  We study properties of the human electrocardiogram under the working
hypothesis that fluctuations beyond the regular structure of single cardiac
cycles are unpredictable. On this background we discuss the possibility to use
the phase space embedding method for this kind of signal. In particular, the
specific nature of the stochastic or high dimensional component allows to use
phase space embeddings for certain signal processing tasks. As practical
applications, we discuss noise filtering, fetal ECG extraction, and the
automatic detection of clinically relevant features. The main purpose of the
paper is to connect results of embedding theory which had not been previously
applied in practise, and practical applications which had not yet been
justified theoretically.
