Middleware Infrastructure for Monitoring Bed Activity

This work describes a service-oriented middleware platform for ambient-assisted living and its use in two different bed-activity services: preventing bedsore and monitoring sleep. It includes detailed description of the middleware platform, its elements and interfaces, as well as a service that can classify typical user bed positions. The key idea behind our work is to leverage wireless sensor networks by collecting the received signal strength (RSS) measured among fixed general-purpose wireless devices, deployed in the environment, and a wearable one. The use of middleware infrastructure that can provide data from any kind of sensor installed at the assisted person's home is essential for ambient assisted living (AAL) applications where context information can be shared among different services. The objective of this work is to provide a middleware infrastructure for the rapid prototyping of applications of ambient intelligence (AMI) for healthcare and AAL, with a certain degree of dependability. In particular, we propose a bed position detection service that is the input for other two important services, namely bedsore prevention and sleep monitoring services. These are the core services for bed activity monitoring service (1) providing inputs for further analysis by other AAL services. Wireless sensor networks (WSNs) are supposed to be widely deployed in indoor settings and on people's bodies in tomorrow's pervasive computing environments. The proposed system leverages the presence of WSNs by collecting the received signal strength (RSS) measured among fixed general purpose wireless devices, deployed in the environment, and a wearable one. The RSS measurements are used to classify a set of user's positions in the bed, monitoring the activities of the user, and thus supporting the bedsores and the sleep monitoring issues. The proposed component-based architecture lets developers use services in a modular way. Future services will be able to use the data produced by the bed position detection service without rewriting a new ad hoc component. Bedsore prevention service: Nursing homes require caregivers that ideally observe the elderly around the clock to prevent bedsores. The caregivers have to provide a high degree of surveillance and attendance to the elderly all the time. Moreover, the knowledge and personality of caregivers affect the quality of nursing care. The most widely accepted ways of preventing bedsores is to actively turn the