• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.393-395
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• 2013

In modern society, the elderly over 65 years old are increasing due to development of medical technology and improvement of their standard of living. Severe fall of the elderly can lead to death threats. To solve this problem, several algorithms and hardware systems for fall detection have been studied and developed. In this paper, a fall detection system using 3-axial acceleration sensor is presented. In the fall detection system, several types of fall-feature parameters are calculated and then the fall is determined by using them. Using this system, best sensitivity and specificity are 98.3% and 94.7%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2101-2108
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• 2014

Automatic fall-detection algorithms using video-data are proposed. Six types of fall-feature parameters are defined applying the optical flows extracted from differential images to principal component analysis(PCA). One fall-detection algorithm is the simple threshold method that a fall is detected when a fall-feature parameter is over a threshold, another is to use the HMM, and the other is to combine the simple threshold and HMM. Comparing the performances of three types of fall-detection algorithm, the algorithm combining the simple threshold and HMM requires less computational resources than HMM and exhibits a higher accuracy than the simple threshold method.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.356-358
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• 2013

본 논문은 3축 가속도 센서를 이용한 낙상 감지 시스템의 3가지 알고리즘을 제안한다. 낙상감지시스템은 3축 가속도 센서 데이터로부터 계산한 낙상 파라미터인 가속도 크기와 각도를 이용한다. 제안한 낙상감지시스템의 성능평가를 위해서 남자 2명과 여자 2명에 대해서 4가지 일상생활과 3가지 낙상상황에서 560개 데이터 값을 얻은 후에 3 가지의 알고리즘을 적용하여 최대 98.33%의 sensitivity와 94.37%의 specificity 결과를 얻었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.287-288
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• 2023

우리 사회가 고령화시대로 접어들면서 낙상은 매우 심각한 사회문제가 되고 있으며 정확한 낙상 감지 기술의 수요도 늘고 있다. 본 연구는 웹 캠을 이용한 개선된 낙상감지 기법을 제안한다. 제안하는 기법은 RGB 영상을 기반으로 스켈레톤 포즈 추출, 데이터 가공, GRU(Gated Recurrent Unit) 신경망 알고리즘을 적용한 낙상 감지 실험 및 감지 결과 분석의 과정이 포함된다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.38-44
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• 2016

In this paper, Author of this article presents a system to ensure the safety of residents in case the residents occurs an fall situation. Author of this article use weighted difference image and motion vector. Proposed system suggested the fall detection algorithm using weighted difference image and motion vector. Fall detection algorithm showed a success rate of 85% ~ 97.1% through 150 experiments. Proposed algorithm showed a litter higher or similar success rate than the existing camera based system.

• 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 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.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.2
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• pp.31-37
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• 2016

Falling situations are extremely critical events for the elderly person who requires timely and adequate emergency service. For the case of emergency, the information of falling and its direction can be used as an important information for the first aid treatment of the injured person. In this paper, a falling detection system which can pinpoint the falling event with the falling direction is implemented. In order to detect the fall situation, a single gyroscope (MPU-6050) is used in the developed system. The fall detection algorithm that can classify 8 different fall directions such as front, back, left, right and in between falls is proposed. The direction of the fall is decided by examining the acceleration values of X and Y directions of the sensor. It is shown that the proposed algorithm successfully detects the falling event and the falling direction with probability of 97% for a selected value of acceleration threshold.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2546-2553
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• 2015

Falling can happen to anyone, anywhere at anytime and especially it is one of the risk factor that can lead causes of death of persons aged 65 and over. Recently, the study of fall detection mechanisms as a smart healthcare service based on the IoT(Internet of Things) are being actively investigated. In this paper, we implement a fall detection system using arduino as a smart sensor communicates with a smart device. When transmitting the information of the acceleration on a sensor smart sensor with a BLE(Bluetooth Low Energy), the smart device processing and analyzing this information. and determines a fall situation. A fall detection system based on the Internet of Things which using smart sensor and smart device, has the advantage of being able to overcome the mobility and portability constraints.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.781-788
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• 2013

In this paper, we introduce a quadruped robot-based alarm system for monitoring the emergency situation due to falling in the elderly. Quadruped robot includes the FPGA Board(Field Programmable Gate Array) applying a red-color tracking algorithm. To detect a falling of the elderly, a sensor node is worn on chest and accelerations and angular velocities measured by the sensor node are transferred to quadruped robot, and then the emergency signal is transmitted to manager if a fall is detected. Manager controls the robot and then he judges the situation by monitoring the real-time images transmitted from the robot. If emergency situation is decided by the manager, he calls 119. When the fall detection system using only sensor nodes is used, sensitivity of 100% and specificity of 98.98% were measured. Using the combination of the fall detection system and portable camera (robot), the emergency situation was detected to 100 %.