SPN-model based simulation of a wearable health monitoring system.
The deployment of Wearable Health Monitoring Systems (WHMS) can potentially enable ubiquitous and continuous monitoring of a patient's physiological parameters. Moreover by incorporating multiple biosensors in such a system a comprehensive estimation of the user's health condition can possibly be derived. In this paper we present a Stochastic Petri Net (SPN) model of a multi-sensor WHMS along with a corresponding simulation framework implemented in Java. The proposed model is built on top of a previously published multisensor data fusion strategy, which has been expanded in this work to take into account synchronization issues and temporal dependencies between the measured bio-signals.
Pantelopoulos
Alexandros
A
Assistive Technologies Research Center, Wright State University, Dayton, Ohio 45435, USA. pantelopoulos.2@wright.edu
Bourbakis
Nikolaos
N
D000465:Algorithms; D003020:Clothing; D003661:Decision Support Techniques; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D018670:Monitoring, Ambulatory / Q000379:methods*; D016571:Neural Networks, Computer