Advanced signal processing techniques for CTG analysis

The paper aims at presenting and discussing some key points about the analysis of fetal heart rate (FHR) recorded by means of CardioTocographv (CTG). Starting from a brief history of CTG computerized analysis, the paper describes how the integration of various computational methods for extracting reliable parameters from FHR variability can help the pre natal diagnosis. The approaches adopted for the analysis are briefly illustrated, considering both traditional time domain parameters as well as new indices in the nonlinear field such as entropy measures, complexity parameters and indices derived from phase rectified signal averaging method. IUGR fetuses can be separated from Normal ones by parameters with high levels of significance. Moreover, collecting few of them allow obtaining classification models able to provide correct classification for more than 90% fetuses. Results obtained from Normal and IUGR populations of fetuses show that i) the integration of linear and nonlinear parameters provide reliable indications about pathophysiologic fetal states; ii) could support early clinical diagnosis of fetal pathologies; iii) should be considered to design novel fetal monitoring systems.