• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.285-286
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• 2016

본 연구는 가상현실시스템을 이용한 훈련이 뇌졸중 환자의 균형과 낙상효능감에 미치는 영향을 알아보기 위해 실시하였다. 연구 대상자는 뇌졸중 환자 20명으로 실험군 10명 대조군 10명씩 각각 배정하였다. 실험군과 대조군 모두 일반적인 주 5회의 물리치료와 작업치료를 받았다. 실험군은 추가적으로 가상현실 프로그램을 이용하여 8주간 1일 20분 주 3회 시행하였다. 본 연구의 측정은 균형수행 능력검사, 낙상효능감 척도검사를 사용하였다. 두 군 간 훈련 후 측정 사이에 균형수행 능력검사와, 낙상효능감 검사에서 통계적으로 유의한 차이를 보였다(p<0.05). 또한 각 군 간 훈련 후 측정 사이에 균형수행 능력검사와, 낙상효능감 검사에서 통계적으로 유의한 차이를 보였다(p<0.05). 따라서 가상현실 프로그램 병행한 훈련이 뇌졸중 환자의 균형과 낙상효능감을 향상시키는데 긍적적인 도움을 주어 유용한 뇌졸중 환자의 치료 프로그램으로 사용될 수 있을 것으로 보여 진다.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.4
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• pp.19-24
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• 2013

The problem of elderly people with weak physical health has become a very important issue in the aging society. Elderly people with very low judgment and decision-making skills often falls because of the degradation of the strength and balance. Due to the fall triggered off fractures, parenchyma damage, and casualties, generally fast emergency treatment is needed. In this paper, an automatic fall detection system consisting of a triaxial accelerometer and tilt sensor. Using the fall system, the performance of the system was analyzed in many situations. The experimental results showed more than 92% analytical skills.

• 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.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.274-282
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• 2012

This study conducted the following experiment to examine change of physicopsychological function on lumbar stabilization exercise(LSE) and virtual reality game training(Nintendo Wii Sport-NWS) to stroke patients subject for fall prevention. Psychological function was measured by falls efficacy with stroke patients and physical function was measured by static and dynamic balance on comparative analysis of pre, post exercise and each groups in 30 stroke patient subject. Static balance was measured by BBS, FRT, dynamic were measured by TUG, 10m walking test and falls efficacy with stroke patients was measured index of falls efficacy. These result lead us to the conclusion that each group were statistically improved at all physicopsychological test, but BBS, FRT, 10m walking test were more statistically improved at LSE group and falls efficacy with stroke patients were more improved at virtual reality game training group. Consequently, virtual reality game training would be lead to positive increment of physicopsychological function on stroke patient.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.547-550
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• 2020

노인인구의 급증에 따라 노인 건강에 대한 관심이 증가하였고 노인 낙상을 발견하는 방법에 대한 관심도 함께 대두되기 시작하였다. 낙상 사고의 경우 낙상을 일으킨 원인보다 낙상이 제때 감지되지 않아 발생하는 이후의 상황이 더욱 심각한 결과를 초래한다. 따라서 낙상이 발생했을 때, 바로 낙상을 감지할 수 있는 시스템 구축이 필요하다. 다양한 낙상 검출을 위한 방법이 존재하지만 그 중 착용이 쉽고 원격지에서 관찰 및 관리가 가능한 웨어러블(Wearable) 기기의 센서 데이터를 사용한 낙상 검출을 진행하였다. 본 논문에서는 머신 러닝 모델들을 사용해서 낙상 검출 성능 비교 및 적절한 모델을 제안한다. 기계 학습 기반의 모델인 결정 트리(Decision Tree), 랜덤 포래스트(Random Forest), SVM(Support Vector Machine)을 사용하여 실제 측정된 데이터에 낙상 검출 학습 능력을 정량화하였다. 또한, 모델의 입력 값에 적용한 데이터 분할, 전처리 및 특징 추출 방법을 통해서 효율적인 낙상 검출을 위한 기계학습 관점에서의 타당성을 판단하고자 한다.

