首页> 外文会议>Learning and Technology Conference >IoT based mobile healthcare system for human activity recognition
【24h】

IoT based mobile healthcare system for human activity recognition

机译:基于机置的人类活动认可的移动医疗保健系统

获取原文

摘要

Developments in information and communication technologies have led to the wider usage of Internet of Things (IoT). In the modern health care applications, the usage of IoT technologies brings physicians and patients together for automated and intelligent daily activity monitoring for elderly people. Mobile devices and wearable body sensors are gradually implemented for the monitoring of personal health care and wellbeing. One of the main technologies of IoT improvements in healthcare monitoring system is the wearable sensor technology. Furthermore, integration of IoT in healthcare has led to initiate smart applications such as mobile healthcare (m-Healthcare) and intelligent healthcare monitoring systems. In this study an intelligent m-healthcare system based on IoT technology is presented to provide pervasive human activity recognition by using data mining techniques. In this paper, we present a user-dependent data mining approach for off-line human activity classification and a robust and precise human activity recognition model is developed based on IoT technology. The proposed model utilizes the dataset contains body motion and vital signs recordings for ten volunteers of diverse profile while performing 12 physical activities for human activity recognition purpose. Results show that the proposed system is superior in performance with 99.89 % accuracy and is highly effective, robust and reliable in delivering m-Healthcare services during different activities.
机译:在信息和通信技术的发展导致了物联网(IOT)的更广泛的使用。在现代医疗保健应用,物联网技术的使用对老年人的自动化和智能化的日常活动监控带来了医生和病人在一起。移动设备和可穿戴式人体感应正在逐渐用于个人保健和健康监测实施。一个物联网改进医疗监控系统的主要技术是可穿戴式传感器技术。此外,物联网在医疗卫生一体化已导致启动的智能应用,如移动医疗(M-医疗保健)和智能医疗监控系统。在这项研究中提出了一种基于物联网技术的智能M-医疗系统通过使用数据挖掘技术来提供普遍的人类活动的认可。在本文中,我们提出了基于物联网技术开发了离线人类活动的分类和一个强大的和精确的人类活动识别模型依赖于用户的数据挖掘方法。该模型利用数据集包含人体运动和生命体征的记录为不同的配置文件的十位志愿者在进行人类活动识别目的12个的体力活动。结果表明,该系统在性能上优于与99.89 %的准确性和高效,强大和可靠的过程中不同的活动提供M-医疗健康服务。

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