• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.9.1-9
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• 2001

Concerning the development of suitable healthcare equipment for a aged people at their homes in order to reduce the labor and increase the efficiency in the homehelpers' work, we conducted a study on the actual conditions of healthcare in Kyoto city (healthcare in taking a meal and excretion, moving and taking a bath by using a hand-powered lift, moving by a wheelchair, shower carrier healthcare, assistance in body care and housework) by digital video filming, interviews and layout investigations. On the base of those investigations by using methods for analysis of video pictures, we divided the healthcate work into scenes and e exctracted the main problems in terms of health care equipment, information, environment, healthcare skills, mental burden, social s system, family burden, ete. Furthermore the questionnaire survey of home helpers (18 persons - 50% answers) clarified that more than half of them have lumbago pains and the biggest load in the everyday healthcare c comes from moving the patients or getting them into or out of t the equipment for moving. Finally we considered concrete proposals appropriate for each h healthcare scene image, based on evaluation toward efficiency (design guidelines) for suitable healthcare equipment for aged people at their homes: 1) Design toward a proper posture 2) Design toward self-help possibility 3) Design toward patient active participation 4) Design toward rationality of the whole process 5) Design toward place-appropriate healthcare equipment 6) Design toward healing of mind 7) Good level of healthcare skills 8) Economic, systematic rationality

• 전기의세계
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• v.53 no.9
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• pp.30-35
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• 2004

초고속 인터넷 기술과 무선 통신망의 발달로 다양한 데이터(video, audio 및 biological data)들을 지원할 수 있는 멀티미디어 시스템의 구현이 가능해짐에 따라 환자의 상태나 요구에 맞추어 효과적인 진료 및 질병 예방을 가능할 수 있게 되었다. U-healthcare 시스템이란 무선 인터넷과 단말기를 생체 계측기와 융합시켜 시간적, 공간적인, 계측장치 제약 없이 환자의 질병관리가 가능한 시스템을 말한다.(중략)

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.281-282
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• 2019

In recent years welfare of animals is the biggest challenge because animals, especially dogs are widely recognized as pet as well as they are using as service animals. So, for the wellbeing of the dog it is necessary to perform objective assessment to track their behavior in everyday life. In this paper, we have proposed an automatic behavior assessment system for dogs based on a neck worn and tail worn accelerometer and gyroscope platform, and data analysis techniques that recognize typical dog activities. We evaluate the system based on the analysis of 8 behavior traits in 3 dogs, incorporating 2 breeds of various sizes. Our proposed framework able to reproduce the manual assessment that is based on the video recording which is treated as gold standard that exhibits the real-life use case of automated dog behavior analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2016-2034
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• 2011

Ubiquitous Healthcare (u-Healthcare) is the intelligent delivery of healthcare services to users anytime and anywhere. To provide robust healthcare services, recognition of patient daily life activities is required. Context information in combination with user real-time daily life activities can help in the provision of more personalized services, service suggestions, and changes in system behavior based on user profile for better healthcare services. In this paper, we focus on the intelligent manipulation of activities using the Context-aware Activity Manipulation Engine (CAME) core of the Human Activity Recognition Engine (HARE). The activities are recognized using video-based, wearable sensor-based, and location-based activity recognition engines. An ontology-based activity fusion with subject profile information for personalized system response is achieved. CAME receives real-time low level activities and infers higher level activities, situation analysis, personalized service suggestions, and makes appropriate decisions. A two-phase filtering technique is applied for intelligent processing of information (represented in ontology) and making appropriate decisions based on rules (incorporating expert knowledge). The experimental results for intelligent processing of activity information showed relatively better accuracy. Moreover, CAME is extended with activity filters and T-Box inference that resulted in better accuracy and response time in comparison to initial results of CAME.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.480-481
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• 2018

