Cardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'.
Cardiotocograph (CTG) is widely used in everyday clinical practice for fetal surveillance, where it is used to record fetal heart rate (FHR) and uterine activity (UA). These two biosignals can be used for antepartum and intrapartum fetal monitoring and are, in fact, nonlinear and non-stationary. CTG recordings are often corrupted by artifacts such as missing beats in FHR, high-frequency noise in FHR and UA signals. In this paper, an empirical mode decomposition (EMD) method is applied on CTG signals. A recursive algorithm is first utilized to eliminate missing beats. High-frequency noise is reduced using EMD followed by the partial reconstruction (PAR) method, where the noise order is identified by a statistical method. The obtained signal enhancement from the proposed method is validated by comparing the resulting traces with the output obtained by applying classical signal processing methods such as Butterworth low-pass filtering, linear interpolation and a moving average filter on 12 CTG signals. Three obstetricians evaluated all 12 sets of traces and rated the proposed method, on average, 3.8 out of 5 on a scale of 1(lowest) to 5 (highest).
100 patients were registered at the Diabetic Clinic in 1981, where they were managed by a team of physician, obstetrician and paediatrician, based on a preset protocol. Only 92 patients were eventually analysed. The study showed a 1.3% incidence of pregnancies complicated by diabetes mellitus. The mean birthweights of infants of both gestational and established diabetics were heavier than that of the general population by race and gestation. 25% of the 92 infants of diabetic mothers have birthweight exceeding the 90th centile of population. Further division of the 92 patients into the "true gestational" diabetics, as shown by an oral glucose tolerance test performed 6 weeks post-natally, also showed a 25% incidence of macrosomia. Late antenatal booking, delayed detection of abnormal glucose tolerance and treatment attributed to the high incidence of macrosomia. Only one infant had birthweight below the tenth centile. There were no perinatal mortality in the 92 patients studied. Macrosomia is a common complication in infants of diabetic mothers despite a physician-obstetrician joint-care system. Also, the risk of having macrosomia amongst gestational diabetics is high.