• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.33-42
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• 2010

In this study, we have proposed a simple cardiorespiratory monitoring method based on displacements of human body which occurs due to periodic heartbeat and breathing. The proposed system consists of an aircushion, pressure sensing hardware and heartbeat and respiration signals extraction algorithm. The aircushion was used for unconstrained measurement of the respiration and heartbeats without a sensor attached on the subject's skin surface. The displacements of subject sitting on the aircushion cause small pressure variations. These variations are amplified and filtered with the pressure sensing hardware. Finally, heart rate and respiration rate are extracted by signal processing algorithm based on frequency domain filter. To evaluate the performance, extracted respiration and heart rate from proposed system were compared with conventional methods. The average sensitivity of respiration and heart rate are 98.67% and 99.24%, respectively. These results show the proposed method has advantages of installing and processing simplicity so as to be used easily in unconstrained respiration and heart rate monitoring in daily life.

• Proceedings of the KAIS Fall Conference
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• 2011.05b
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• pp.583-585
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• 2011

이 논문에서는 비접촉 방식의 심박 및 호흡 검출이 가능한 FFT를 이용하는 새로운 검출 방식의 알고리즘을 제안한다. 기존 FFT 방식은 주파수 도메인에서 필터링을 수행한 후 IFFT 후 특징점 추출 알고리즘을 수행하여 심박 및 호흡을 추출한다. 이 논문에서는 제안된 FFT 방식을 사용하여 기존의 FFT 방식과 달리 FFT를 한 후 주파수 영역에서 바로 심박수 및 호흡수를 추출할 수 있음을 제안한다.

• Journal of electromagnetic engineering and science
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• v.10 no.4
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• pp.250-255
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• 2010

This paper presents a non-contact measurement method of vital signal by the use of multiple-input multiple-output (MIMO) bio-radar system, configured with two antennas that are separated by a certain distance. The direction of arrival (DOA) estimation algorithm for coherent sources was applied to detect vital signals coming from different spatial angles. The proposed MIMO bio-radar system was composed of two identical transceivers sharing single VCO with a PLL. In order to verify the performance of the system, the DOA estimation experiment was completed with respect to the human target at angles varying between $-50^{\circ}$ and $50^{\circ}$ where the bio-radar system was placed at distances (corresponding to 50 cm and 95 cm) in front of a human target. The proposed MIMO bio-radar system can successfully find the direction of a human target.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.216-222
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• 2013

It is known that blood circulation in human body causes the skin tone to change concurrently with heartbeats. A number of apps have been developed to measure the heartbeat using smartphone camera; however, no any further analysis is performed. In this paper we propose an algorithm that detects heartbeats from the phone's camera and further extracts the heart rate variability (HRV). We compare the HRV extracted from the camera with the HRV extracted from the electrocardiogram. We estimated a number of commonly used HRV characteristics and compared them. Our results show that smartphone camera leads to slightly overestimated characteristics although the difference in extracted HRV signals is negligible. As a consequence we suggest that a smartphone camera can be employed in a quick heart diagnosis and diagnosis of autonomic nervous system.

• Journal of Biomedical Engineering Research
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• v.29 no.6
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• pp.466-476
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• 2008

The more people use ambulatory electrocardiogram(ECG) for arrhythmia detection, the more researchers report the automatic classification algorithms. Most of the previous studies don't consider the un-balanced data distribution. Even in patients, there are much more normal beats than abnormal beats among the data from 24 hours. To solve this problem, the hierarchical classification using 21 features was adopted for arrhythmia abnormal beat detection. The features include R-R intervals and data to describe the morphology of the wave. To validate the algorithm, 44 non-pacemaker recordings from physionet were used. The hierarchical classification model with 2 stages on domain knowledge was constructed. Using our suggested method, we could improve the performance in abnormal beat classification from the conventional multi-class classification method. In conclusion, the domain knowledge based hierarchical classification is useful to the ECG beat classification with unbalanced data distribution.