이 논문은 발목에 만성적인 불안정성을 가진 환자의 발목을 재사용하는 것을 방지하기 위한 것이다. 이를 위해 발목의 안쪽 굽힙과 바깥쪽 굽힘의 각도가 측정된다. 각도가 규정 된 범위 내에 있고 환자가 통증을 호소하지 않으면 정상으로 간주한다. 그러나 각도가 규정 된 범위를 벗어나서 환자가 통증을 호소하는 경우 이상이 있는 것으로 간주되어 이상 증상에 대한 치료가 필요할 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1118-1133
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• 2017

Computer vision-based human activity recognition (HAR) has become very famous these days due to its applications in various fields such as smart home healthcare for elderly people. A video-based activity recognition system basically has many goals such as to react based on people's behavior that allows the systems to proactively assist them with their tasks. A novel approach is proposed in this work for depth video based human activity recognition using joint-based motion features of depth body shapes and Deep Belief Network (DBN). From depth video, different body parts of human activities are segmented first by means of a trained random forest. The motion features representing the magnitude and direction of each joint in next frame are extracted. Finally, the features are applied for training a DBN to be used for recognition later. The proposed HAR approach showed superior performance over conventional approaches on private and public datasets, indicating a prominent approach for practical applications in smartly controlled environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.678-679
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• 2022

In this paper, information on ankle instability will be acquired and processed by selecting the area of flexion of the ankle among a diverse range of areas of the Healthcare System. In addition, re-damaging of patient's ankle will be prevented on the basis of such information. Moreover, the system of automatically measuring and managing the angles of dorsiflexion and plantarflexion of the ankle by using video will be presented in this System.

• Journal of Web Engineering
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• v.21 no.5
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• pp.1671-1690
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• 2022

Human activity recognition (HAR) is a key technology in many applications, such as smart signage, smart healthcare, smart home, etc. In HAR, deep learning-based methods have been proposed to recognize activity data effectively from video streams. In this paper, the end-to-end model based on convolutional long short-term memory (LSTM) is proposed to recognize human activities. Convolutional LSTM can learn features of spatial and temporal simultaneously from video stream data. Also, the number of learning weights can be diminished by employing convolutional LSTM with an end-to-end model. The proposed HAR model was optimized with various simulation environments using activities data from the AI hub. From simulation results, it can be confirmed that the proposed model can be outperformed compared with the conventional model.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.509-514
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• 2021

The pandemic of COVID-19 is driving the demand for non-face-to-face diagnosis, observation, and treatment in the healthcare environment, which has led to increased interest in helathcare robots. The authors intend to predict the direction in which the quarantine healthcare robots should be utilized in the post-corona era through analysis of national agency reports, on-offline press reports, and domestic and foreign robot company press releases. The COVID-19 pandemic has raised interest in medical robots. And there is a need to apply healthcare robots that can perform tasks such as disinfection, logistics transfer, screening tests, monitoring of patients, remote medical treatment support for isolated patients, and video calls with family members. Therefore, it is considered that future correct development and application of healthcare robots and empirical research to verify them should be continued based on sufficient consideration for various problems associated with the practical application of robots.

• The Korean Journal of Rehabilitation Nursing
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• v.16 no.1
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• pp.37-46
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• 2013

Purpose: This study was to identify the effects of a nurse-led education program using computerized animation video for post-operative colon cancer patients. Methods: a total of 163 patients and 51 nurses were participated in this study. With a non-equivalent control group post-test design, patients were divided into three groups (77 got traditional education, 46 were applying brochure, 40 were watching video). Twelve-item animation video and brochure about the management after discharge for post-operative colon cancer patients were developed based on patient survey and the items of Korea Healthcare Accreditation. Results: The computerized video watching group had better satisfaction than the others, but there was no significant difference about comprehension. When video was applied, satisfaction, usefulness, application, and perceived patients' comprehension of nurses were all increased. Conclusion: This video education program was developed by nurses and it had a special thing for patient to access the same program even after discharge using the authorization system. It would be helpful for nurses to be more concentrated on the direct care for hospitalized patients as well as for patients to provide self-care at home. This program would be adjusted into more various diseases and settings.