• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.151-155
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• 2019

Recently heart attack is 80% of the sudden death of elderly. The causes of a heart attack are complex and sudden, and it is difficult to predict the onset even if prevention or medical examination is performed. Therefore, early diagnosis and proper treatment are the most important. In this paper, we show the accuracy of normal and abnormal classification with neural network using weighted fuzzy function for accurate and rapid diagnosis of myocardial infarction. The data used in the experiment was data from the UCI Machine Learning Repository, which consists of 14 features and 303 sample data. The algorithm for feature selection uses the average of weight method. Two features were selected and removed. Heart attack was classified into normal and abnormal(1-normal, 2-abnormal) using the average of weight method. The test result for the diagnosis of heart attack using a weighted fuzzy neural network showed 87.66% accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.326-330
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• 2012

In 2011, There were about 25,000 people died because of heart disease. The aim of this paper is to design a heart attack situation monitoring and spreading system for patients. Wearable computer with a sensor is used to monitor heart rate. Heart rate is transffered to smartphone with bluetooth. After analyzing heart rate, smartphone spread out the emergency situation by various service including emergency call, SNS and SMS.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.77-88
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• 2021

Heart Failure represents a critical pathological case that is challenging to predict and discover at an early age, with a notable increase in morbidity and mortality. Machine Learning and Neural Network techniques play a crucial role in predicting heart attacks, diseases and more. These techniques give valuable perspectives for clinicians who may then adjust their diagnosis for each individual patient. This paper evaluated neural network models for heart attacks predictions. Several online learning methods were investigated to automatically and accurately predict heart attacks. The UCI dataset was used in this work to train and evaluate First Order and Second Order Online Learning methods; namely Backpropagation, Delta bar Delta, Levenberg Marquardt and QuickProp learning methods. An optimizer technique was also used to minimize the random noise in the database. A regularization concept was employed to further improve the generalization of the model. Results show that a three layers' NN model with a Backpropagation algorithm and Nadam optimizer achieved a promising accuracy for the heart attach prediction tasks.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.242-249
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• 2019

Old people and patients with cardiovascular disease could die of a heart attack in the bath with heated water for a long time. Various researches have been studied to prevent these accidents from happening such as measuring the ECG signal when taking bath. However, these devices are hard to use and the higher price is not easily accepted by the public. In this paper, a low-cost and use-friendly, real time high precision water temperature monitoring device to prevent heart attack in the bath was developed. The device with waterproof design that lets the device can float on the surface of the water, and an accurate way to make water temperature measurement method was proposed by this paper that is immerging the sensor into water with 4cm depth to measure the temperature of underwater. The manufactured device was conducted to two experiments; one was to verify the basic functions of the device, and another one was for compare the proposed device with commercial products for monitoring the water temperature in the bathtub. As the experimental results shown, the proposed device has stable performance for the water temperature measurement and communicating with laptop in wireless.

• The Korean Nurse
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• v.22 no.5 s.123
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• pp.33-40
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• 1983

• Journal of Oriental Neuropsychiatry
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• v.16 no.2
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• pp.1-11
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• 2005

Objective : This study was to evaluate the clinical improvement of Panic attack and Anticipatory anxiety on Panic Disorder patients after Oriental medical treatment. Methods : We compared post-treatment with pre-treatment on Panic attack and Anticipatory anxiety with Thirty eight Panic Disorder patientsafter Oriental medical treatment - acupunture, herbal medicine, oriental psychotherapy. Results and Conclusions : 1. Foremost herbal medicines were Siwuanshentang(四物安神揚)(39.47%), Qingxinwendantang(情心溫膽揚)(13.16%). Types of demonstration weredeficiency of the heart blood(心血不足)(39.47%), deficiency of qi and blood in the heart and spleen(心脾兩虛)(28.95%), timidity die to insufficiency of qi and deficiency of blood of the heart(心脫虛法)(15.79%), stagnation of phlegm(痰獨阻滯)(13.16%), deficiency of liver-yin and kidney-yin(肝腎陰虛)(2.63%) in order. 2. The physical constitutions in Thirty eight Panic Disorder patients weretwenty nine of Taiyinren(76.3%),six of Shaoyinren(15.8%), three of Shaoyangren(7.9%) in order. 3. This oriental medical treatment was effective in Panic attack from $7.68{\pm}0.87$ to $2.68{\pm}1.613$ and in Anticipatory anxiety from $7.47{\pm}1.006$ to $2.47{\pm}1.841$ in comparison post-treatment with pre-treatment. 4. A percentage of subjective improvement was 72.6%. There were 18.4% in the same, 15.8% in slight improvement, 18.4% in medium improvement, 47.4% in remarkable improvement.

