• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.1
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• pp.50-54
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• 2014

This study presents a method for heart rate detection using oscillation wave signal and tries to enhance the performance of peak detection. For this objective, the method uses the average slopes around the main peak. The crossing point of the increasing and the decreasing slopes is selected as the peak point of heart rate period. The proposed method showed smoothed heart rate graph and reduced irregularity in heart rate values.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1194-1199
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• 2009

Heart rate may be a very important parameter in human health. To extract heart rate, the electrocardiogram(ECG) is commonly used. But the ECG acquisition procedure is very complex. On the other hand, the acquisition of pulse wave or photoplethysmogram(PPG) is very easy. However, the peak of PPG is not so sharp as ECG. This study tries to enhance the performance of peak detection in PPG signal. The method uses the average slopes around the main peak. The crossing point of the increasing and the decreasing slopes is selected as the peak point of heart rate period. The proposed method showed smoothed heart rate graph and reduced irregularity in heart rate values.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.441-448
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• 2007

Heart rate variability (HRV) in electrocardiogram (ECG) is an important index for understanding the health status of heart and the autonomic nervous system. Most HRV analysis approaches are based on the proper heart rate (HR) data. Estimation of heart rate is thus a key process in the HRV study. In this paper, we report an innovative method to estimate the heart rate. This method is mainly based on the concept of periodicity transform (PT) and instantaneous period (IP) estimate. The method presented is accordingly called the "PT-IP method." It does not require ECG R-wave detection and thus possesses robust noise-immune capability. While the noise contamination, ECG time-varying morphology, and subjects' physiological variations make the R-wave detection a difficult task, this method can help us effectively estimate HR for medical research and clinical diagnosis. The results of estimating HR from empirical ECG data verify the efficacy and reliability of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.167-174
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• 2002

This study describes a fetal heart rate(FHR) estimation algorithm using phonogram. Using a phonogram amplifier, various fetal heart sounds are collected in a university hospital. The FHR estimation algorithms consists of a lowpass filter, decimation, envelop detection, pitch detection, and post-processing. The post-processing is the FHR decision procedure using all informations of fetal heart rates. Using the algorithm and other parameters of fetal heart sound, a fetal monitoring software was developed. This can display the original signals, the FFT spectra, FHR and its trajectory. Even though the fetal phonogram amplifier detects the fetal heart sounds well, the sound quality is not so good as the ultrasonography. In case of very week fetal heart sound, autocorrelation of it showed clear periodicity. But two main peaks in one period is an obstacle in pitch detection and peaks are not so vivid. The proposed FHR estimation algorithm showed very accurate and stable results. Since the developed software displays multiple parameters in real time and has convenient functions, it will be useful for the phonogram-style fetal monitoring device.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1978_1979
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• 2009

Heart rate may be a very important parameter in human health. To extract heart rate, the electrocardiogram(ECG) is commonly used. But the ECG acquisition procedure is somewhat complex. On the other hand, the acquisition of pulse wave or photoplethysmogram(PPG) is very easy. However, the peak of PPG is not so sharp as ECG. This study tries to enhance the performance of period detection in PPG signal. The method uses the average slopes around the main peak. The crossing point of the increasing and the decreasing slopes is selected as the peak point of heart rate period. The proposed method showed smoothed heart rate graph and reduced irregularity in heart rate values.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.185-190
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• 1989

In this paper, the discriminant analysis was performed on parameter for detection of cardiac arrythmia. The parameters used for discriminant analysis was two group. One group consist of 05 width and Heart rate, and the other Morphology and Heart Rate. For this study, we designed data acquisition system for EKG signals. The parameters pre-processed by this system was heart rate, 05 width and Morphology. And then, we analyzed the discriminancy of two group and extracted the quantity of discriminancy. The analysis results showed first that the group with morphology and heart rate is better discriminant than with 05 width and heart rate : next, that it can quantify the discriminany of each group of diseases.

• Korean Journal of Veterinary Service
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• v.13 no.2
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• pp.189-195
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• 1990

During 9 months (March-November, 1989), observation of Leucocytozoon infection rate to blood and parenchymatous viscera (spleen, liver, heart) in Pusan, Gyeongnam (Kimhae, Yangsan) districts slaughtered chicken and the results obtained were as follow : 1. Among the blood smear sample of 213 heads of the chicken, 43 heads (20.2%) were infected with Leucocytozoon 2nd stage gametocyte and 4 heads (1.9%) were mixed infected with Leucocytozoon 5th stage gametocyte. 2. In histopathological detection of schizont in tissues section of spleen, liver and heart, there were 16.7% in spleen, 5.6％ in liver and 9.1％ in heart, mean detection rate were 10.6%. Spleen had the highest detection rate of schizont. 3. In seasonal-related Infection rate, summer was higher than spring.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.25-32
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• 2022

IR-UWB radar has been regarded as the most promising technology for non-contact respiration and heartbeat monitoring because of its ability of detecting slight motion even in submillimeter range. Measuring heart rate is most challenging since the chest movement by heartbeat is quite subtle and easily interfered with by a random body motion or background noise. Additionally, periodic sampling can be limited by the performance of computer that handles the radar signals. In this paper, we deploy Lomb-Scargle periodogram method that estimates heart rate even with irregularly sampled data and uneven signal amplitude. Lomb-Scargle periodogram is known as a method for finding periodicity in irregularly-sampled and noisy data set. We also implement a motion detection scheme in order to make the heart rate estimation pause when a random motion is detected. Our scheme is implemented using Novelda's X4M03 radar development kit and its corresponding drivers and Python packages. Experimental results show that the estimation with Lomb-Scargle periodogram yield more accurate heart rate than the method of measuring peak-to-peak distance.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.290-295
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• 2016

This paper proposes a new method for the automatic detection of atrial fibrillation (AF), using Markov regime switching GARCH (1, 1) model. The proposed method is based on the observation that variability patterns of heart rate intervals during AF significantly differ from regular patterns. The proposed method captures the different patterns of heart rate intervals between two regimes : normal and AF states. We test the proposed method using Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) atrial fibrillation database, and demonstrate the effectiveness of the proposed method.