• Korean Journal of Veterinary Research
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• v.36 no.1
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• pp.235-245
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• 1996

Serial ultrasonographic examinations were performed on 9 pregnant Korea Jin-do bitches that were the Korean native breed, from days 15 to 60 pregnancy to determine the time of first detection and ultrasonographic appearance of the fetal and extra-fetal structures of pregnancy. Gestational age was timed from the day of ovulation (Day 0), which was estimated to occur when plasma progesterone concentration was first increased above 4.0 ng/ml. Gestational ages at earliest detection of the following fetal and extra-fetal structures were; gestational sac at days 17 to 22; placental layers in the uterine wall at days 20 to 24; zonary placenta at days 25 to 28; yolk sac membrane at days 22 to 24; amnionic membrane at days 27 to 29; embryo initial detection at days 21 to 23; fetal heartbeat at days 21 m 25; bipolar shape embryo at days 25 to 26; fetal movement at days 28 to 31; limb buds at days 31 to 35; anechoic area in head at days 31 to 36; stomach at days 34 to 37; urinary bladder at days 34 to 37; skeleton at days 36 to 38; dorsal sagittal tubular structure in vertebrae at days 36 to 38; lung hyperechoic vs liver at days 37 to 39; liver hypoechoic vs abdomen at days 37 to 40 and kidney at days 43 to 48, respectively.

• Journal of Biomedical Engineering Research
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• v.45 no.3
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• pp.128-137
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• 2024

It is necessary to develop a pulsatile Extracorporeal Membrane Oxygenator (p-ECMO) with counter-pulsation control(CPC), which ejects blood during the diastolic phase of the heart rather than the systolic phase, due to the known issues with conventional ECMO causing fatal complications such as ventricular dilation and pulmonary edema. A promising method to simultaneously detect the pulsations of the heart and p-ECMO is to analyze blood pressure waveforms using deep neural network technology(DNN). However, the accurate detection of cardiac rhythms by DNNs is challenging due to various noises such as pulsations from p-ECMO, reflected waves in the vessels, and other dynamic noises. This study aims to evaluate the accuracy of DNNs developed for CPC in p-ECMO, using human-like blood pressure waveforms reproduced in an in-vitro experiment. Especially, an experimental setup that reproduces reflected waves commonly observed in actual patients was developed, and the impact of these waves on DNN judgments was assessed using a multiple DNN (m-DNN) that provides accurate determinations along with a separate index for heartbeat recognition ability. In the experimental setup inducing reflected waves, it was observed that the shape of the blood pressure waveform became increasingly complex, which coincided with an increase in harmonic components, as evident from the Fast Fourier Transform results of the blood pressure wave. It was observed that the recognition score (RS) of DNNs decreased in blood pressure waveforms with significant harmonic components, separate from the frequency components caused by the heart and p-ECMO. This study demonstrated that each DNN trained on blood pressure waveforms without reflected waves showed low RS when faced with waveforms containing reflected waves. However, the accuracy of the final results from the m-DNN remained high even in the presence of reflected waves.

• Journal of Veterinary Clinics
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• v.16 no.1
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• pp.128-137
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• 1999

Plasma progesterone (P$_4$) concentrations were measured for confirming the estrus observation and for the early pregnancy diagnosis in 130 cows of small farmers. Ultrasonographic examinations were performed from day 30 after artificial insemination to establish the characteristic ultrasonographic appearances of gestational structures in each pregnant stages. Of the 130 cows inseminated, 111 cows (85.4%) were an ovulatory estrus, 12 cows (9.2%) were an unovulatory estrus, and 7 cows (5.4%) were the error of estrus detection, respectively. The accuracy for early pregnancy diagnosis in 111 ovulatory estrus cows achieved when the discriminatory concentration at day 21 after artificial insemination was placed at 3.0 ng-/ml in plasma, was 86.7 % for positive diagnosis and 100% for negative diagnosis, respectively. Pregnancy diagnosis by ultrasonography were performed to evaluate gestational structures from day 30 after artificial insemination in 83 cows. Pregnant cows were 72 of 83 cows. The characteristic ultrasonography of gestational structures in each gestational stages was as follows. The embryo proper was observed within anechoic fetal fluid between 28 and 40 days after insemination, and amnion and embryonic heartbeat was also detected in this period. Between days 41 and 50, embryo proper was detected as an discriminated from head and body, and forelimb buds and hindlimb buds were also observed in this period. Between days 51 and 60, an embryo proper was clearly discriminated from head and body, and fetal movement, forelimb buds and hindlimb buds were observed in this period. Between days 61 and 70, fetus was completely developed, and fetal skeleton, organs and cotyledon were observed. After day 71, each organs of fetus were rapidly developed and a fetus was partially observed in screen because fetus was too big and larger, These results indicate that plasma P$_4$ determination at days 0,6 and 21 after artificial insemination can be utilized for confirming the estrus observation and for early pregnancy diagnosis. Also, ultrasonography was reliable method for early pregnancy diagnosis at day 30 after artificial insemination.

