• 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.

• The Journal of Korean Society for School & Community Health Education
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• v.20 no.1
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• pp.113-126
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• 2019

Objectives: The purpose of this study is to understand the relevance of chronic disease conditions and fall experience among people aged 65 and older. and use them as basic data to reduce the risk of falling. Methods: The study selected 26,122 men and 37,777 women aged 65 and over as final subjects of the study, using raw data from the Community Health Survey in 2015. The statistical analysis used SAS 9.4 USA. Results: About 20% of those aged 65 and older experienced a fall, with one in five elderly people experiencing a fall, and the ratio of men to women was 3:7, women higher than men. As the age grew, the lower the level of education, the more senior citizens who lived alone occurred falls. In addition, the incidence of falls was higher when the number of chronic diseases was more than three. The incidence of falls was 1.1-1.5 times higher depending on chronic diseases. Conclusion: The development of education and exercise programs for preventing fall of senior citizens aged 65 and older is required and further study is needed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.249-251
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• 2021

In this paper, we introduce the deep-learning system using Tensorflow for recognizing situations that can occur fall situations when the elderly are moving or standing. Fall detection uses the LSTM (long short-term memory) learned using Tensorflow to determine whether it is a fall or not by data measured from wearable accelerator sensor. Learning is carried out for each of the 7 behavioral patterns consisting of 4 types of activity of daily living (ADL) and 3 types of fall. The learning was conducted using the 3-axis acceleration sensor data. As a result of the test, it was found to be compliant except for the GDSVM(Gravity Differential SVM), and it is expected that better results can be expected if the data is mixed and learned.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2451-2454
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• 2005

In recent years, the importance of the characterization of fall for a fracture prevention system keeps increasing since fracture from a fall can lead to serious health problems. Fall is one of the major sources which increase morbidity in elderly people. In terms of the cost and the influence to the quality of life, the most serious injury with hip fractures is caused by falls. The traditional methods in characterizing fall patterns have been mainly by the epidemiological surveys. With surveys, the exact data of fall patterns can not been acquired. In this paper, we measured and analyzed with the parameters related to fall pattern such as velocities and accelerations during the motion of falls using 3D motion capture program. We acquired the parameters of the fall pattern of intentional and unexpected fall. The result showed that the variation of velocity and acceleration during fall was very important in characterizing fall pattern, which of vital importance for the development of a fracture prevention system and for the safety of the elderly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2142-2149
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• 2014

This study was to find out urinary incontinence, quality of sleep and efficacy of fall in the community dwelling elderly and to investigate how the factors were connected to one another. Data were collected between January 3rd and 30th, 2013 from 112 elderly people who aged 65 or older. They agreed to participate in this study sampled among elders assistants in a way of responding to the questionnaire after being read. The study scales were composed of demographic characteristics, urinary incontinence, quality of sleep and efficacy of fall. A total of 45(40.2%) subjects were reported fall experienced. The results showed a positive correlation with urinary incontinence, quality of sleep and efficacy of fall. Multiple linear regression analysis revealed that predictor of efficacy of fall was quality of sleep. A combination of the urinary incontinence and quality of sleep accounted for 9.6% of the efficacy of fall.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.533-539
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• 2015

The purpose of this study was to investigate the effects of 12weeks complexed lower body muscle-strengthening exercise program on fall risk in elderly women. Twenty subjects volunteered to participate who use a welfare center in W city For the study we divided into two groups: exercise group (EC, n=10, mean age:$69.6{\pm}2.2$), comparative group(CG, n=10, mean age:$71.3{\pm}4.6$). In order to investigate the effect of lower body muscle-strengthening program on the degree of risk of fall. It reached a conclusion as follows after having applied BBS (Berg Balance Scale) and OLST (One-Leg Stance Test) to examine the degree of risk of fall. As a result of changes in BBS and OLST, there were significant differences between EG and CG for each test(p<.00). Therefore, it confirmed that the application of complexed lower body muscle-strengthening program to the elderly who have a high risk of fall influences the risk of fall positively.

