Objectives: To determine how different mathematical time series approaches can be implemented for the detection of qualitative patterns in physiologic monitoring data, and which of these approaches could be suitable as a basis for future bedside time series analysis.

Intelligent alarm systems are needed for adequate bedside decision support in critical care. Clinical information systems acquire physiological variables online in short time intervals. To identify complications as well as therapeutic effects procedures for rapid classification of the current...

As high dimensional data occur as a rule rather than an exception in critical care today, it is of utmost importance to improve acquisition, storage, modelling and analysis of medical data, which appears feasible only with the help of bedside computers. The use of clinical information systems...

Objectives: Time series analysis techniques facilitate statistical analysis of variables in the course of time. Continuous monitoring of the critically ill in intensive care offers an especially wide range of applications. In an open clinical study time series analysis was applied to the...

In critical care extremely high dimensional time series are generated by clinical information systems. This yields new perspectives of data recording and also causes a new challenge for statistical methodology. Recently graphical correlation models have been developed for analysing the partial...

Clinical information systems can record numerous variables describing the patient’s state at high sampling frequencies. Intelligent alarm systems and suitable bedside decision support are needed to cope with this flood of information. A basic task here is the fast and correct detection of...

Operational protocols are a valuable means for quality control. However, developing operational protocols is a highly complex and costly task. We present an integrated approach involving both intelligent data analysis and knowledge acquisition from experts that supports the development of...

In modern intensive care physiological variables of the critically ill can be reported online by clinical information systems. Intelligent alarm systems are needed for a suitable bedside decision support. The existing alarm systems based on fixed treshholds produce a great number of false...

Im Rahmen des Projektes ?Zeitreihenanalytische Methoden zur Behandlung von Online-Monitoring-Daten aus der Intensivmedizin? im Sonderforschungsbereich 475 wird eine klinische Studie zur Evaluierung und zum Vergleich von Alarm-Algorithmen für die Patientenüberwachung auf Intensivstationen...