Department of Civil Engineering, and The Key Lab of Digital Signal and Image Processing of Guangdong Province, Shantou University, Guangdong, People's Republic of China,
J Med Syst. 2015 Oct;39(10):107. doi: 10.1007/s10916-015-0286-3. Epub 2015 Aug 15.
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.
医疗技术是老年人口的必然趋势，因此智能家居护理是科技发展的一个重要方向，特别是老年人居家安全管理问题变得越来越重要。在这项研究中，提出了一种低运算算法，并使用三角模式规则，然后可以通过在家中安装带有摄像头的机器人快速检测人形跌倒动作，从而能够实时判断家中老年人的跌倒动作。本文将介绍一种初步设计和实验结果，该实验利用图像预处理和三个三角质心点来提取特征，从身体姿势上检测跌倒动作。结果表明，所提出的方法将采用一些特征值，准确率可达单个字符姿势的 90%。此外，当采用连续时间采样标准和支持向量机 (SVM) 分类器时，准确率可达 100%。
