• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1751-1768
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• 2011

Falls are one of the most concerned accidents for elderly people and often result in serious physical and psychological consequences. Many researchers have studied fall detection techniques in various domain, however none released to a commercial product satisfying user requirements. We present a systematic modeling and evaluating procedure for best classification performance and then do experiments for comparing the performance of six procedures to get a statistical classifier based wrist-type fall detector to prevent dangerous consequences from falls. Even though the wrist may be the most difficult measurement location on the body to discern a fall event, the proposed feature deduction process and fall classification procedures shows positive results by using data sets of fall and general activity as two classes.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.123-125
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• 2022

본 논문에서는 Yolo-pose를 이용하여 장단기 메모리(Long short-term Memory)에 적용하는 시스템을 소개한다. 영상데이터로부터 Yolo-pose를 이용하여 일상생활과 낙상으로 구분된 데이터를 추출하여 LSTM에 적용하여 학습시킨다. 학습은 오버피팅을 방지하기 위하여 8대2의 Validation을 진행하며 Confusion matrix로 나타낸다. Yolo-pose의 결과값은 sensitivity와 specificity 모두 100%를 기록하여 일상생활과 낙상을 잘 구분하는 것을 확인 하였다.

• 한국정보통신학회논문지
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• 제12권2호
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• pp.401-406
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• 2008

낙상이 탈골, 골절, 치명적인 머리 부상이나 심지어 죽음과 같은 심각한 결과를 초래하기 때문에 낙상 사건 검출은 특히 혼자 사는 노인들에 대해 가장 일반적인 문제들 중의 하나이다. 낙상이나 낙상과 관련된 부상들을 방지하기 위해서 최근 몇몇 기존 비디오 센서 기반의 방법들은 낮은 낙상 검출율을 보여주고 있다. 낮은 검출율 문제를 개선하고 시스템 성능을 높이기 위해, 본 논문은 실시간 환경에서 연속하는 차영상 간의 차와 시간적 템플릿(temporal templates)을 이용한 노인들에 대한 새로운 낙상 사건 검출 방법을 제시하였다. 제안된 알고리즘은 비록 한 대의 USB PC 카메라에 의해 획득된 낮은 질의 비디오 시퀀스임에도 불구하고 96.43%의 성공적인 검출율과 3.125%의 낮은 false positive rate를 얻었다. 실험 결과는 높은 검출율과 낮은 false positive rate에 관한 매우 기대되는 성능을 보여주고 있다.

• PNF and Movement
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• 제22권1호
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• pp.43-54
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• 2024

Purpose: Falls among persons older than 65 years are a significant concern due to their frequency and severity. This study aimed to develop a vest-type embedded artificial intelligence (AI) system capable of detecting and predicting falls in various scenarios. Methods: In this study, we established and developed a vest-type embedded AI system to judge and predict falls in various directions and situations. To train the AI, we collected data using acceleration and gyroscope values from a six-axis sensor attached to the seventh cervical and the second sacral vertebrae of the user, considering accurate motion analysis of the human body. The model was constructed using a neural network-based AI prediction algorithm to anticipate the direction of falls using the collected pedestrian data. Results: We focused on developing a lightweight and efficient fall prediction model for integration into an embedded AI algorithm system, ensuring real-time network optimization. Our results showed that the accuracy of fall occurrence and direction prediction using the trained fall prediction model was 89.0% and 78.8%, respectively. Furthermore, the fall occurrence and direction prediction accuracy of the model quantized for embedded porting was 87.0 % and 75.5 %, respectively. Conclusion: The developed fall detection and prediction system, designed as a vest-type with an embedded AI algorithm, offers the potential to provide real-time feedback to pedestrians in clinical settings and proactively prepare for accidents.

• 한국전기전자재료학회논문지
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• 제29권11호
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• pp.676-680
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• 2016

This paper describes a low voltage detection circuit used in the semiconductor chips. The circuit was composed of a detection part of the CMOS structure as three stages and two inverters. The output of the low voltage detection circuit become to 'high' from 'low', when the power supply voltage falls below 80%. When the power supply voltage is 5 V, it was detected at 4 V point. The proposed low voltage detection circuit can be easily applied only by changing the resister and the capacitor without structural change in a wide range of power supply voltage.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 봄 학술발표회 논문집
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• pp.309-316
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• 1998

In this paper, a newly derived formulation of a crack detection model is presented and its feasibility to detect cracks in structures is verified experimentally. To meet this objective, the followig approach is utilized. Firstly, the crack detection scheme which consists of the damage localization model and the crack detection model is formulated. Secondly, the feasibility and practicality of the complete procedure of the crack detection model is evaluated by locating and sizing cracks in clamped-clamped beams for which a f3w modal parameters were measured for sixteen uncracked and cracked states. Major results observed from the crack detection exercises include that far most damage cases, the predicted crack locations falls within very close to the inflicted locations of cracks in the test beam and the size of crack values estimated at the predicted locations are very close to the inflicted magnitudes.

