• Korean Journal of Human Ecology
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• v.19 no.6
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• pp.1031-1044
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• 2010

Corresponding to the rapid growth of the aging population without an adequate social safety net for the elderly, older people face great disadvantages due to sudden illness or poor health and a lack of support from the younger generation. Furthermore, older women are suffering from a drastic deterioration of their economic status because of insufficient retirement savings. Examining the impact of labor force participation and living arrangement on health status and life satisfaction in later life, it is important to consider gender differences in context of social policies for the elderly. Using data based on a stratified national sample of the elderly by the Korean Longitudinal Study of Aging (KLoSA), multiple regression model were used to estimate the relationships between labor force participation and health status and subjective life satisfaction concerning the quality of their later life. The result indicates that good health status and high level of life satisfaction are associated with the type of paid work status for the elderly men, but those are associated with the type of non paid work, such as family businesses employees for the elderly women. Significant differences in chronic health condition and subjective life satisfaction by employment characteristics are found among the elderly. In addition, older women's high level of life satisfaction was associated with the participation of the social activity. The major conclusion from these results should help us understand gender differences in the elderly and acknowledge further exploration of gender variations in these people's later life.

• The Journal of Korean Academic Society of Nursing Education
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• v.12 no.1
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• pp.28-35
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• 2006

Purpose: This study was performed to verify the effect of rhythmic activity program on the elderly particularly their level of instrumental activities of daily living(IADL), depression and sleep. Method: The design of this study is one-group pretest-post test design. Three self-reported questionnaires were used as follows: first, the IADL Scale developed by Lawton and Brody(1969) and revised by Suh(1996) for measuring IADL, second, the Geriatric Depression Scale developed by Sheikh and Yesavage(1986) and revised by Song(1991) for measuring depression, third, Korean Sleep Scale developed by Oh, Song, & Kim(1998) for measuring sleep aspects; fourth, the applied version of Facial Pain Scale developed by Wong & Baker(1988) and revised by Song(2004) for measuring sleep quality. Twenty-seven elderlies carried out 50 minutes of rhythmic activity program for 4 weeks. Before and after the experiment, they were tested for IADL, depression and sleep. Collected data were processed using the SPSS/WIN 12.0 program analyzed by the frequency, percentage, mean and paired t-test. Results: The improvement in IADL of the elderly was not enhanced significantly but depression and sleep disorders significantly decreased. Conclusion: Rhythmic activity program is an effective nursing intervention for the elderly.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.41-43
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• 2005

PDA-based monitoring is used to acquire continuously the patient's vital signs, including electrocardiography, activity, heart rate and $SpO_2$. In this paper, A biomedical signal acquisition device was designed using 3-axial MEMS accelerometer and 1-ch ECG amplifier, to have the function of monitoring activity and electrocardiography. The proposed system is composed of transmitter and receiver. Through the Zigbee communication, subject's biosignals can be transmitted in real-time to receiver, and transmitted data confirmed using PDA. The packet size used in this device was set not to exceed a maximum payload size of 116 byte. One packet consists of two segments. The transmission speed was 21 packet per second, 420 ECG samples per second, and 42 acceleration samples per second. The proposed method can be used to develop Activities of Daily Living(ADL} monitoring devices for the elderly or movement impaired people and enables patients to be monitored without any constraints. Also, this method will reduce medical costs in the aged society.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1189-1204
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• 2018

Detecting and capturing 3D human structures from the intensity-based image sequences is an inherently arguable problem, which attracted attention of several researchers especially in real-time activity recognition (Real-AR). These Real-AR systems have been significantly enhanced by using depth intensity sensors that gives maximum information, in spite of the fact that conventional Real-AR systems are using RGB video sensors. This study proposed a depth-based routine-logging Real-AR system to identify the daily human activity routines and to make these surroundings an intelligent living space. Our real-time routine-logging Real-AR system is categorized into two categories. The data collection with the use of a depth camera, feature extraction based on joint information and training/recognition of each activity. In-addition, the recognition mechanism locates, and pinpoints the learned activities and induces routine-logs. The evaluation applied on the depth datasets (self-annotated and MSRAction3D datasets) demonstrated that proposed system can achieve better recognition rates and robust as compare to state-of-the-art methods. Our Real-AR should be feasibly accessible and permanently used in behavior monitoring applications, humanoid-robot systems and e-medical therapy systems.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• Journal of Korean Academy of Nursing
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• v.31 no.1
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• pp.139-149
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• 2001

The purpose of this study was to analyze characteristics related to the activity of Daily Living (ADL) and dementia among the elderly people who have Medicaid. The cross-sectional descriptive survey study was a nationwide randomization sampling among the population of elderly families who have Medicaid. The data were collected during the month of October, 1999 and total sample was 1,027 elderly people. There were major findings according to the studies. In the results of the ADL assessment most of elderly people were within the 24 to 45 point range. Also, 63.3% of elderly people who made 45 points do not need help when performing daily activities according to the 15 areas of activity components, and 4.9% of these people couldn't do their daily activities. The results of the Dementia assessment were 70.6% of elderly people were in the normal range, 21.7% have a mild case, and 2.8% have severe case of dementia. These were found by using instruments for mental states, which simplified to items of detection of early dementia. In the result of these tests, there was a significantly positive correlation between ADL and degree of dementia with the pearson correlation coefficients. As a result of these studies, the author recommend to strengthen function and organization of public health like a visiting nurse center for elderly people who are over 65 years old. In addition, the government should apply early detection and management system for dementia in the community continuously and cost-effectively, especially for elderly people who live alone and are vulnerable elderly as our priority.

