• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.25-31
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• 2005

We know that the Hurst Exponent (HE) is a real number in [0, 1] which denotes randomness of time series. in this research, we suggest non-linear analysis of human biological signals through HE. The feasibility of human biological signals using inductive incitement provides Some diagnosis for active treatment. In our experiment, we measured the heartbeat through the MCG, 29 healthy and 34 abnormal subjects ostensibly. The raw data of acupuncture incitement are supported by opinions of gross examination and pathological diagnosis. The mean values of HE are 0.345, 0.755 and 0.805 for the periods of before, during and after acupuncture treatment, respectively in case of abnormal subjects. On the other hand, the mean values, 0.808, 0.797 and 0.785 are for normal cases, correspondingly. From this data, we show that HE is very significant in abnormal controls according to an acupuncture incitement, and the incitement effect is evidently extracted in abnormal subjects. But, in normal subjects, the incitement effect is meaningless.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.200-207
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• 2014

Arrhythmia electrocardiogram signal contains a specific unusual heartbeat with abnormal morphology. Because unusual heartbeat is useful for diagnosis and classification of various diseases, such as arrhythmia, detection of unusual heartbeat from the arrhythmic ECG signal is very important. Amplitude and kurtosis at R-peak point and RR interval are characteristics of ECG signal on R-wave. In this paper, we provide a method for detecting unusual heartbeat based on these. Through the value of the attribute deviates more from the average value if unusual heartbeat is more certainly, the proposed method detects unusual heartbeat in order using the mean and standard deviation. From 15 ECG signals of MIT-BIH arrhythmia database which has R-wave distortion, we compare the result of conventional method which uses the fixed threshold value and the result of proposed method. Throughout the experiment, the sensitivity is significantly increased to 97% from 50% using the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.731-739
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• 2015

In arrhythmia ECG signal, abnormal beat that has various abnormal shape depending on the generation site and conduction disorders is included and it is very important to diagnose heart disease such as arrhythmia. In this paper, we propose a PVC abnormal beat detection algorithm associated with ventricular disease. The PVC abnormal beat is characterized by distortion of the QRS complex occurs among the components of the ECG signal. Therefore it is possible to detect PVC abnormal beat according to the degree of distortion of the QRS complex. First, quantify the distortion of the QRS complex by using the potential of the R-peak, kurtosis and period. By using the mean and standard deviation, PVC abnormal beat is detected depending on the degree of distortion from the normal beat. The proposed algorithm can detect the average over 98% of the AAMI-V class type abnormal beat associated with ventricular disease in MIT-BIH arrhythmia database.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.85-89
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• 2014

Electrocardiogram (ECG) is a diagnostic test which records the electrical activity of the heart, shows abnormal rhythms and detects heart muscle damages. With this ECG signal, medical centers diagnose patients' heart disease symptoms. A normal resting heart rate for adults rages from 60 to 100 beats a minute. An irregular heartbeat is called "arrhythmia", and arrhythmia is also called "cardiac dysrhythmia". In an arrhythmia, the heartbeat maybe too slow(slower than 60beats), too rapid(faster than 100beats), too irregular, etc. Among these symptoms of arrhythmia, if the heart beat is slower than the normal range, the symptom is called "bradycardia", and if it is faster than the range, it is called "tachycardia" In this letters, we proposed the detection algorithm of cardiac arrhythmia in ECG signal using R-R interval through the detection of R-peak.

• 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.

