Extending Agent Based Telehealth Platform with Activities of Daily Living Reasoning Capabilities

2016 IEEE International Conference on Healthcare Informatics (ICHI)(2016)

引用 0|浏览19
暂无评分
摘要
In the future patients will have a more active role in strengthening and maintaining their own health. Telehealth can empower and motivate patients by giving them the chance to stay in their own homes instead of going to the hospital. A telehealth system is deployed in a patient's home hence it will influence his or her everyday live. Therefore we believe that a telehealth system shall adapt its behavior so that it will not be a burden for the patient/resident to use. To this aim we have extended an existing telehealth platform to reason about activities of daily living in a smart home scenario. The extensions have been tested on up to three of the CASAS datasets. The extensions are two algorithms: one for understanding the resident's everyday habits and one for predicting the resident's next activity. The prediction algorithm correctly predicts 69.76%, 73.06%, and 65.14% in the CASAS datasets.
更多
查看译文
关键词
ambient intelligence,activities of daily living,activity prediction,sequential prediction algorithm,case-based reasoning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要