Effect of signal acquisition method on the fetal heart rate analysis with phase rectified signal averaging. (24th November 2016) - van Scheepen, J A M; Koster, M P H; Vasak, B; Redman, C; Franx, A; Georgieva, A
Abstract: Phase rectified signal averaging (PRSA) is increasingly used for fetal heart rate (FHR) monitoring, both with traces acquired with external Doppler cardiotocography (D-FHR), and with transabdominal fetal electrocardiography (ta-FHR). However, it is unclear to what extend the acquisition method influences the PRSA analysis, whether results from using one acquisition method are comparable to those based on FHR acquired by the other method, and if not, which should be the preferred method. To address these questions, we applied PRSA analysis to 28 antepartum synchronous recordings of the FHR using simultaneously D-FHR and ta-FHR. The data included late-onset intrauterine growth restricted (IUGR) fetuses ( n   =  20) and non-IUGR fetuses ( n   =  8), all of them at gestation  ⩾34 weeks. PRSA analysis depends on two parameters intrinsic to the algorithm, T and S . We analyzed the data using parameters that included all values adopted by other researchers previously (derived from a literature search in PubMed and Google Scholar). T and S were adjusted for the difference in acquisition techniques. We found that the correlation between PRSA analysis based on D-FHR and ta-FHR decreased with decreasing values of the PRSA parameters T and S . Therefore, the acquisition technique affects PRSA values for high resolution PRSA (low values of T and S ). In conclusion, for low resolution PRSA, the results from both acquisition methods are comparable. Because ta-FHR signals provide beat to beat data and thus capture more subtle differences in the heart rate variation than D-FHR signals (pre-processed by commercial monitors), we assumed that ta-FHR may provide potentially valuable extra information compared to D-FHR. However, no parameter settings or acquisition method seemed to have a diagnostic value for identifying the late-onset IUGR babies in our dataset.