1. Fall Down Detection Under Smart Home System.
- Author
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Juang, Li-Hong and Wu, Ming-Ni
- Subjects
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ACCIDENTAL fall prevention , *ALGORITHMS , *COMPUTERS , *DIGITAL diagnostic imaging , *EMERGENCY medical services communication systems , *INTERNET , *POSTURE , *RESEARCH funding , *ROBOTICS , *SAFETY , *TECHNOLOGY , *VIDEO recording , *REMOTE access networks , *WIRELESS LANs , *HOME environment , *BODY movement , *DESCRIPTIVE statistics , *OLD age ,RESEARCH evaluation - Abstract
Medical technology makes an inevitable trend for the elderly population, therefore the intelligent home care is an important direction for science and technology development, in particular, elderly in-home safety management issues become more and more important. In this research, a low of operation algorithm and using the triangular pattern rule are proposed, then can quickly detect fall-down movements of humanoid by the installation of a robot with camera vision at home that will be able to judge the fall-down movements of in-home elderly people in real time. In this paper, it will present a preliminary design and experimental results of fall-down movements from body posture that utilizes image pre-processing and three triangular-mass-central points to extract the characteristics. The result shows that the proposed method would adopt some characteristic value and the accuracy can reach up to 90 % for a single character posture. Furthermore the accuracy can be up to 100 % when a continuous-time sampling criterion and support vector machine (SVM) classifier are used. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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