• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2071-2078
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• 2009

In this paper, we proposed a non-contact respiration measurement system with ultrasonic proximity sensor. Ultrasonic proximity sensor approach of respiration measurement which respiration signatures and rates can be derived in real-time for long-term monitoring is presented. 240 kHz ultrasonic sensor has been applied for the proposed measurement system. The time of flight of sound wave between the transmitted signal and received signal have been used for a respiration measurement from abdominal area. Respiration rates measured with the ultrasonic proximity sensor were compared with those measured with standard techniques on 5 human subjects. Accurate measurement of respiration rate is shown from the 50 cm measurement distance. The data from the method comparison study is used to confirm the performance of the proposed measurement system. The current version of respiratory rate detection system using ultrasonic can successfully measure respiration rate. The proposed measurement method could be used for monitoring unconscious persons from a relatively close range, avoiding the need to apply electrodes or other sensors in the correct position and to wire the subject to the monitor. Monitoring respiration using ultrasonic sensor offers a promising possibility of non-contact measurement of respiration rates. Especially, this technology offers a potentially inexpensive implementation that could extend applications to consumer home-healthcare and mobile-healthcare products. Further advances in the sensor design, system design and signal processing can increase the range of the measurement and quality of the rate-finding for broadening the potential application areas of this technology.

• Journal of the Semiconductor & Display Technology
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• v.17 no.3
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• pp.108-112
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• 2018

In this paper, a respiration measurement method using FMCW signal for off-the-shelf smartphone is presented and investigated. The proposed algorithm transmits FMCW signal periodically instead of transmitting continuously so that one can reduce the power consumption from speaker in smartphone and the algorithm complexity. In order to eliminate the clicking noise generated when transmitting FMCW signal, Tukey window with ${\alpha}=0.01$ is applied to prevent the noise from being heard. An application program for Android OS which can transmit FMCW signal through speaker and record the reflected signals through MIC has been developed. Since the total duration of the signal transmission is set to 20msec per 1 second for the experiments, the power consumption can be decreased by 80% compared to the continuous transmission. It was confirmed that the clicking noise is inaudible as long as a smartphone is located at more than 10cm from ears. In the experiments on a sleeping child, the breathing signal of about 0.27Hz was measured.

• 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.

• 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.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2053-2054
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• 2011

Cardiopulmonary resuscitation(CPR) is performed by artificial ventilation and thoracic compression for the patient under emergent situation to maintain at least the minimum level of respiration and blood circulation for life survival. Good quality CPR requires monitoring respiration. We developed a system for continuous monitoring respirational signal while CPR, using respirational airflow sensor for CPR. Signal extraction circuit obtains pressure signal while CPR. Obtained signal would be performed analog-digital conversion and changed to airflow value by characteristic formula. Single inspiration and expiration were considered a period. Detected valid data were displayed LCD.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.17-23
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• 2017

In this paper, we implemented a respiration measurement system consisting of piezoelectric sensor, respiration signal processing device, and a viewer on a notebook. We tried an experiment for measuring respiration and detecting sleep apnea syndrome when a subject lay on a bed. We applied the respiration measurement algorithm to sensor data obtained from four subjects. In order to get a good graph shape, data manipulation methods such as moving averages and maximum values were applied. The window size for moving average was chosen as N=70, and the threshold value for each subject was customized. In this case, the proposed system showed 96.0% accuracy. When the maximum value among 90 data was applied instead of moving average, our system achieved 95.1% accuracy. In an experiment for detecting sleep apnea syndrome, the system showed that sleep apnea occurred correctly and calculated the average interval of sleep apnea. While infants or the elderly as well as patients with sleep apnea syndrome are lying down on a bed, our results are also expected to be able to cope with some accidental emergency situation by observing their respiration and detecting sleep apnea.

