Reconstructing Missing Signals In Multi-Parameter Physiologic Data By Mining The Aligned Contextual Information

The PhysioNet Challenge 2010 is to recover missing segments of a particular signal in the given multi-parameter physiologic data set. In this paper we propose a contextual information based framework to achieve robust reconstruction. For a given target signal that is to be reconstructed, our algorithm intelligently choose among three sub-algorithms to best recover the missing segments. Experiments are carried out on the Physionet/CinC Challenge 2010 data sets. The results show that the proposed method is particularly effective on signals that have well aligned contextual signals.