Processing XXXX Composite Events in MAGPIE.

@entity1 @entity6 @entity102
UNASSIGNED: The focus of this research is in the definition of programmable expert Personal Health Systems (PHS) to monitor @entity1 affected by @entity102 using agent oriented programming and mobile computing to represent the interactions happening amongst the components of the system. The paper also discusses issues of knowledge representation within the medical domain when dealing with temporal patterns concerning the physiological values of the @entity1 . In the presented agent based PHS the doctors can personalize for each @entity1 monitoring rules that can be defined in a graphical way. Furthermore, to achieve better scalability, the computations for monitoring the @entity1 are distributed among their devices rather than being performed in a centralized server. The system is evaluated using data of 21 @entity6 @entity1 to detect temporal patterns according to a set of monitoring rules defined. The system's scalability is evaluated by comparing it with a centralized approach. The evaluation concerning the detection of temporal patterns highlights the system's ability to monitor chronic @entity1 affected by @entity6 . Regarding the scalability, the results show the fact that an approach exploiting the use of mobile computing is more scalable than a centralized approach. Therefore, more likely to satisfy the needs of next generation PHSs. PHSs are becoming an adopted technology to deal with the surge of @entity1 affected by @entity102 . This paper discusses architectural choices to make an agent based PHS more scalable by using a distributed mobile computing approach. It also discusses how to model the medical knowledge in the PHS in such a way that it is modifiable at run time. The evaluation highlights the necessity of distributing the reasoning to the mobile part of the system and that modifiable rules are able to deal with the change in lifestyle of the @entity1 affected by @entity102 .
