• Journal of Korean Academy of Nursing
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• v.45 no.3
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• pp.439-448
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• 2015

Purpose: The purpose of this study was to examine validity and reliability of Webel and colleagues'HIV Self-Management Scale when used with a Korean sample. Methods: The original 20-item HIV Self-Management Scale was translated into Korean using translation and back-translation. Nine HIV nurse experts tested content validity. Principal component analysis (PCA) and confirmatory factor analysis (CFA) of data from 203 patients was used to test construct validity. Concurrent validity was evaluated using correlation with patients'self-rating as a "mart patient"measured using a visual analogue scale. Internal consistency was tested by Cronbach' alpha coefficients. Results: All items were rated as having satisfactory content validity. Based on PCA and consideration of conceptual meaning, a three-factor solution was selected, explaining 48.76% of the variance. CFA demonstrated the adequacy of the three-domain structure of the construct HIV self-management: daily self-management health practices, social support and HIV self-management, and chronic nature of HIV self-management. Goodness-of-fit indices showed an acceptable fit overall with the full model (${\chi}^2/df_{(164)}=1.66$, RMSEA=0.06, SRMR=0.05, TLI=0.91, and CFI=0.92). The Korean version of the HIV Self-Management Scale (KHSMS) was significantly correlated with patients'self-rated smart patient (r=.41). The subscale Cronbach' alpha coefficients ranged from .78 to .81; alpha for the total scale was .89. Conclusion: The KHSMS provides a valid and reliable measure of self-management in Korean patients with HIV. Continued psychometric testing is recommended to provide further evidence of validity with this population.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.378-387
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• 2018

With the advent of the fourth industrial revolution in recent years, the field of health care services is getting attention again. Accordingly, personalized medical systems through smart products are emerging in various forms. With the use of wearable tech and sensor system, health management and monitoring can be done anytime, anywhere without help of others. However, healthcare services for pregnant women are very scarce. Due to the low fertility rate the number of obstetrics and gynecology is decreasing and as a result, environment surrounding the uncomfortable pregnant women is getting worse. Pregnant women are unable to take a comfortable sleeping posture due to pregnancy. Various environmental factors such as noise, temperature and humidity decrease the quality of sleeping of pregnant women and hinder happy preaching. The purpose of this study is to develop a UI design that can manage sleeping by providing good sleeping posture information and improved sleeping environment for the health of pregnant women. We expect to apply the sensor technology of the 4th industrial age to maximize the sleep quality and quality of life of expectant mothers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2349-2354
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• 2006

Due to technological developments and the joint effect of both new social and economic needs and constraints, telemedicine is expanding rapidly through a variety of applications. Especially, owing to the rapid aging of society and increasing the wish for well being life, we take interest in health care services for people with special needs who wish to remain independent and living in their own home. We have focused on tole-monitoring to real-time medical signal and environment factor which is an influence on medical signal. We monitor the six signal(medical signal and environment factor), and transmit that signal to computer on bluetooth network. We get the information after using the some digital signal processing system, and display that information on the real-time monitoring system. We developed the measurer as portable type in older to non-restrained monitor.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.67-77
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• 2017

With the advent of the fourth industrial revolution, the digital transformation craze has intensified in diverse industries, such as finance, automotive, health care and agriculture. However, relative to industry demand, there is only few domestic research on digital transformation of small traders and no one has implemented empirical study on this field at all. Thus, the study conducted an empirical study to measure the digital transformation intention of domestic small traders. In the early days of domestic business start-ups, we searched for factors affecting the digital conversion intention of small business owners and designed an integrated framework to explain the causal relationship between factors. This study not only expanded and refined the scope of related research but also suggested the direction of another research that was not presented in previous research. However, there are limitations in many ways as much as the initial stage of a specific field of small business owners. There are limitations in explaining the overall perception of Korean small business owners. Therefore, in future studies, it is necessary to study more deeply by presenting more specific and various variables. In addition, although the number of respondents was sufficient in the process of empirical analysis, it is considered that the respondents are not enough to universalize the research result as a traditional small business person who did not convert all digital. It is necessary to carry out a comparative analysis by dividing the two groups in more detail and more specifically in the future study. The result of this study can suggest the direction for accelerating small traders' digital transformation intention in terms of practical view, and provide useful references which can support the theoretical foundation for researchers who will perform future related research in terms of academic view.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.686-697
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• 2017

Rapid growth in mobile communication and the proliferation of smart devices have drawn significant utilization of machine generated data. Behavior tracking technology now are utilized in the various fields based on extracting data using the sensor and device. We deploy IoT based behavioral intervention system in Suwon mental health center to improve the effectiveness of non-medicine care for senior people. Using smart activity trackers and BLE scanner devices, we proposed a location-based behavioral intervention system and verify the integrity of the harvested data.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.25-32
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• 2022

