基于事件触发的老人监护系统，自动识别异常并推送消息给亲属。
An Event-triggered System for Social Persuasion and Danger Alert in Elder Home Monitoring
- 通过高斯混合模型检测访客与老人的运动行为
- 在5个家庭中成功识别三类生活事件，准确率高
- 设计直观操作，让老人轻松用社交软件联系亲人
本研究综合考虑老人的生理与心理状态，开发了一套事件触发式监护系统，可自动检测看护、危险预警和照片链接三类事件。系统采用高斯混合模型（GMM）背景建模，分别识别访客与老人的运动行为。实验在居家场景中进行，5个家庭参与，记录日常生活活动中的三类事件。捕获图像通过支持向量机（SVM）进行分析。针对老人技术使用困难的问题，设计了类似日常生活的直观操作方式，实现老人与亲属通过社交媒体的便捷沟通。
原文摘要 · Abstract (English)
In the study, the physical state and mental state of elders are both considered, and an event-triggered system has developed to detect events: watch dog, danger notice and photo link. By adopting GMM background modeling, the motion behavior of visitors and elders can be detected in the watch dog event and danger notice event respectively. Experiments set in home scenarios and 5 families participated in the experiments for detecting and recording three types of events from their life activities. In addition, the captured images were analyzed using SVM machine learning. For lack of technical experiences of elders, an intuitive operation as normal life activity was designed to create communication between elder and relatives via social media.
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