Clustering Fetal Heart Rate Tracings by Compression

Abstract

Fetal heart rate (FHR) monitoring is widely used regarding the detection of fetuses in danger of death or damage. Thirty one FHR tracings acquired in the antepartum period were clustered by compression in order to identify abnormal ones. A recently introduced approach based on algorithmic information theory was used. The new method can mine patterns in completely different areas, without domain-specific parameters to set, and does not require specific background knowledge. At the highest level the FHR tracings were clustered according to an unanticipated feature, namely the technology used in signal acquisition. At the lower levels all tracings with abnormal or suspicious patterns were clustered together, independently of the technology used