Abstract
Recording of maternal uterine pressure (UP) and fetal heart rate (FHR) during labour and delivery is a procedure referred to as cardiotocography (CTG). We model this as an input-output system to estimate its dynamics in terms of an impulse response function (IRF). CTG data is very noisy and missing data are common. In this paper, we identify the models using subspace methods, which incorporate noise-suppression and permit the use of non-contiguous data. Using contiguous data, the subspace method performed better than linear regression; more of the 57 CTG pathological records in our database were modelled (30 vs. 26). Allowing non-contiguous data, even more pathological records were modelled with this approach (49). Furthermore, the models were discriminating; compared to linear regression, the IRF gain showed statistically significant differences more often between normal and pathological records (in 15/18 vs. 10/18 epochs) over the final three hours of labour.
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