• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.4
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• pp.835-840
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• 2008

Acupuncture has long been contended to be effective in an ischemic stroke. A real-time monitoring of glutamate, an excitotoxin in the process of ischemic neuronal damage, in the striatum is tried in a rat model of global ischemia. Global ischemia was induced by the 11 vessel occlusion method for 10 minutes, during which acupuncture stimulation on GB34 and GB39 points was executed. Glutamate release in the rat striatum was monitored 256 times per second using real-time amperometric biosensor. Real time measurement data of 10 minutes prior to the induction of ischemia served as baseline data. Data acquisition continued for 30 minutes after the initiation of reperfusion. Peak concentration of glutamate release along with incidentally measured EEG and cerebral blood flow was compared between cases with and without acupuncture stimulation. Peak concentration of glutamate lowered when acupuncture stimulation was executed. A real time monitoring system of 11 vessel-occlusion induced global ischemia model was successfully established. The effect by acupuncture on acute global ischemia was successfully observed in this real-time monitoring setting, which may be one of the neuroprotective mechanism of acupuncture.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.57-66
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• 2014

This paper proposes the UHISRL(Ubiquitous Healthcare Information System based on Real Time Location) which manages patient, doctor, medicine by using RFID. The proposed UHISRL monitors the patient's health state, and enables us to confirm the result with Smart Phone and Tablet PC. Also, it can block Replay and Spoofing attack by using the ERHL(Extended Randomized Hash Lock) authentication scheme designed in this paper. A patient privacy is enhanced by limiting UHISRL DB access according to attributes with CP-ABE (Cipher Text - Attributed based Encryption) technique. Specially, UHISRL can prevent an unexpected accident by monitoring a chronic patient's emergency situation in real time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3A
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• pp.279-286
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• 2010

Although seaman has made a contribution marine transportation and the marine products industry, the current status of preventing occupational disease by monitoring health danger factors is very unsatisfied. Therefore, a monitoring system regarding health condition and disease occurrence of seaman is required. In this paper, we propose a real-time sailor management system based on uniqutious healthcare, which collects various organic signals and analyzes their relation in order to confirm blood pressure, temperature and pulsation of seaman. The proposed system enables a medical doctor to manage the diseases anywhere at any time even via a PC and PDA.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.905-914
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• 2005

This paper suggests a healthcare home service system based on the distributed object group framework that can not only provide healthcare application services using the information obtained from the physical healthcare sensors and devices, and but also monitor and control these services remotely. The distributed object group framework supports the object group service, the interaction service between object groups and the real-time service in order to execute the healthcare application. Here object group means the unit of logical grouped objects or healthcare sensors and devices for a service. Our suggested system consists of 3 layers. The first layer presents the physical sensors and devices for healthcare, as a physical layer. The second layer lays the distributed object group framework, and the third layer, the upper's one, implements healthcare applications based on lower layers. With healthcare applications providing for this system, we implemented the location tracking service, the health information service and the titrating environment service. Also the integrated executing results of these services can be monitored and controlled via remote desktop systems or PDAs.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.282-292
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• 2007

In this paper, we propose the active model based on the distributed object group framework which provides adaptive information sharing service to support it to various Healthcare home service. And we applied it to Healthcare home service. This proposed model provides information that collected from physical environment of the home network and sensors for healthcare service according to situation of the user. We uses information of the healthcare information database which was constructed previously, and we uses TMO scheme for to solve each other different periodic qualify. We uses information of the healthcare information database which was constructed previously, and we uses TMO scheme for to solve each other different periodic quality. Specialty, We wrote about interaction of various Healthcare Home services for adaptive information services, and wrote about u-healthcare framework based on DOGF. Finally, we apply active model to healthcare monitoring service, and we showed its result and performance evaluation.

• Journal of Convergence Society for SMB
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• v.6 no.4
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• pp.79-84
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• 2016

A novel diagnosis scheme PCADP(personalized computer aided diagnosis probability) is proposed to overcome the problems mentioned above. PCADP scheme is a personalized diagnosis method based on ontology and it makes the bio-data analysis just a 'process' in the Smart healthcare service system. In addition, we offer a semantics modeling of the smart healthcare ontology framework in order to describe smart healthcare data and service specifications as meaningful representations based on this PCADP. The PCADP scheme is a kind of statistical diagnosis method which has real-time processing, characteristics of flexible structure, easy monitoring of decision process, and continuous improvement.

• Journal of the Korean Applied Science and Technology
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• v.37 no.1
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• pp.76-82
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• 2020

Big data analysis in healthcare research seems to be a necessary strategy for the convergence of sports science and technology in the era of the Fourth Industrial Revolution. The purpose of this study is to provide the basic review to secure the diversity of big data and healthcare convergence by discussing the concept, analysis method, and application examples of big data and by exploring the application. Text mining, data mining, opinion mining, process mining, cluster analysis, and social network analysis is currently used. Identifying high-risk factor for a certain condition, determining specific health determinants for diseases, monitoring bio signals, predicting diseases, providing training and treatments, and analyzing healthcare measurements would be possible via big data analysis. As a further work, the big data characteristics provide very appropriate basis to use promising software platforms for development of applications that can handle big data in healthcare and even more in sports science.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.267-270
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• 2009

Researches of U-Healthcare have been fulfilled lively with an advanced age and change of lifestyles. Especially, medical field has focused on researches of U-Healthcare due to that reasons. The U-Healthcare service requires the foundation technologies, such as sensor aggregating, data transmitting and realtime monitoring technologies, In this study, we implemented medical sensor that applied Bluetooth technology to guarantee the patient's movement. Moreover, we also implemented a gateway which based on Google Android System in ARM 11 Embedded system.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.328-330
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• 2004

In this paper, ECG based cardiac disease diagnosis models are developed. Conventionally, ECG monitoring equipments can only measure and store ECG signals and they always require medical doctor's diagnosis actions which are not desirable for continuous ambulatory monitoring and diagnosis healthcare systems. In this paper, two kinds of neural based self cardiac disease diagnosis engines are developed and tested for four kinds of diseases, sinus bradycardia, sinus tachycardia, left bundle branch block and right bundle branch block. For diagnosis engines, error backpropagation neural network (BP) and probabilistic neural network (PNN) were applied. Five signal features including heart rate, QRS interval, PR interval, QT interval, and T wave types were selected for diagnosis characteristics. To show the validity of proposed diagnosis engine, MIT-BIH database were used to test. Test results showed that BP based diagnosis engine has 71% of diagnosis accuracy which is superior to accuracy of PNN based diagnosis engine. However, PNN based diagnosis engine showed superior diagnosis accuracy for complex-disease diagnoses than BP based diagnosis engine.

• The Magazine of the IEIE
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• v.31 no.1
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• pp.58-72
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• 2004

Smart sensors and biochip technologies have received a great deal of attention in recent years not only because of the enormous potential markets in the healthcare expenditures but more importantly because of its great impact on the quality of human life in the future. Collaborative research among BT (Bio Technologies), IT (Information Technologies) and NT (Nano Technologies) will bring us a new paradigm of the healthcare services. Examples include disease prediction based on the genetic tests, personal medicines, point-of-care analysis, rapid and sensitive infectious disease diagnostics, environmental monitoring for chemical or biological warfares, intelligent drug delivery systems etc. In this report, recent accomplishment in the research area on biosensors, DNA chips, Protein Chips and Lab-on-a-chips are reviewed.