ts was $-0.4^{\circ}C$ in February 2015 and $2.0^{\circ}C$ in January 2016. The maximum monthly Ts was $23.6^{\circ}C$ in August in both years. In 2015, annual precipitation was 823.4 mm and it was 1003.8 mm in 2016. The amount of precipitation increased by 21.9% in 2016 compared to 2015, but in 2015, it rained for 8 days more than in 2016. In 2015, the pattern of low precipitation was continuously shown, and there was a long dry period as well as a period of concentrated precipitation in 2016. 473.7 mm of precipitation, which accounted for about 51.8% of the precipitation during study period, was concentrated during summer (June to August) in 2016. The maximum values of daily Rs in both years were observed on the day when precipitation of 20 mm or more. From this, the maximum Rs value in 2015 was $784.3mg\;CO_2\;m^{-2}\;h^{-1}$ in July when 26.8 mm of daily precipitation was measured. The maximum was $913.6mg\;CO_2\;m^{-2}\;h^{-1}$ in August in 2016, when 23.8 mm of daily precipitation was measured. Rs on a rainy day was 1.5~1.6 times higher than it without precipitation. Consequently, the annual Rs in 2016 was about 12% higher than it was in 2015. It was shown a result of a 14% increase in summer precipitation from 2015. Conclusions: In this study, it was concluded that the precipitation pattern has a great effect on soil respiration. We confirmed that short-term but intense precipitation suppressed soil respiration due to a rapid increase in soil moisture, while sustained and adequate precipitation activated Rs. In especially, it is very important role on Rs in potential activating period such as summer high temperature season. Therefore, the accuracy of the calculated values by functional equation can be improved by considering the precipitation in addition to the soil temperature applied as the main factor for long-term prediction of soil respiration. In addition to this, we believe that the accuracy can be further improved by introducing an estimation equation based on seasonal temperature and soil moisture.

Experimental Estimation of the Effect of Rainfall Interception on Soil Respiration in a Broad-leaved Deciduous Forest in Western Japan (일본 서부 낙엽활엽수림의 차단 강수가 토양호흡에 미치는 영향 평가)

  • Tamai, Koji
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.11 no.4
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    • pp.247-251
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    • 2009
  • To estimate the effect of rainfall on soil respiration, soil $CO_2$ efflux was measured with a manipulation of rainfall interception at a broad-leaved deciduous forest in western Japan from 20 February to 19 November 2001. The diurnal patterns of soil respiration observed at the intercepted subplot ($F_c$) were quite similar to those of soil temperature at 0.2 m depth with a maximum around midnight and a minimum from noon to early afternoon. Such diurnal patterns have not been observed in the previous studies at the same study site under natural conditions (which manifested no clear diurnal variations). Furthermore, the magnitudes of $F_c$ showed substantial differences (e.g., ~50% reduction under water-limited conditions) compared to those of the potential soil respiration under natural conditions ($F_{cal}$). These findings demonstrate that rainfall events not only affected the magnitude of soil $CO_2$ efflux but also modified the vertical structure of soil temperature, thereby altering diurnal patterns of soil respiration.

Estimation of Respiration Using Photoplethysmograph During Sleep (광용적맥파 신호를 이용한 수면 중 호흡 추정)

  • Park, Jong-Uk;Lee, Jeon;Lee, Hyo-Ki;Kim, Hojoong;Lee, Kyoung-Joung
    • Journal of Biomedical Engineering Research
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    • v.34 no.3
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    • pp.105-110
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    • 2013
  • Respiratory signal is one of the important physiological information indicating the status and function of the body. Recent studies have provided the possibility of being able to estimate the respiratory signal by using a change of PWV(pulse width variability), PRV(pulse rate variability) and PAV(pulse amplitude variability) in the PPG (photoplethysmography) signal during daily life. But, it is not clear whether the respiratory monitoring is possible even during sleep. Therefore, in this paper, we estimated the respiration from PWV, PRV and PAV of PPG signals during sleep. In addition, respiration rates of the estimated respiration signal were calculated through a time-frequency analysis, and errors between respiration rates calculated from each parameter and from reference signal were evaluated in terms of 1 sec, 10 sec and 1 min. As a result, it showed the errors in PWV(1s: $36.38{\pm}37.69$ mHz, 10s: $36.53{\pm}38.16$ mHz, 60s: $30.35{\pm}38.72$ mHz), in PRV(1s: $1.45{\pm}1.38$ mHz, 10s: $1.44{\pm}1.37$ mHz, 60s: $0.45{\pm}0.56$ mHz), and in PAV(1s: $1.05{\pm}0.81$ mHz, 10s: $1.05{\pm}0.79$ mHz, 60s: $0.56{\pm}0.93$ mHz). The errors in PRV and PAV are lower than that of PWV. Finally, we concluded that PRV and PAV are more effective than PWV in monitoring the respiration in daily life as well as during sleep.