• Journal of Veterinary Clinics
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• v.14 no.1
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• pp.112-117
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• 1997

12-month-old Buldig and 3-year-old German Shepherd, treated with corticosteroids duringthe late pregnancy, were referred to the Veterinary Teaching Hospital, Chonnam National University, with chief complaints of vaginal discharge. Radiographic, ultrasonographic and surgical findings that obtained from each cases were as follows; case I: Radiographic findings were identified 2 fetuses that were normal skeleton, however, fetal viability could not be determined. Ultrasonographic findings were identified absence of fetal heartbeat and fetal movement, abnormal echogenicity of the abdominal visera, and echogenic materials remaining within the fetal fluid. After hysterotomy, macroscopic findings of uterus were liquefied materials remaining within the uterine lumen. Fetuses were excessively autolysis (falling off the hair, depression of the eye, and necrosis of the abdormal visera and skin). case II: Radiographic findings were identified irregular fetal structures and fetal movement, loss of recognizable fetal anatomy, dislocation of fetal veterbrae and echogenic materials remaining within the uterine lumen. After ovariohysterectomy, macroscopic finding of uterus and fetus were thickened uterine wall, yellowish-brown colored administration of corticosteroids during gestation should be contraindicated because fetal death is inducced. Ultrasonography has an advantage over radiography in that it permits evaluation of fetal viability.

• Journal of The Korean Society of Clinical Toxicology
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• v.17 no.2
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• pp.132-134
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• 2019

Green tobacco sickness is an illness caused by dermal exposure to nicotine. The common symptoms of the disease include dizziness, headache, nausea, vomiting, severe general weakness, fluctuations of blood pressure or heartbeat, abdominal cramping, chills, increased sweating, salivation, and difficulty breathing. A 79-year-old female arrived at the emergency room for an evaluation of sudden onset dizziness. Magnetic resonance imaging and angiography of the brain did not show any relevant abnormal findings. Four days later, with supportive care, she said that she had harvested green tobacco for six hours on the day of admission and the tobacco harvest was the first time in her life. She sweated excessively during the hot and humid weather and the tobacco leaves were wet from rain the night before. The serum cotinine tested at five days of admission was 16ng/ml. She was diagnosed with acute nicotine poisoning by her clinical symptoms and the half-life of cotinine in the blood.

• Biomedical Science Letters
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• v.25 no.3
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• pp.237-246
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• 2019

Left ventricular hypertrophy (LVH) refers to the expansion and the enlarged myocardium due to the increased resistance to ejection from the left ventricle to the aorta and/or the periphery, or the long-term burden imposed by the blood increase. Hypertension is a major risk factor that accounts for more than 50% of the causes of cardiovascular disease. If hypertension endure in the long term, the myocardium responds to abnormal heartbeat in the heart. Therefore, the prevalence of left ventricular hypertrophy also increases. As a result of genome-wide association study (GWAS) analysis for European people, PDGFC, MARK3, and BCL2 were related to blood pressures. In this study, the genetic polymorphisms of PDGFC, MARK3, and BCL2 were extracted and selected based on Korean genomic and epidemiologic data, and then logistic regression analysis was performed on LVH. As a result, one SNP (rs9307953) in PDGFC gene, four SNPs (rs6575983, rs17679475, rs2273703 and rs10141388) in MARK3 gene and two SNPs (rs17756073 and rs17070739) in BCL2 gene were statistically significant. The rs6575983 of the MARK3 gene showed the highest significance level ($P=7.2{\times}10^{-3}$) among the SNPs and the relative risk of 1.08 (95% confidence interval: 1.06 to 1.45). These results suggest that the polymorphisms of PDGFC, MARK3, and BCL2 not only affect European blood pressures but also correlate with LVH in Korean. These results suggest that increased understanding of the genetic correlations of the pathogenesis of LVH.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.37-43
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• 2020

Recently, many researches have been actively to diagnose symptoms of heart disease using ECG signal, which is an electrical signal measuring heart status. In particular, the electrocardiogram signal can be used to monitor and diagnose arrhythmias that indicates an abnormal heart status. In this paper, we proposed 1-D convolutional neural network for arrhythmias classification systems. The proposed model consists of deep 11 layers which can learn to extract features and classify 5 types of arrhythmias. The simulation results over MIT-BIH arrhythmia database show that the learned neural network has more than 99% classification accuracy. It is analyzed that the more the number of convolutional kernels the network has, the more detailed characteristics of ECG signal resulted in better performance. Moreover, we implemented a practical application based on the proposed one to classify arrythmias in real-time.

• 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.