• 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.

• Journal of radiological science and technology
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• v.44 no.2
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• pp.123-131
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• 2021

In this study, safety education contents for medical radiation workers were produced based on Mixed Reality(MR). Currently, safety training for radiation workers is based on theory. This is insufficient in terms of worker satisfaction and efficiency. To address this, we created ICT(Information and Communication Technologies)-based MR radiation worker safety education content. The expected effect of Mixed Reality worker safety education content is that education is possible without space and time constraints, realistic education is possible without on-site training, and interaction between images is possible through reality-based 3D images, enabling self-directed learning Is that. In addition, learning in a virtual space expressed through HMD(Head Mounted Display) is expected to make education more enjoyable and increase concentration, thereby increasing the efficiency of education. A quantitative evaluation was conducted by an accredited institution and a qualitative evaluation was performed on users, which received excellent evaluation. The MR safety education conducted in this study is expected to be of great help to the education of medical radiation workers, and is expected to develop into a new educational paradigm as online education in accordance with Corona 19 progresses.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.569-572
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• 1998

In this paper, we devised pulse rate diagnosis for provide basic index of cold-hot diagnosis. The system consist of database part and pulse rate detection part for detection pulse wave, respiration and ECG. The database is constructed windwos95 platform using DAO(data access object). Search algorithm used ISAM algorithm. The database consist of one's information and medical report for a subject and detected pulse wave.

• Annual Conference of KIPS
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• 2017.11a
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• pp.778-780
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• 2017

현재 메신저 플랫폼을 기반으로 한 챗봇 서비스의 등장으로 앱에서 봇으로 ICT 생태계는 급속히 진화를 전망하고 있다. 현재 챗봇은 클라우드 기반의 오픈소스 플랫폼으로 구축되어 있어 대부분이 서비스로 제공된다. 이를 활용해 개발자들이 어플리케이션을 손쉽게 개발할 수 있다. Facebook 메신저를 활용한 챗봇 기반 전문의료 상담 및 예약 플랫폼으로, 사용자는 병원 방문 없이 단순한 키워드, 혹은 문장검색만으로 병명을 알 수 있다. 또한, 병명과 관련하여 사용자 위치 주변의 병원을 손쉽게 검색 예약할 수 있다.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1398-1404
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• 2018

High-performance computing (HPC) provides to researchers a powerful ability to resolve problems with intensive computations, such as those in the math and medical fields. When an HPC platform is provided as a service, users may suffer from unexpected obstacles in developing and running applications due to restricted development environments and dependencies. In this context, operating system level virtualization can be a solution for HPC service to ensure lightweight virtualization and consistency in Dev-Ops environments. Therefore, this paper proposes three types of typical HPC structure for container environments built with HPC container and Docker. The three structures focus on smooth integration with existing HPC job framework, message passing interface (MPI). Lastly, the performance of the structures is analyzed with High Performance Linpack benchmark from the aspect of performance degradation in network communications under Docker.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1207-1212
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• 2018

The ultrasound image uses ultrasonic pulses to receive the reflected waves and construct an image necessary for diagnosis. At this time, when the signal becomes weak, noise is generated and a slight difference in brightness occurs. In addition, fluctuation of image due to breathing phenomenon, which is the characteristic of ultrasound image, and change of motion in real time occurs. Such a noise is difficult to recognize and diagnose visually in the analysis process. In this paper, morphological features are automatically extracted by using image processing technique on ultrasound acquired images. In this paper, we implemented a GPU - based fast filter using a cloud big data processing platform for image processing. In applying the GPU - based high - performance filter, the algorithm was run with performance 4.7 times faster than CPU - based and the PSNR was 37.2dB, which is very similar to the original.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.4
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• pp.40-50
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• 2019

In recent years, it is important to visualize an accurate human body model for the low-end system in the medical imaging field where augmented reality technology and virtual reality technology are used. Decreasing the geometry of a model causes a difference from the original shape and considers the difference as an error. So, the error should be minimized while reducing geometry. In this study, the organ areas of a human body in the tomographic images such as CT or MRI is segmented and 3D geometric model is generated, thereby implementing the reconstruction method of multiple resolution level-of-detail model. In the experiment, a virtual reality platform was constructed to verify the shape of the reconstructed model, targeting the spine area. The 3D human body model and patient information can be verified using the virtual reality platform.

• Journal of Platform Technology
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• v.12 no.2
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• pp.23-33
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• 2024

The development of mixed reality (MR) technology has a great influence on the research and development of medical support equipment. In particular, it supports to respond effectively to emergencies occurring in the field. MR technology enables access to first aid and field support by combining virtual information with the real world so that users can see virtual objects in the real world. However, due to the nature of the equipment, there is a limitation in accurately matching virtual objects based on user vision. To improve these limitations, this paper proposes a 3D biometric object recognition and matching algorithm in the MR environment. As a result of the experiment, when a virtual object is rendered and visualized while equipped with an optical-based HMD from the user's side, it was possible to reduce the user's field of view error and eliminate the joint-loss phenomenon during skeleton recognition. The proposed method can reduce errors between the real user's field of view and the virtual image and provide a basis for reducing errors that occur in the process of virtual object recognition and matching. It is expected that this study will contribute to improving the accuracy of the telemedicine support system for first aid.

• Journal of the Korea Society of Computer and Information
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• v.17 no.7
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• pp.97-106
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• 2012

Management of biosignal data in mobile devices causes many problems in real-time transmission of large volume of multimedia data or storage devices. Therefore, this research paper intends to suggest an m-Health system, a clinical data processing system using mobile in order to provide quick medical service. This system deployed health system on IP network, compounded outputs from many bio sensing in remote sites and performed integrated data processing electronically on various bio sensors. The m-health system measures and monitors various biosignals and sends them to data servers of remote hospitals. It is an Android-based mobile application which patients and their family and medical staff can use anywhere anytime. Medical staff access patient data from hospital data servers and provide feedback on medical diagnosis and prescription to patients or users. Video stream for patient monitoring uses a scalable transcoding technique to decides data size appropriate for network traffic and sends video stream, remarkably reducing loads of mobile systems and networks.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.207-212
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• 2018

As a data analysis tool which is becoming popular in the Big Data era, R is rapidly expanding its user range by providing powerful statistical analysis and data visualization functions. Major advantage of R is its functional scalability based on open source, but its scale scalability is limited, resulting in performance degrades in large data processing. RHadoop, one of the extension packages to complement it, can improve data analysis performance as it supports Hadoop platform-based distributed processing of programs written in R. In this paper, we evaluate the validity of RHadoop by evaluating the performance improvement of RHadoop in real medical big data analysis. Performance evaluation of the analysis of the medical history information, which is provided by National Health Insurance Service, using R and RHadoop shows that RHadoop cluster composed of 8 data nodes can improve performance up to 8 times compared with R.