• Journal of agricultural medicine and community health
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• v.36 no.3
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• pp.167-178
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• 2011

Purpose: This study was done to identify the effects of a health diary program on fall related outcomes the low-income elderly women. Methods: The study was carried out with a nonequivalent control group with pretest-posttest design. The study was composed of two groups, each made up of 24 subjects: experimental group and control group. The subjects were low-income women aged over 65 years with osteoarthritis and both the experimental and control groups were made up of subjects with the same age profiles. The independent variable was the health diary program, and the dependent variables were fall related outcomes (fear of falling, fall-efficacy, knowledge of fall) difficulty of performing activity, and mood state. The health diary program was performed for 50 minutes each session and twice a week for 8 weeks. Data were collected before the health diary program 10 weeks after the beginning of the program. Results: The experimental group showed significant differences in knowledge of fall, fear of falling, and mood state compared to the control group. However there was no significant differences in difficulty of performing activity and fall efficacy. Conclusion: The results of this study may be used as part of an education to prevent falls for low-income elderly women with osteoarthritis.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.17-18
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• 2018

본 논문에서는 병실의 침대 위에서 움직임으로 침대 밖으로 떨어지는 것을 방지하기 위한 환자감시 시스템인 낙상 방지 시스템을 제안한다. 환자는 휴식을 취하거나 각종 처치를 위하여 침대에 머무르게 된다. 이 과정에서 대부분의 환자들은 기력이 낮아지고 자기 신체에 대한 제어 능력이 낮아져 침대의 바깥쪽으로 움직이는 경우가 종종 발생한다. 본 논문에서는 초음파를 이용한 환자까지의 거리 맵을 생성한 다음 거리 맵을 기반으로 환자의 위치를 추정하였다. 경과 측정거리는 10mm 이내로 측정이 가능하였고, 기존의 방식과 비교하여 내구성과 활용성이 우수하였다.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.1-9
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• 2012

As we are turnning into the aged society, accidents by falling down are increasing in the aged people's group. In this paper, we design the system with the 3-Axis acceleration sensor which is composed by a single chip. The body activity signal is measured with the signal detector and RF communicator in this proposed system and the and falling by the entering signal pattern analysis with 3-Axis acceleration sensor. For the RF communication, we are using nRF24L01p and 8bits ATmega uC for the processor. The error of energy expenditure estimation between motor driven treadmill and proposed a body activity module was 7.8% respectively. Human activities and falling is monitored according to analyze and judge the critical value of the Signal Vector. as falled down if they don't turn off the alarm after specific period and the aged person's after falling down activities are their position and more.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1384-1387
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• 2015

고령화 사회로 진입하면서 노인들은 노화과정에 의한 보행능력의 감소 및 근력 약화와 같은 신체적 변화로 인해 잦은 낙상을 경험한다. 이에 따라 낙상 사고를 감지하는 연구가 활발히 진행되고 있다. 낙상은 사전 예방도 중요하지만 사고 발생 후의 신속한 대처도 중요하다. 낙상을 감지하고 의료진에게 즉시 낙상정보를 제공하여 후속적 조치를 취하는 것은 사고 후 대처의 핵심이다. 본 논문에서는 스마트폰 환경에서 사용자의 낙상 후 방향을 판별하기 위해 두 가지 센서 데이터의 특정 값들을 추출하였으며, 이에 5 가지 기계학습 알고리즘을 적용하였다. 사용자는 스마트폰을 착용한 상태로 전후좌우 4 방향 낙상 실험을 진행하며 스마트폰 내에 내장된 3 축 가속도 센서와 3 축 자이로 센서값을 측정한다. 피험자 11 명을 대상으로 낙상 실험 결과, 5 가지의 분류기 중 k-NN에서 98.6%의 인식률을 나타내었다. 뽑아낸 특징 값과 분류 알고리즘은 낙상의 방향 검출에 유용한 것으로 판단된다.

• The Journal of Korean society of community based occupational therapy
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• v.2 no.2
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• pp.37-49
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• 2012

Objective : The purpose of this study is to investigate the effect of mental practice on increasing balance and fall index & fall efficacy scale of persons with post stroke. Method : As a single subject research design with multiple baseline across individuals, the patients were four stroke patients, employed in this study. The employed program included receiving mental practice, and measuring balance score changes using FRT for 4 weeks, including baseline and intervention periods. The subject's fall danger were measured by Fall Index Test(Tetrax) and Fall Efficacy Scale for balance ability were analyzed. The analyses were performed using visually and Two Standard Deviation Band Method. Result : Using FRT, the participants improved their standing balance. During the intervention periods, Their improvement of balance skills results in decreasing Fall Index increasing Fall Efficacy. Conclusion : As a result of this study, mental practice can be an effective method to improve the balance of stroke patien.