Abstract
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.
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