...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Mobile networks & applications >Activity Recognition for Context-aware Hospital Applications: Issues and Opportunities for the Deployment of Pervasive Networks
【24h】

Activity Recognition for Context-aware Hospital Applications: Issues and Opportunities for the Deployment of Pervasive Networks

机译：情境感知型医院应用的活动识别：普适网络部署的问题和机遇

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Hospitals are convenient settings for the deployment of context-aware applications. The information needs of hospital workers are highly dependent on contextual variables, such as location, role and activity. While some of these parameters can be easily determined, others, such as activity are much more complex to estimate. This paper describes an approach to estimate the activity being performed by hospital workers. The approach is based on information gathered from a workplace study conducted in a hospital, in which 196 h of detailed observation of hospital workers was recorded. Contextual information, such as the location of hospital workers, artifacts being used, the people with whom they collaborate and the time of the day, is used to train a back propagation neural network to estimate hospital workers activities. The activities estimated include clinical case assessment, patient care, preparation, information management, coordination and classes and certification.The results indicate that the user activity can be correctly estimated 75% of the time (on average) which is good enough for several applications. We discuss how these results can be used in the design of activity-aware applications, arguing that recent advances in pervasive and networking technologies hold great promises for the deployment of such applications.
机译：医院是用于部署上下文感知应用程序的便捷设置。医院工作人员的信息需求高度依赖于上下文变量，例如位置，角色和活动。尽管其中一些参数可以轻松确定，但其他参数（例如活动）的估算要复杂得多。本文介绍了一种估算医院工作人员正在从事的活动的方法。该方法基于在医院进行的工作场所研究中收集到的信息，其中记录了196小时对医院工作人员的详细观察。上下文信息，例如医院工作人员的位置，所使用的人工物品，与他们合作的人员以及一天中的时间，都可以用来训练反向传播神经网络来估计医院工作人员的活动。估计的活动包括临床病例评估，患者护理，准备，信息管理，协调以及分类和认证。结果表明，可以正确估计75％的时间（平均）正确估计用户活动，足以满足多种应用程序的需要。我们讨论了如何在活动感知型应用程序的设计中使用这些结果，并认为无处不在和网络技术的最新进展为此类应用程序的部署带来了广阔前景。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号