An Efficient Design of a Machine Learning-Based Elderly Fall Detector.
Lecture Notes of the Institute for Computer Sciences, Social Informatics, and Telecommunications Engineering(2018)
摘要
Elderly fall detection is an important health care application as falls represent the major reason of injuries. An efficient design of a machine learning -based wearable fall detection system is proposed in this paper. The proposed system depends only on a 3 -axial accelerometer to capture the elderly motion. As the power consumption is proportional to the sampling frequency, the performance of the proposed fall detector is analyzed as a function of this frequency in order to determine the best trade-off between performance and power consumption. Thanks to efficient extracted features, the proposed system achieves a sensitivity of 99.73% and a specificity of 97.7% using a 40Hz sampling frequency notably outperforming reference algorithms when tested on a large dataset.
更多查看译文
关键词
Elderly fall detection,Micro electro mechanical system,Inertial measurement unit,Support vector machine,Multi-layer perceptron,K-nearest neighbors
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要