• Therapeutic Science for Rehabilitation
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• v.7 no.2
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• pp.41-50
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• 2018

Objective: This study was conducted to investigate the correlation of cognitive function and fall-risk behavioral factors. Methods: The elderly over than 65 year-old with and without cognitive impairment were recruited in four different regional areas. Total 43 data of K-MoCA and FaB were collected. Pearson correlation of total scores of K-MoCA and FaB was analyzed using SPSS 22. Correlation between total score of K-MoCA and each item of FaB which describes the fall-risk behaviors was analyzed as well. Results: The cognitive function was statistically positive correlated with the fall-related behaviors in pearson correlation analysis (p<.01). Nine items of total 30 items of FaB was significantly correlated with total score of K-MoCA. Conclusion: Fall-risk behaviors were decreased as the cognitive level was improved. If the cognitive function was vulnerable, the insight to fall-risk behaviors deficits and various fall-related behavioral factors exits. The high fall-risk behaviors were correlated with cognitive function, so that the cognitive level should be considered in fall prevention intervention in Occupational Therapy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.51-62
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• 2022

This study suggests a design of predictive modeling for a hospital fall risk based on inpatients' posture. Inpatient's profile, medical history, and body measurement data along with basic information about a bed they use, were used to predict a fall risk and suggest an algorithm to determine the level of risk. Fall risk prediction is largely divided into two parts: a real-time fall risk evaluation and a qualitative fall risk exposure assessment, which is mostly based on the inpatient's profile. The former is carried out by recognizing an inpatient's posture in bed and extracting rule-based information to measure fall risk while the latter is conducted by medical staff who examines an inpatient's health status related to hospital fall risk and assesses the level of risk exposure. The inpatient fall risk is determined using a sigmoid function with recognized inpatient posture information, body measurement data and qualitative risk assessment results combined. The procedure and prediction model suggested in this study is expected to significantly contribute to tailored services for inpatients and help ensure hospital fall prevention and inpatient safety.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.271-277
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• 2018

The aim of this study was to select useful items for assessing fall risk in community-dwelling elderly. This study assumed five fall risk factors: Symptoms of falling, physical function, disease and physical symptoms, environment, and behavior and character based on previous studies. The questionnaire consisted of 44 items according to the contents validation, crossover analysis and factor analysis. The Korean version of the Fall Risk Assessment Scale (FRA-K) will be used as a useful tool to improve the fall problems perceived to be serious social problems and to provide important information for prevention of falls.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6353-6363
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• 2013

This study examined the factors associated with recurrent falls among the community-dwelling elderly. The participants were 329 community-dwelling elderly. The data was collected from February 5, 2010 to February 14, 2010. Over the past 1 year, 14.3% of the 329 participants fall once, and 4.0% experienced recurrent falls. There was a significant difference among the non fallers, single faller and recurrent fallers with regard to the static balance(F=5.86, p=.003), dynamic balance(F=24.32, p<.001), risk of fall(F=9.94, p<.001) and compliance of prevention behavior related to falls(F=3.09, p=.047). The analysis results for the correlation between variables showed that the number of falls had a negative effect on the knee flexors muscular strength(r=-.15, p=.008), static balance(r=-.16, p=.004) and compliance of prevention behavior related to falls(r=-.12, p=.030) and a positive affect for the dynamic balance(r=.26, p<.001), depression(r=.13, p=.019) and risk of falls(r=.30, p<.001). The variables explained 36.0% of the variants in the occurrence of recurrent falls. Therefore, an effective recurrent fall prevention program should focus on multiple risk factor intervention.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.55-65
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• 2022

Elderly people with Parkinson's disease have higher rates of physical and mental risk factors for falls than non-Parkinson's disease elderly. The purpose of this study is to investigate this by using national data that includes the entire population of the elderly in Korea. As a secondary analysis study using data survey on the elderly by the Ministry of Health and Welfare in 2017, there were a total of 103 elderly people with Parkinson's disease, and a total of 96 subjects were analyzed excluding missing values. In the elderly with Parkinson's disease, the factor most influencing the fall was IADL, and IADL is related to motor control function. Decreased motor control limits physical movements essential for daily life, and even affects self-protective behavior in emergency situations, affecting falls. Based on the research results that IADL can affect falls, various exercise therapies for fall prevention interventions in the elderly with Parkinson's disease can be suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.510-516
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• 2020

This study investigated the characteristics and factors affecting inpatient infants, children, and adolescents who experienced falling, using NHDIS data from 2008 through 2017, The study analyzed data of 116 patients who were under 18 and who experienced injuries (KSCD, S00-S99) by falling (KSCD, W00-W19). Frequency analysis, cross-tabulations, and multiple regression analysis were conducted, using SPSS 23. There were more boys than girls, and most of the falls occurred at the ages of over one to under six years old. Most of the children had respiratory diseases, and most had open wounds or bruises due to falling. Also, most of the falls were related to the bed. In the factor analysis, age (β=.318), the main diagnosis (β=.231), and injury (β=.169) except gender affected falling. This suggests that it is necessary to conduct fall prevention education for children, considering the developmental stage characteristics and age group. It is necessary to screen the risk group such as children with a disease with relatively less restriction of activities or with a hyperactive disorder, and to develop a related manual. Hopefully, the results will be used as the basic data for fall prevention education and creating a fall prevention manual according to the characteristics of children's developmental stage for patients who need hospitalization, their caregivers, and the relevant medical team.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.25-27
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• 2021

With the recent development of deep learning technology, computer vision-based AI technologies have been studied to analyze the abnormal behavior of objects in image information acquired through CCTV cameras. There are many cases where surveillance cameras are installed in dangerous areas or security areas for crime prevention and surveillance. For this reason, companies are conducting studies to determine major situations such as intrusion, roaming, falls, and assault in the surveillance camera environment. In this paper, we propose a real-time abnormal behavior analysis algorithm using object detection and tracking method.