• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.625-632
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• 2014

The u-health service is using portable device such as smart device and it consists of small computing device. The u-health service carry out same performance with desktop computer. We designed message structure based on Bluetooth HDP. This message structure is used to transmit patient's biometric data on the smart device of medical team, patient and family over the mobile network environment. ISO/IEEE 11073 PHD standard was defined based on the method of communication between the agent and the manager. And We are confirmed the reliable transmission of biometric data at the smart device by implementing the android OS based patient information monitoring application to check the status of patient for medical team, patient and family.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.862-865
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• 2013

The smartphone digs deep into our lives, is changing our life. With increases the penetration of smart phones, it getting better performance. In recent years, tend to increase its utilization by an increase in the prevalence of smart phones equipped with NFC short-range wireless communication technology based on RFID in a number of areas, including e-cards, tagging. In this paper, we implement a system that can operate the system by traditional saddlecloth way of waiting waiting waiting standby system more efficient by applying NFC.

• Journal of the Korean Society of Radiology
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• v.10 no.1
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• pp.59-64
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• 2016

The purpose of this study intend to develop the automatic voice system for language communicating over foreign patients in testing of magnetic resonance imaging. Used sentences for the automatic voice system was selected with twelve sentences and five foreign languages in hospital in use. These translated texts were provided free of charge from Oddcast's website, which is recorded each language-specific voice as Wav files, The recorded audio file were produced by the two types of a power-point show of MS-office 2013(extension; ppsx) form and Web-enabled system using the PHP program to be applied in the mobile phone environment. It is considered to relieve the stress about an language barrier to medical technician and the voice system designed with the variable language will be enhanced the diagnostic information on foreign patients. Because automatic voice system designed for this study can enhance the understanding of test in between korean medical technician and foreign patients, It will be expected to utilize more usefully in clinical practice.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.283-285
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• 2013

본 논문에서는 헬스케어 시스템 제공업체와 소비자 모두 스마트폰 헬스케어를 향상시킬 도구로 수용할 수 있고 ISO/IEEE11073, HL7 표준을 적용한 홈 헬스케어 시스템을 제안하고자 한다. 이 시스템은 표준 기반의 홈 헬스케어 게이트웨이 플랫폼의 중요성이 부각되는 홈 헬스케어에서 건강측정을 위하여 가장 많이 사용되는 혈당계, 혈압계, 심박측정계, 산소포화도 측정계, 심전도 측정계 등의 홈 헬스케어 의료기기를 제안하였다. 아울러, 표준 핵심 기술 요소인 ISO/IEEE 11073, HL7을 준용하는 게이트웨이 플랫폼을 스마트폰에 적용하여 PMG(personal mobile gateway) 기반의 홈&모바일 헬스케어 시스템이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.410-412
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• 2008

본 논문에서는 의료기관내 이기종 시스템(OCS, PACS, EMR 등) 및 외부 기관(타 의료기관, 정부기관 등)과의 원활한 의료정보 공유를 위한 Framework을 제시하고자 한다. 의료기관 내/외부의 이질적인 Legacy System 간의 자료 교환을 위하여 현재 범용적으로 사용되는 HL7 Messaging standards를 기반으로 정보를 생성 공유하게 한다. 또한, HL7 Message 생성시 표현기법이 다른 데이터들을 HL7 표준에 해당하는 데이터로 자동 변환시킬 수 있는 방안을 제시하고, 이렇게 모인 의료정보를 다기종 Platform(PC, Mobile phone 등)에서 효율적인 접근을 위한 모델도 함께 제시한다.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.59-65
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• 2016

The result of analyzing the cognitive reaction due to the color environment has been applied to various filed especially in medical field. Moreover, the study about the identification of patient's condition and examination the brain activity by collecting the bio-signal based on the color environment is being actively conducted. Even though, there were a variety of experiments by convention the color environment using a light or LED color, it still has a problem that affects the psychological information. Therefore, our proposed system using a HMD (Head Mounting display) to provide a completed color environment condition. This system uses the BMS(Biomedical System) to collect the biometric information which responds to the specific color condition and the human body response information can be measured by the development the Memory and Attention test on Mobile phone. The collection of Biometric information includes electro cardiogram(ECG), respiration, oxygen saturation (Sp02), Bio-impedance, blood pressure will store in the database. In addition, we can verify the result of the human body reaction in the color environment by Memory and Attention application. By utilizing the reaction of the human body information that is collected thought the proposed system, we can analyze the correlation between the physiological information and the color environment. And we also expect that this system can apply to the medical diagnosis and treatment. For future work, we will expand the system for prediction and treatment of Alzheimer disease by analyzing the visualization data through the proposed system. We will also do evaluation on the effectiveness of the system for using in the rehabilitation program.

• Korean Journal of Artificial Intelligence
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• v.8 no.2
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• pp.1-5
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• 2020

Children's home accidents are less common than in the past. However, safety accidents continue to occur due to carelessness of the parents. To solve the problem, there are fall prevention screens that can withstand the weight of children, and safety railings that can be adjusted directly to solve the problem. However, these have disadvantages such as stability, convenience, and damage to the landscape. In this paper, we developed an automatic safety accident prevention fence system that can be installed on a window using Arduino, eliminating the disadvantages of previous safety accident prevention products. This system measures the height of a person standing in front of the fence and the distance between the person and the fence with two infrared sensors and moves automatically using a motor. In addition, in accordance with the U-Healthcare society, users can check the temperature, humidity, and fine dust concentration of the external environment through mobile. Each information can be obtained through DHT 11 sensor, fine dust concentration sensor, and Bluetooth connected toArduino. These can help the user's health care.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.542-547
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• 2014

This paper describes the medical and IT convergence system using a smart phone and a heuristic method for the measurement of the dripping speed of the liquid in a drip chamber, which can estimate the remaining time using pattern recognition and difference image from video frame information based on Android technology. The video frames were first made using a smartphone camera and we calculated the difference image between the n image and the (n-1) image and then changed into binary images using the threshold value. At this point, it is very important to find an optimal threshold value using heuristic method to recognize the dripping of the liquids. In addition, the user can adjust the dripping speed according to the doctor's prescription, exactly like watching the progress bar of a mobile application. The experiment results show that our method using video processing technique accurately measures the dripping speed for a wide range of speeds that are sufficient for ordinary practice.

• Journal of The Korean Association of Information Education
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• v.11 no.2
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• pp.139-146
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• 2007

Today, using RFID(Radio Frequency Identification) card is extended in diversity as medical treatment, circulation market, military affairs, manufacture, security, etc. The RFID technology is an automatic identification method, relying on storing and remotely retrieving data for the purpose of identification using radio waves. This advantage of the RFID will be as a replacement for traditional Barcoding. Besides, book-lending system and attendance management system become the center of educational institution in interest. This paper presents a attendance management system using the RFID card which provides directly information of attendance for professors with mobile and students with web. Also, the students only have ID card that embed RFID tag which is recognized attendance through DB that storages to is received a information of student from RFID card Reader. And it is possible management or report for attendance and time table not only for professors by management program but also for students by web program.