• The Journal of Korean Physical Therapy
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• v.26 no.6
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• pp.430-435
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• 2014

Purpose: The objective of this study was a virtual reality-based balance training program effective for improvement in physical function, examined the balance ability and fall efficacy of elderly women with experienced falls, intending to examine the program's usefulness as an exercise program to prevent the recurrence of a fall. Methods: The participants were 30 elderly women aged 65 or older who met the conditions. The participants were randomly assigned to either a balance training group (BT) or a virtual reality-based balance training group (VT) and received the training three times per week, 30 minutes per day, for six weeks. To measure static balance, the Tetrax Portable Multiple System (Tetrax Ltd, Israel) were used. To measure dynamic balance, the Berg Balance Scale (BBS) and functional reach test (FRT) was used, and regarding fall efficacy, the Korean Fall Efficacy Scale (K-FES) was used. Results: Tetrax significantly improved after the intervention in both the BT group and the VT group (p<0.05). The comparison between the two groups was not significantly. BBS and FRT result significantly improved after the intervention in both the BT and VT groups (p<0.001), while K-FES was significantly ameliorated in the VT group only (p<.05). Comparing the groups, there were more significant changes in the BBS (p<0.05) and FRT (p<0.01) result of the VT group than the BT group. Conclusion: A virtual reality-based balance training program is considered to be usable as an exercise program to prevent recurrence of falls in elderly women.

• Korean Journal of Adult Nursing
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• v.15 no.3
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• pp.432-440
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• 2003

Purpose: The purposes of this study were to examine 1) functional status at 2 months after hip fracture surgery 2) health care utilization after a fall episode and 3) fear of falling experienced during first 2 months after a fall episode. Method: With a convenient sample of 99 elderly from six university or general hospitals with hip fracture from a fall, data were collected at 2-3 days before discharge and at 2 months after hip fracture surgery. Result: 1) At 2 months after hip fracture from a fall, significant proportion (25.3%) of elderly was not able to walk indoors. 2) Average length of hospital stay was 27.6 days with a range of 8 to 86 days. About 51% subjects received physical therapy during hospital stay, and only 6.1% subjects received physical therapy following discharge from the hospital. 3) Significant proportion (72.7%) had fear of falling after the fall episode. About 51% reported that they restricted their activities because they had fear of falling. Conclusion: Fall is a dreaded event which result in loss of independence and restriction of activity. Development and application of fall prevention program is critical especially for those with risk factors of fall.

• Korean Journal of Applied Biomechanics
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• v.31 no.3
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• pp.189-198
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• 2021

Objective: The aim of this study is to investigate the effect of biomechanical variables on gait according to indoor and outdoor environmental conditions in elderly women at risk of falling. Method: 26 elderly women aged 70 years or older, and consisted of 13 elderly people with a walking speed of less 1.0 m/s and 13 people in the fall risk group as normal groups. Depending on the purpose of the study, physical examination and psychological questionnaire were prepared, and then walking was performed in an indoor/outdoor environment, and the gait pattern, muscle activity, and plantar pressure results were compared and analyzed in the elderly females through a 2 group × 2 environment 2-way repeted ANOVA analysis. Results: The gait variable showed an interaction effect the cadence. The muscle variables showed interaction effects in the rectus femoris and tibialis anterior muscles, and the interaction effects of the plantar pressure variables were confirmed in the forefoot and midfoot of the contact area, and the midfoot of the mean pressure. Conclusion: These results indicate that both groups are exposed to falls risk when gait in an outdoor environment, but the fall risk group has a higher risk of falls in both the gait pattern, muscle activity, and plantar pressure variables. The results of this study are considered to be helpful as basic data and development of exercise programs to prevent falls.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.199-206
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• 2013

An emergency monitoring system for the elderly, which uses acceleration data measured with an accelerometer, angular velocity data measured with a gyroscope, and heart rate measured with an electrocardiogram, is proposed. The proposed fall detection algorithm uses multiple parameter combinations in which all parameters, calculated using tri-axial accelerations and bi-axial angular velocities, are above a certain threshold within a time period. Further, we propose an emergency detection algorithm that monitors the movements of the fallen elderly person, after a fall is detected. The results show that the proposed algorithms can distinguish various types of falls from activities of daily living with 100% sensitivity and 98.75% specificity. In addition, when falls are detected, the emergency detection rate is 100%. This suggests that the presented fall and emergency detection method provides an effective automatic fall detection and emergency alarm system. The proposed algorithms are simple enough to be implemented into an embedded system such as 8051-based microcontroller with 128 kbyte ROM.