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IoT based mobile healthcare system for human activity recognition

机译:基于物联网的移动医疗系统,用于人类活动识别

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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:信息和通信技术的发展导致物联网(IoT)的广泛使用。在现代医疗保健应用中,物联网技术的使用将医生和患者聚集在一起,以自动,智能地监视老年人的日常活动。移动设备和可穿戴式人体传感器已逐渐用于监控个人健康和福祉。可穿戴式传感器技术是医疗监控系统中IoT改进的主要技术之一。此外,物联网在医疗保健中的集成已导致启动智能应用程序,例如移动医疗保健(m-Healthcare)和智能医疗保健监控系统。在这项研究中,提出了一种基于物联网技术的智能移动医疗系统,以通过使用数据挖掘技术提供广泛的人类活动识别。在本文中,我们提出了一种用于离线人类活动分类的基于用户的数据挖掘方法,并基于物联网技术开发了一种鲁棒而精确的人类活动识别模型。所提出的模型利用了包含十名不同轮廓的志愿者的身体运动和生命体征记录的数据集,同时执行了十二项体育活动以实现人类活动识别的目的。结果表明,所提出的系统性能优越,准确度达99.89%,在不同活动期间提供m-Healthcare服务的效率高,功能强大且可靠。

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