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EN
We are developing Data Stream Management System that can be applied in medical monitoring system. One of the problems is how to support efficient data access methods. This paper considers indexing issues in data management system. The indexing is a commonly used method of data access acceleration. Classical and new streaming methods of indexing have been presented. The method was developed in data stream management system and first applied in a centralized neonatal monitoring system.
EN
Fetal monitoring system belongs to signal processing system class. The main functions of the system are signal acquisition from bedside monitors, on-line trace analysis and dynamic presentation of incoming data. Collected data set is controlled by centralised application. Relational database management system cannot process samples of high frequency biomedical signals on-line. Therefore, we decide to build our own data management system dedicated to stream processing that support continuous query. This paper describes a method of building a query plan based on proposed algebra. The presented example of application enables implementation of algorithm determining long- and short-term indices for fetal heart rate variability assessment on the basis of declarative query language. Our solution enables to define query based on data streams that make the updated answers currently available.
EN
The paper presents the algebra and declarative query language developed for fetal monitoring system MONAKO. At present, the system architecture is centralised. Recording, analyzing and visualization of data are carrying out in the central unit. Therefore, the system cannot scale in a simple manner. Presented solution enables to define query based on data streams that makes the updated answers currently available. Applying database management system that carries out its tasks based on presented assumptions enables the construction of monitoring system of distributed architecture
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