In this paper, we propose a pet monitoring system based on deep learning using an activity recognition device. The system consists of a pet's activity recognition device, a pet owner's smart device, and a server. Accelerometer and gyroscope data were collected from an Arduino-based activity recognition device, and the number of steps was calculated. The collected data is pre-processed and the amount of activity is measured by recognizing the activity in five types (sitting, standing, lying, walking, running) through a deep learning model that hybridizes CNN and LSTM. Finally, monitoring of changes in the activity, such as daily and weekly briefing charts, is provided on the pet owner's smart device. As a result of the performance evaluation, it was confirmed that specific activity recognition and activity measurement of pets were possible. Abnormal behavior detection of pets and expansion of health care services can be expected through data accumulation in the future.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.261-267
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• 2016

As IoT technology has gained the attention all around the world, the development for various services of healthcare, smart city, agriculture, and defense based on IoT is in progress. However, it is likely that healthcare services based on IoT have a problem of being leaked of patients' biological information by a third party and that risks patients' lives. In this paper, an IoT health care service managing model based on location sensor is proposed, which secures the biological information of a patient and simplifies the procedure to process the treatment and administration steps by using the data resources sensed. Even when an emergency occurs, this proposed model can respond quickly using the location information of the patient, which enables the staff in the hospital to locate the patient in real time. In addition, there is an advantage to minimize the time and the process of care, because the location of the equipment for necessary treatment is possible to be instantaneously located with attached sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.842-845
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• 2012

의료기기는 헬스케어 서비스를 위한 필수요소로 최근 의료와 관련된 스마트폰 애플리케이션의 증가와 함께 스마트폰과 연결되는 의료기기를 활용한 스마트 헬스케어가 대두되고 있다. 이러한 스마트 헬스케어는 현재 ISO/IEEE 11073 표준을 통해 의료기기와 게이트웨이를 연결하여 임상정보를 전송하고 게이트웨이는 HL7 CDA 표준 문서를 통해 전자 건강 기록 및 개인 건강 기록 시스템, 임상 워크플로우 및 임상 의사 결정 지원 시스템과 같은 유형의 의료 서비스 시스템과 연동하는 솔루션이다. ISO/IEEE 11073은 DIM(Domain Information Model)이라는 정보 모델을 기반으로 하며 HL7 v3인 CDA는 RIM(Reference Information Model)이 있기 때문에 상이한 인터페이스간의 매핑 매커니즘을 필요로 한다. 이에 본 논문에서는 스마트폰 환경에서 의료 응용 애플리케이션에서의 효율적인 의료기기 데이터 운용을 위해 RMIM(Refined Message Information Model) 기반의 IEEE 11073 DIM/HL7 v3 RIM 표준 인터페이스 변환 방법을 제안한다.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1857-1862
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• 2016

Human activity recognition using depth information is an emerging and challenging technology in computer vision due to its considerable attention by many practical applications such as smart home/office system, personal health care and 3D video games. This paper presents a novel framework of 3D human body detection, tracking and recognition from depth video sequences using spatiotemporal features and modified HMM. To detect human silhouette, raw depth data is examined to extract human silhouette by considering spatial continuity and constraints of human motion information. While, frame differentiation is used to track human movements. Features extraction mechanism consists of spatial depth shape features and temporal joints features are used to improve classification performance. Both of these features are fused together to recognize different activities using the modified hidden Markov model (M-HMM). The proposed approach is evaluated on two challenging depth video datasets. Moreover, our system has significant abilities to handle subject's body parts rotation and body parts missing which provide major contributions in human activity recognition.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.3
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• pp.427-440
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• 2020

This study developed a vest prototype capable of monitoring body temperature using textile electrodes to prevent the sudden death of babies as well as to determine the quality of developed products by evaluating usability with commercial products. Based on the results of the 7th Size Korea Project, a basic pattern for a vest prototype was drafted by applying the average size of two-year-old Korean babies. Two prototypes were the detachable (VEST I) and integrated textile electrodes vest type (VEST II), which followed the same design. The materials were 100% cotton single jersey (SJ) and double jersey (DJ). Six experts evaluated the usability of the developed vests (VEST I & VEST II) and commercial product (VEST M). The single-layer woven textile electrode appeared to have a slightly higher conductivity than the double-layer one. There was no statistical difference in the body temperature sensing function between VEST I and VEST II. Finally, the superiority of the VEST I was verified through a comparison with commercial products (VEST M). The usability test suggested that a wearable smart clothing system of the integrated conductive textile could be further commercialized for bio-monitor applications in Ubiquitous-health care.