• Journal of IKEEE
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• v.11 no.1 s.20
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• pp.24-29
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• 2007

In this paper, we developed a Mac-Yule measurement system which consider psychological stable state of patience. The developed system consist with a hardware device that can derive a EEG, respiration and pulse wave, and a software which acquire a biological signal and signal processing The EEGs are derived with bipolar method from frontal head. The respiration signals obtain from nasal front with a transducer which consist with thermistor bridge. The pulse waves are detected from earlobe with photoplethysmograph method. A power spectrum of EEG are used as the decision parameters of psychological stable state of patience. The decision of Mac-Yule are defined as origin text method that of numbers of pulse to 1 respiration period. As the results of experiment with developed system, we could have a spectrum band discretion of EEG signal, stable respiration signal detection and automatic gain controlled pulse signal with realtime. And then, we could detect Mac-Yules from processed signals.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.4
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• pp.100-108
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• 2019

In this paper, a new stacked element pressure sensor has proposed for heartbeat and respiration measurement. This device can be directly attached to an individual's chest; heartbeat and respiration are detected by the pulsatile vibration and deformation of the chest. A key feature of the device is the simultaneous measurement of heart rate and respiration. The structure of the sensor consists of two stacked elements, in which one element includes one polyvinylidene fluoride (PVDF) thin film bonded on polydimethylsiloxane (PDMS) substrate. In addition, for the measurement and signal processing, the electric circuit and the filter are simply constructed with an OP-amp, resistance, and a capacitor. One element (element1, PDMS) maximizes the respiration signal; the other (element2, PVDF) is used to measure heartbeat. Element1 and element2 had sensitivity of 0.163V/N and 0.209V/N, respectively, and element2 showed improved characteristics compared with element1 in response to force. Thus, element1 and element2 were optimized for measuring respiration heart rate, respectively. Through mechanical and vivo human tests, this sensor shows the great potential to optimize the signals of heartbeat and respiration compared with commercial devices. Moreover, the proposed sensor is flexible, light weight, and low cost. All of these characteristics illustrate an effective piezoelectric pressure sensor for heartbeat and respiration measurements.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.407-413
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• 2018

Most sleep apnea patients exhibit severe snoring, and long-lasting sleep apnea may cause insomnia, hypertension, cardiovascular diseases, stroke, and other diseases. Although polysomnography is the typical sleep diagnostic method to accurately diagnose sleep apnea by measuring a variety of bio-signals that occur during sleep, it is inconvenient as the patient has to sleep with attached electrodes at the hospital for the diagnosis. In this study, a diagnostic pillow is designed to measure respiration, heart rate, and snoring during sleep, using only one polyvinylidene fluoride (PVDF) sensor. A PVDF sensor with piezoelectric properties was inserted into a specially made instrument to extract accurate signals regardless of the posture during sleep. Wavelet analysis was used to identify the extractability and frequency domain signals of respiration, heart rate, and snoring from the signals generated by the PVDF sensor. In particular, to separate the respiratory signal in the 0.2~0.5 Hz frequency region, wavelet analysis was performed after removing 1~2 Hz frequency components. In addition, signals for respiration, heart rate, and snoring were separated from the PVDF sensor signal through a Butterworth filter and median filter based on the information obtained from the wavelet analysis. Moreover, the possibility of measuring sleep apnea from these separated signals was confirmed. To verify the usefulness of this study, data obtained during sleeping was used.

• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.280-285
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• 2017

This paper presents a respiration measurement sleeping pillow based on pressure sensors. The respiration measurement sleeping pillow system consists of a sleeping pillow, an interface circuit, a respiration measurement system, and four force-sensitive resistor(FSR) sensors attached at the bottom of the sleeping pillow. The FSR sensors are used to detect the respiration signals induced by the body movement while breathing. The respiration signals of a twenty health man were measured and analyzed by utilizing the respiration measurement sleeping pillow system. The pillow system could detect the respiration signals and had similar characteristics to the chest type BIOPAC respiration sensor used by medical doctors. The respiration rates of ten subjects were also measured. The average measurement accuracy was about 98.8%. The research results showed that this pillow system can be used to detect and analyze the respiration signal when sleeping for the better sleep management.