IEEE J Biomed Health Inform. 2015 Mar;19(2):752-60. doi: 10.1109/JBHI.2014.2326604. Epub 2014 May 22.
An ever-growing range of wireless sensors for medical monitoring has shown that there is significant interest in monitoring patients in their everyday surroundings. It however remains a challenge to merge information from several wireless sensors and applications are commonly built from scratch. This paper presents a middleware targeted for medical applications on smartphone-like platforms that relies on an event-based design to enable flexible coupling with changing sets of wireless sensor units, while posing only a minor overhead on the resources and battery capacity of the interconnected devices. We illustrate the requirements for such middleware with three different healthcare applications that were deployed with our middleware solution, and characterize the performance with energy consumption, overhead caused for the smartphone, and processing time under real-world circumstances. Results show that with sensing-intensive applications, our solution only minimally impacts the phone's resources, with an added CPU utilization of 3% and a memory usage under 7 MB. Furthermore, for a minimum message delivery ratio of 99.9%, up to 12 sensor readings per second are guaranteed to be handled, regardless of the number of applications using our middleware.
越来越多的用于医疗监测的无线传感器表明，人们对在日常环境中监测患者有着浓厚的兴趣。然而，将来自多个无线传感器的信息融合在一起仍然是一个挑战，并且应用程序通常是从头开始构建的。本文提出了一种针对智能手机平台上的医疗应用的中间件，该中间件基于事件设计，能够灵活地与不断变化的无线传感器单元集进行耦合，同时对互联设备的资源和电池容量的开销很小。我们使用我们的中间件解决方案部署了三个不同的医疗保健应用程序来说明这种中间件的需求，并根据能量消耗、智能手机造成的开销和实际情况下的处理时间来描述其性能。结果表明，对于感应密集型应用程序，我们的解决方案对电话资源的影响很小，仅增加了 3%的 CPU 利用率和不到 7MB 的内存使用。此外，对于 99.9%的最小消息传递比率，无论使用我们中间件的应用程序数量如何，都可以保证每秒处理多达 12 个传感器读数。