• Transactions on Electrical and Electronic Materials
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• 제8권6호
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• pp.293-298
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• 2007

The aged are faced with increasing risk for falls. The aged have more fragile bones than others. When falls occur, it is important to detect this emergency state because such events often lead to more serious illness or even death. A implementation of PDA system, for detection of emergency situation, was developed using 3-axis accelerometer in this paper as follows. The signals were acquired from the 3-axis accelerometer, and then transmitted to the PDA through a Bluetooth module. This system can classify human activity, and also detect an emergency state like falls. When the fall occurs, the system generates the alarm on the PDA. If a subject does not respond to the alarm, the system determines whether the current situation is an emergency state or not, and then sends some information to the emergency center in the case of an urgent situation. Three different studies were conducted on 12 experimental subjects, with results indicating a good accuracy. The first study was performed to detect the posture change of human daily activity. The second study was performed to detect the correct direction of fall. The third study was conducted to check the classification of the daily physical activity. Each test lasted at least 1 min. in the third study. The output of the acceleration signal was compared and evaluated by changing various postures after attaching a 3-axis accelerometer module on the chest. The newly developed system has some important features such as portability, convenience and low cost. One of the main advantages of this system is that it is available at home healthcare environment. Another important feature lies in its low cost of manufacture. The implemented system can detect the fall accurately, so it will be widely used in emergency situations.

• 한국멀티미디어학회논문지
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• 제21권3호
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• pp.382-390
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• 2018

A major accident occurring on the bed is falls that occur during at times when the care of nurses or protectors is inadequate, which is fatal to patients or the elderly. In particular, Enuresis or sleepiness caused by sleep apnea increases the risk of falls. Therefore, it is very important to detect falls and sleep apnea of patients without infringing privacy in the bed to patient's safety and accident prevention. In this paper, we reviewed the technologies developed for bed monitoring and implemented a non-intrusive monitoring system. The Occupancy Sensor allows the temperature of the bed and surrounding area to be extracted to enable track of the patient's motion. The Doppler Radar detects the patient's movements at normal times and the respiration state when patients have no movement during sleeping. It is specially designed for real-time monitoring of falling and respiration during sleeping through contactless multi-sensing while solving patient's privacy problems.

• Physical Therapy Rehabilitation Science
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• 제10권2호
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• pp.185-196
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• 2021

Objective: Falling is one of main accident to facilitate the physical injuries in order adults. The purpose of the systematic review was to determine the effects of postural balance training whether the recovery of falls in elderly with normal physical function or not throughout summing the selected studies quantitatively. Design: A systematic review Methods: MEDLINE and other four databases were searched up to April 20, 2021 and randomized controlled trials (RCTs) evaluating postural balance approaches on fall risks in elderly. The researched studies excluded the double studies, titles and abstract, and finally full-reported study. The selected RCTs studies were extracted characteristics of the studies and summary of results based on PICOS-SD (population, intervention, comparison, outcomes, and setting- study design) model to synthesize the papers qualitatively. Results: The review involved 22 RCT reports with 4,847 community older adults aged 65 years or over. Nineteen of the selected RCT studies reported dual or multimodal exercises show the beneficial effect for older adults compared to one-type treatment or no intervention. All of selected showed low risk in the selection, attrition, and reporting bias. However, detection bias showed low risk at 75% records of the involved RCTs and performance bias was low risk at only three records. Conclusions: The results of the systematic review propose that a standardized therapeutic approach and the intensity are needed for improving risk of falls in older adults.

• 로봇학회논문지
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• 제19권2호
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• pp.213-220
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• 2024

Fall detection and prevention technologies play a pivotal role in ensuring the well-being of individuals, particularly those living independently, where falls can result in severe consequences. This paper addresses the challenge of accurate and quick fall detection by proposing a Bayesian probability-based measure applied to surface electromyography (sEMG) signals. The proposed algorithm based on a Bayesian filter that divides the sEMG signal into transient and steady states. The ratio of posterior probabilities, considering the inclusion or exclusion of the transient state, serves as a scale to gauge the dominance of the transient state in the current signal. Experimental results demonstrate that this approach enhances the accuracy and expedites the detection time compared to existing methods. The study suggests broader applications beyond fall detection, anticipating future research in diverse human-robot interface benefiting from the proposed methodology.