A high-availability architecture for continuous monitoring of sleep disorders.

We present a complete technical solution for continuously monitoring vital signs required for observing sleep apnoea events, one of the major sleep respiratory disorders. Based on industry accepted medical devices, we developed a GSM-based remote data acquisition and transfer module that is integrated via a set of web services into the server side of the application. The back-end is responsible with aggregating all the data, and, based on machine learning techniques, it provides a first level of filtering in order to warn about possible abnormalities. The proposed solution is currently under the test phase at the "Victor Babes" Hospital in Timisoara, Romania.