• YAKHAK HOEJI
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• v.51 no.5
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• pp.336-342
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• 2007

Treatment of hypertension is important in reducing death and attack rates by Ischemic heart disease (IHD). The purposes of this study are to investigate recent prescriptions for patients with IHD and to evaluate antihypertensive drug use. On the basis of the guidelines proposed by Seventh Report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure, we analyzed prescriptions of antihypertensive drugs for patients with IHD. It is necessary to set up new guideline for appropriate treatment to lower death and attack rates for patients with IHD.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.269-275
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• 2022

Public healthcare has recently become an issue of great importance due to the exponential growth in the human population, the increase in medical expenses, and the COVID-19 pandemic. Speed is one of the crucial factors in saving life, particularly in case of heart attack. Therefore, a healthcare device is needed to continuously monitor and follow up heart health conditions remotely without the need for the patient to attend a medical center. Therefore, this paper proposes a portable electrocardiogram (ECG) monitoring system to improve healthcare for heart attack patients in both home and ambulance settings. The proposed system receives the ECG signals of the patient and sends the ECG values to a MySQL database on the IoT-cloud via Wi-Fi. The signals are displayed as an ECG data chart on a webpage that can be accessed by the patient's doctor based on the HTTP protocol that is employed in the IoT-cloud. The proposed system detects the ECG data of the patient to calculate the total number of heartbeats, number of normal heartbeats, and the number of abnormal heartbeats, which can help the doctor to evaluate the health status of the patient and decide on a suitable medical intervention. This system therefore has the potential to save time and life, but also cost. This paper highlights the five main advantages of the proposed ECG monitoring system and makes some recommendations to develop the system further.

• Journal of Korean Public Health Nursing
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• v.31 no.2
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• pp.272-283
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• 2017

Purpose: This descriptive study compared changes in life style and health perceptions before and after the onset of coronary heart disease in 100 patients. Methods: Data were from May to July in 2016 through questionnaires and medical records. The collected data were analyzed by a $x^2$ test, and paired t-test using SPSS 12.0. Results: After the onset of heart disease, significant decreases were observed in smoking ($x^2=17.21$, p<.001) and drinking ($x^2=43.56$, p<.001), while exercise increased significantly ($x^2=32.77$, p<.001). Appetite, stress and health state were significantly decreased after the onset of heart disease (t=3.18, p=.002, t=3.55, p=.001, t=4.43, p<.001), and knowledge about disease was significantly increased after the onset of heart disease (t=-13.66, p<.001). Conclusion: The results of this study indicate that continuous follow-up management programs including smoking and drinking cessation, exercise, appetite and stress management should be developed and implemented for Coronary Heart Disease with PCI.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1141-1148
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• 2016

This paper proposed a heart attack predictive monitoring system using QRS pattern of ECG for wearable healthcare. It detects abnormal heart pattern with a ECG (X, Y) coordinate pattern DB on wearable monitoring smart watch. We showed the acute heart failure prevention system and method with a proposed scheme. Especially, It proved the method which can do first aid in gold time through abnormal heart analysis with a digital ECG(X, Y) pattern information when acute heart failure occurs.