Extraction of a local linear trend from physiological time series

We discuss methods for robust signal extraction from noisy physiological time series as measured in intensive care. The aim is a method which allows a fast and reliable de-noising of the data and separation of artifacts from relevant changes in the patients condition. For approximating local linear trends we use robust regression estimators. We examine the performance of the L1 regression, the repeated median and the least median of squares for this task.