• Journal of IKEEE
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• v.24 no.4
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• pp.1188-1191
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• 2020

In this paper, automotive safety and convenience service is proposed based on bluetooth and smart watch. The proposed service performs accident detection, kidnapping detection, kid-left-alone-in-car detection, parking location recording, and smart key function. Conventional smartphone services often fails to precisely recognize accident and kidnapping situations since smartphone is located on the dashboard or in the bag. On the contrary, smartwatch recognizes accident and kidnapping situations more precisely since it is always worn on the wrist with hearbeat monitoring. The proposed service recognise various situations around drives and passengers using acceleration sensor, GPS sensor, heartbeat sensor and bluetooth link status. It also performs accident notice, sound recording, and other necessary actions. It also performs door opening, door closing, hazard light flickering, and other necessary actions using OBD-II connection to the vehicle.

• Journal of Embryo Transfer
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• v.23 no.1
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• pp.5-11
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• 2008

Serial ultrasonographic examinations were daily performed from 15 days after ovulation until parturition to determine the time of first detection and ultrasonographic appearance of the fetal and extra-fetal structures in pregnant 10 Maltese, 10 Yorkshire Terrier, 15 Shih-tzu, and 10 Miniature Schnauzer bitches, respectively. Gestational age was timed from the day of ovulation (day 0), which was estimated to occur when plasma progesterone concentration was first increased above 4.0ng/ml. The gestational length was $63.4{\sim}63.6$ (range: $61{\sim}65$) days and the geatational length was no statistically significant difference among bitches (p>0.05). The initial detection of the extra-fetal structures were; gestational sac at days $18.9{\sim}19.5\;(17{\sim}22)$, zonary placenta at days $24.6{\sim}25.5\;(23{\sim}28)$, yolk sac membrane at days $24.6{\sim}25.5\;(23{\sim}27)$, yolk sac tubular shape at days $26.1{\sim}26.3\;(24{\sim}28)$, and amniotic membrane at days $26.1{\sim}28.2\;(24{\sim}31)$, respectively. The time of the first detection of the extra-fetal structures were no statistically significant difference among bitches (p>0.05). The initial detection of the fetal structures were; embryo initial detection at days $22.5{\sim}22.9\;(21{\sim}24)$, heartbeat at days $23.2{\sim}23.8\;(21{\sim}25)$, embryo bipolar shape $27.6{\sim}28.9\;(26{\sim}30)$, fetal movement at days $31.9{\sim}32.8\;(27{\sim}34)$, limb buds at days $29.1{\sim}30.7\;(27{\sim}33)$, stomach at days $31.1{\sim}33.1\;(29{\sim}34)$, urinary bladder at days $32.4{\sim}33.2\;(29{\sim}35)$, skeleton at days $34.7{\sim}35.9\;(34{\sim}39)$, and kidney at days $42.1{\sim}44.7\;(41{\sim}48)$, respectively. The the time of the first detection of the fetal structures were no statistically significant difference among bitches (p>0.05). These results indicate the evaluation of the time of first detection and ultrasonographic characteristics of the gestational structures might be useful for pregnancy diagnosis, estimating fetal age, embryonic resorption, fetal monster, abnormal fetal growth and fetal viability, respectively.