• Journal of Korean Physical Therapy Science
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• v.11 no.4
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• pp.11-19
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• 2004

Muscle stiffness, pain discomfort in daily activities are cardinal symtoms on arthritis. To reduce these symtoms, a nonequivalent one-group pre & posttest experiment was carried out at a rural community health post area in kwangju province during eight weeks(from 25th of January to 20th of March, 2002) The subjects were sixteen old (60-80) with osteoarthritis. And to reduce the level of pain, discomfort in daily living and to increase that of life satisfaction, 25-30minutes of muscle-joint exercise followed by 25-30minutes of local heat therapy were done three times a week. The total experimental period extended at 12 weeks and the total 36 times it executed 1. The retrogression characteristic osteoarthritis elderly with local heat and a muscle joint exercise was the telegram which it receives and after receiving, the score of the paindaily activity function appeared to the lead, there was a difference which considers statistically, this constriction was supported.(Z=4.947, p<0.0001) 2. The retrogression characteristic osteoarthritis elderly with local heat and a muscle joint exercise was the telegram which it receives and after receiving, the score of daily activity function appeared lowly, there was a difference which considers statistically, this construction was supported.(Z=2.7226, p<0.0279) 3. The retrogression characteristic osteoarthritis elderly with local heat and a muscle joint exercise was the telegram which it receives and after receiving, there was not a difference where the quality of life considers statistically, this construction was rejected.(Z=-1.2087, p>0.2171)

• Therapeutic Science for Rehabilitation
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• v.9 no.2
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• pp.99-117
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• 2020

Objective : The purpose of this study was to study the effects of occupation-based community rehabilitation on occupational performance skills and activities of daily living in stroke disabled persons living in the community, and to investigate the changes in occupation quality and satisfaction. Methods : In this single-subject ABA design study with follow-up evaluation, one severely disabled person diagnosed with stroke who lived in the community was recruited. The procedure consisted of a total of 25 sessions for 17 weeks. Intervention was according to occupation-based community rehabilitation, and the researcher visited the subject's home. Individualized intervention was applied according to the OTIPM. The intervention was composed of task assignment and feedback, home environment modification, information-related caregiver education, and community resource network. The evaluation of each session included the changes in the frequency of occupational performance skills, the quality of occupational performance in daily life, and the changes in occupational satisfaction, activities of daily living, quality of life, and maintenance of in the occupational performance skills during follow-up. The results were visually analyzed using a bar graph and a linear graph. Results : The results showed that the occupation-based community rehabilitation improved activities of daily living such as putting on socks, shoes slip-on, and upper body dressing garment within reach. Within the framework of the AMPS, it was confirmed that the quality of occupational performance was improved in all the subjects, and the degree of satisfaction also improved. Conclusion : This study showed that occupation-based rehabilitation can improve the occupational performance skills of stroke home disabled people positively affect the quality of occupational performance in daily life. Therefore, I think it is meaningful that useful for them.

• The Korean Journal of Community Living Science
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• v.18 no.2
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• pp.277-291
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• 2007

The purpose of this study was to examine the costume worn by women in daily life according to life scenes depicted in genre paintings of the late Chosan Dynasty. The sentiments and customs of the time were examined to discover how costume culture followed women's lifestyles in the late period of the Chosun Dynasty. First, according to life scenes, a field amusement type costume was the most common garment and a commercial activity type costume was the least common garment. Second, when the form of costume was examined followed by the lifestyle it depicted, the following observations were noted. Women depicted in a housework type lifestyle often wore a Minjeogori. In contrast, women appearing in a labor production type or a commercial activity type lifestyle often wore a Banhoijangjeogori with the width of the coat narrowing gradually according to the trends of the time. In the forms of Chima, the women wore a Duluchima and a Gudlchima for convenience during their work and covered a Haengjuchima over it. Third, women shown in a field amusement type, a home enjoyment type or an affection pursuit type lifestyle mainly wore a deep blue colored Chima and Hoijang or Banhoijang Jeogori. While most of the women depicted in a labor production type, a housework type or a commercial activity type lifestyle wore a natural cotton colored Jeogori and a natural cotton colored and light indigo Chima. Fourth, in the field amusement type and the affection pursuit type lifestyle, the wearing of a headdress during outings of women appeared variously influenced by the strengthening restrictions placed on the women's lives according to the ethics of Confucianism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3836-3854
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• 2022

The student group division is benefit for universities to do the student management based on the group profile. With the widespread use of student smart cards on campus, especially where students living in campus residence halls, students' daily activities on campus are recorded with information such as smart card swiping time and location. Therefore, it is feasible to depict the students with the daily activity data and accordingly group students based on objective measuring from their campus behavior with some regular student attributions collected in the management system. However, it is challenge in feature representation due to diverse forms of the student data. To effectively and comprehensively represent students' behaviors for further student group division, we proposed to adopt activity data from student smart cards and student attributes as input data with taking account of activity and attribution relationship types from different perspective. Specially, we propose a novel student group division method based on a multi-view student attribute heterogeneous information network (MSA-HIN). The network nodes in our proposed MSA-HIN represent students with their multi-dimensional attribute information. Meanwhile, the edges are constructed to characterize student different relationships, such as co-major, co-occurrence, and co-borrowing books. Based on the MSA-HIN, embedded representations of students are learned and a deep graph cluster algorithm is applied to divide students into groups. Comparative experiments have been done on a real-life campus dataset collected from a university. The experimental results demonstrate that our method can effectively reveal the variability of student attributes and relationships and accordingly achieves the best clustering results for group division.