论文标题
基于从用户运动学习的个性化秋季检测监测系统
Personalized fall detection monitoring system based on learning from the user movements
论文作者
论文摘要
显示个性化的秋季检测系统可提供添加的额外，并与当前的秋季检测系统相比。个性化模型也可以应用于很难收集一类数据的任何东西。结果表明，适应用户需求，提高系统的整体准确性。未来的工作包括在用户上检测智能手机，以便用户可以将系统放置在身体上的任何位置并确保其检测到。即使准确性不是100％，个性化概念证明也可以用于实现更高的准确性。本文中使用的个性化概念也可以扩展到医学领域的其他研究，也可以扩展到特定类别的数据。应该研究对特征提取和特征选择模块的更多研究。对于特征选择模块，更多地研究基于一个类数据的功能。
Personalized fall detection system is shown to provide added and more benefits compare to the current fall detection system. The personalized model can also be applied to anything where one class of data is hard to gather. The results show that adapting to the user needs, improve the overall accuracy of the system. Future work includes detection of the smartphone on the user so that the user can place the system anywhere on the body and make sure it detects. Even though the accuracy is not 100% the proof of concept of personalization can be used to achieve greater accuracy. The concept of personalization used in this paper can also be extended to other research in the medical field or where data is hard to come by for a particular class. More research into the feature extraction and feature selection module should be investigated. For the feature selection module, more research into selecting features based on one class data.
