• Journal of Korean Gerontological Nursing
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• v.20 no.sup1
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• pp.127-136
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• 2018

Purpose: The purpose of this study was to investigate the possibility of using intelligent robot based nursing practice as discussed in previous research and also, to propose directions for robot care for elders. Methods: For this study 28 previous researches using robots in health care field were reviewed and related research trends introduced. Results: Robot applications in the healthcare field were mainly for rehabilitation, surgery, interaction, and nursing assistance through robotics. Especially types of robot include pet type robots, humanoid robots, surgical robots, rehabilitation robots, robot suit and entertainment robots with monitors. The research participants were patients with dementia and institutionalized elderly people. It was found that a human-robot interaction was effective from physical, mental, emotional and social aspects. Conclusion: Robots can be used for various purposes such as nursing assistance, patient health promotion and education. It is necessary to reduce the human burden of care work using robots and to introduce robot care programs which can meet the needs of elders. Therefore, korean nurses should make efforts to change their practice to new geriatric nursing through repeated research based on the scientific data.

• Health Policy and Management
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• v.21 no.3
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• pp.381-396
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• 2011

This study is to investigate the factors affecting the regional rate of certification for long-term care insurance benefits. Analyzed data were the 253,935 certified beneficiaries (equivalent to 4.9% of total elderly population) as long-term care degree (LTC degree) 1~3 extracted from the applicants for long-term care in the beginning stage of the system from April 15 2008 to July 1 2009. Although the data were collected from individuals, after restructured into regional data and then analysed in the unit of 225 administrative regions for the Korean Long-term Care Insurance. The rate of certification was operated as the percentage of people of LTC degree 1~3 to the elderly population in each region. The average rate of certification among regions was 4.91%, and ranged from 2.20% to 8.32%. In the analysing regression models, most socio-demographic variables, applicants' disease characteristics, regional service infrastructure, and the certification interviewer's characteristics were included. The most influencing variables were the disease factors of applicants, especially dementia or cerebrovascular disease rather than arthritis, osteoporosis, or fracture patients were strong factors for the regional rate of certification. However, advanced studies adding more explainable factors on the regional variance of certification rate would be necessary to provide political agenda and measures for evidence-based certification process with high reliability and validity for a sustainable LTC system in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.402-409
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• 2019

Patients with dementia or elderly patients who can not move at all by themselves are at a high risk of falls and bedsore due to lack of caregivers. In this paper, to solve this problem, we propose an algorithm to determine the patient's lying postures by discriminating the main body parts such as head, shoulders, and hips based on the pressure intensity sensed at regular intervals. A smart mat with a lattice structure in which a pressure sensor is arranged so that the body part can be discriminated irrespective of the physical characteristics has been implemented. It consists of two modules of $7{\times}7$ array size. Each module consists of 49 FSR-406 sensors and independently senses pressure. For each module, the body part corresponding to the upper body or the lower body is sequentially discriminated by using a pressure distribution such as a cumulative pressure sum using a filter. The proposed algorithm can identify five lying positions by examining the inclusion relationship between body parts belonging to layer-1 such as head, shoulder, and hip area.

• Korean Journal of Clinical Pharmacy
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• v.31 no.2
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• pp.96-103
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• 2021

Background: The number of elderly people with comorbidities who experience dysphagia associated with geriatric disorders, such as stroke, Parkinson's disease, and Alzheimer's dementia, is increasing. Consequently, the demand for long-term prescriptions of powdered medications is expected to rise. Most patients procure repackaged prescription medications from pharmacies; however, the guidelines regarding their expiration dates are unclear. Objectives: The aim of this study was to assess awareness among adults regarding the expiration dates and drug stability issues associated with repackaged prescription medications, including powdered medications. Methods: A questionnaire with 16 components was designed and distributed online (August 1-September 1, 2019) to adults aged 19 years or older. Statistical analyses, including descriptive analysis and chi-square test, were conducted on the obtained data. A p-value <0.05 was considered significant. Results: Data from 254 respondents were analyzed; 191 (75.20%) respondents worked in non-healthcare-related fields. A significant number of healthcare workers recognized the stability issues associated with powdered medications (p<0.001). However, a large proportion of healthcare workers were not aware of the expiration dates (p>0.05). Conclusions: More than half of the total respondents, including healthcare workers, were not familiar with the appropriate expiration dates of repackaged prescription medications. The establishment of evidence-based guidelines regarding drug expiration dates and the dissemination of awareness among patients are required. Furthermore, clinical practices including repackaging or pulverizing medications for long-term prescriptions should be avoided owing to the associated drug stability issues.

• Journal of Nutrition and Health
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• v.41 no.8
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• pp.718-732
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• 2008

The purpose of this study was to investigate nutrients or food factors related to cognitive function of elderly having Alzheimer's disease. In this study 38 subjects who were over 65 years old have participated in dementia clinic at A medical center. After they were diagnosed to Alzheimer's Disease (AD) through blood analysis, neuropsychological test, brain image and interview by medical specialist, we examined for their general information, anthropometry, blood pressure and dietary intakes. Dietary intakes were investigated using the 24-hour recall record. Energy intake was adequate and the energy composition of carbohydrate, protein and fat was 60.8 : 16.2 : 23.0, but dietary intakes of calcium, vitamin A and folate were less than 75% of the recommended intake levels for Koreans. The multiple regression analysis adjusted with age, sex and educational level showed that cognitive function was positively related to intakes of zinc, fishes and shellfishes, beans & nuts, sugars and fats, and negatively related to intakes of plant calcium and eggs. These results indicate that intakes of specific nutrients or food groups are associated with the specific domains of cognitive function in elderly with AD.

