Flow-Based Situation-Aware Approach for eHealth Data Processing

A major challenge for remote patient monitoring (RPM) systems is processing data collected from a large number of healthcare devices and developing suitable algorithms and approaches to react accordingly to a wide spectrum of situations of interest, which must be properly detected. Flow-based programming, whose operation is based on state changes, is a promising approach to overcome this challenge, facilitating the personalization of data processing according to patients' health conditions. However, this approach is not suited to the detection of complex contextual situations, thereby hindering its adoption in RPM systems for data processing. In this regard, we propose an approach that combines situation awareness and flow-based programming to widen the capability of RPM systems to handle many-sided scenarios, which requires the monitoring of complex patient healthcare conditions. An evaluation of the proposed approach was conducted to demonstrate the flexibility of the solution for processing heterogeneous health information.