Model-based signal analysis and interpretation in the intensive care unit

This paper describes the architecture and functionality of a distributed intelligent signal analysis and interpretation system developed for the monitoring of neonates in the intensive care unit. In this system, named SIMON, various aspects of a monitoring task are performed by three independent modules running asynchronously: the feature extraction, the patient model, and the display modules. Central to SIMON is the notion of context sensitivity which permits the adaptation of the monitoring strategy in response to changes either in the patient state or in the monitoring equipment as well as the contextual interpretation of incoming data.