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Fall Down Detection Under Smart Home System.
- Source :
-
Journal of Medical Systems . Oct2015, Vol. 39 Issue 10, p1-12. 12p. - Publication Year :
- 2015
-
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]
- Subjects :
- *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
Subjects
Details
- Language :
- English
- ISSN :
- 01485598
- Volume :
- 39
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- Journal of Medical Systems
- Publication Type :
- Academic Journal
- Accession number :
- 115925163
- Full Text :
- https://doi.org/10.1007/s10916-015-0286-3