• Korean Journal of Psychosomatic Medicine
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• v.29 no.1
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• pp.67-76
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• 2021

Objectives : The aim of this study was to compare activities of daily living (ADLs) according to degenerative changes in brain [i.e., medial temporal lobe atrophy (MTA), white matter hyperintensities] and to examine the association between neurocognitive functions and ADLs in Korean patients with dementia due to Alzheimer's disease (AD) and mild cognitive impairment (MCI). Methods : Participants were 111 elderly subjects diagnosed with AD or MCI in this cross-sectional study. MTA in brain MRI was rated with standardized visual rating scales (Scheltens scale) and the subjects were divided into two groups according to Scheltens scale. ADLs was evaluated with the Korean version of Blessed Dementia Scale-Activity of daily living (BDS-ADL). Neurocognitive function was evaluated with the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease assessment packet (CERAD-K). Independent t-test was performed to compare ADLs with the degree of MTA. Pearson correlation and hierarchical multiple regression analyses were performed to analyze the relationship between ADLs and neurocognitive functions. Results : The group with high severity of the MTA showed significantly higher BDS-ADL scores (p<0.05). The BDS-ADL score showed the strongest correlation with the word list recognition test among sub-items of the CERAD-K test (r=-0.568). Findings from the hierarchical multiple regression analysis revealed that the scores of MMSE-K and word list recognition test were factors that predict ADLs (F=44.611, p<0.001). Conclusions : ADLs of AD and MCI patients had significant association with MTA. Our study, which identifies factors correlated with ADLs can provide useful information in clinical settings. Further evaluation is needed to confirm the association between certain brain structures and ADLs.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.940-952
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• 2020

The Alzheimer's disease (AD) is a neurodegenerative disease commonly found in the elderly individuals. It is one of the most common forms of dementia; patients with AD suffer from a degradation of cognitive abilities over time. To correctly diagnose AD, compuated-aided system equipped with automatic classification algorithm is of great importance. In this paper, we propose a novel deep learning based classification algorithm that takes advantage of MRI biomarker images including brain areas of hippocampus and cerebrospinal fluid for the purpose of improving the AD classification performance. In particular, we develop a new approach that effectively applies MRI biomarker patch images as input to 3D Deep Convolution Neural Network. To integrate multiple classification results from multiple biomarker patch images, we proposed the effective confidence score fusion that combine classification scores generated from soft-max layer. Experimental results show that AD classification performance can be considerably enhanced by using our proposed approach. Compared to the conventional AD classification approach relying on entire MRI input, our proposed method can improve AD classification performance of up to 10.57% thanks to using biomarker patch images. Moreover, the proposed method can attain better or comparable AD classification performances, compared to state-of-the-art methods.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.167-172
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• 2019

The purpose of this study was to investigate the effect of computer based cognitive rehabilitation program on the generative naming. Twenty - one patients were assigned to the CoTras program and eight were treated with traditional face - to - face language rehabilitation such as paper and table activities. The experimental group and the control group performed sequential language recall memory training, association memory recall training, language categorization memory training, and language integrated memory training for 12 weeks. The Welch's robust ANCOVA showed significant differences in mean fluency and MMSE-K changes (p<0.05). On the other hand, phonemic fluency increased significantly after 12 weeks of treatment compared to baseline in both experimental and control groups, but there was no statistically significant difference between treatment groups. The results of this study suggest that the computer based cognitive rehabilitation program may be more effective in improving the semantic fluency than the conventional cognitive-linguistic rehabilitation.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.327-336
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• 2021

It is important to prevent progression of mild cognitive impairment (MCI) to Alzheimer's disease or other dementia. This study was conducted to investigate cognitive-based intervention and its effectiveness for the older patients with MCI through systematic review. Data search was conducted in September 2020, using the Korea Research Information Service (Riss) and KoreaMed. After selection of literatures according to the predefined inclusion criteria, a total of 12 articles were included. It is revealed that the cognitive-based intervention for the older adults with MCI was found to have a positive effect on the various factors including cognitive function, depression, physical health status, quality of life, and communication. However, it is difficult to draw a definite conclusion due to the various intervention strategies and instruments used. Thus, based on the results of this study, we suggest more studies to verify the effectiveness of such programs.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.443-448
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• 2023

Over the past five years, the number of patients with sleep disorders has increased by about 250,000 from 840,000 in 2017 to 1.09 million in 2021. In addition, sleep disorder is a factor that causes dementia risk factors, and furthermore, the population with sleep disorder is a very important policy issue in terms of stable health insurance financial management in the future in terms of national health management in the super-aging trend. Therefore, this study aims to establish an efficient treatment environment in medical institutions responsible for the current status of polysomnography and effective reimbursement policies for the recently increasing population with sleep disorders, and appropriate sleep management policies for future sleep disorders through correct implementation. We are trying to find out the actual condition and improvement plan through interviews with related organizations and experts.