S. Guid Oei

Bio: S. Guid Oei is an academic researcher from Eindhoven University of Technology. The author has contributed to research in topics: Pregnancy & Uterine Monitoring. The author has an hindex of 25, co-authored 93 publications receiving 1899 citations.

External cephalic version: a safe procedure? A systematic review of version-related risks

Abstract: Background. The Term Breech Trial has considerably increased the number of cesareans. External cephalic version (ECV) might be an effective method of lowering the rate of cesareans; its efficacy has been well established. However, although in the absence of anesthesia the risks are thought to be low, most studies have used populations too small to allow definite conclusions on version-related risks. Methods. In an attempt to make an inventory of these risks, we have systematically analyzed 44 studies, covering a total of 7377 patients from 1990 to 2002. The studies used were derived from a Medline and Embase search. Results. The most frequently reported complications were transient abnormal cardiotocography (CTG) patterns (5.7%). Persisting pathological CTG readings (0.37%) and vaginal bleeding occur rarely (0.47%). The incidence of placental abruption was even lower, at 0.12%. Fetomaternal transfusion was absent in five out of seven studies, with a mean incidence of 3.7%. Emergency cesareans were performed in 0.43% of all versions. Perinatal mortality was 0.16%. Conclusions. External cephalic version seems to be a safe procedure.

Estimation of internal uterine pressure by joint amplitude and frequency analysis of electrohysterographic signals.

Abstract: Monitoring the uterine contraction provides important prognostic information during pregnancy and parturition. The existing methods employed in clinical practice impose a compromise between reliability and invasiveness. A promising technique for uterine contraction monitoring is electrohysterography (EHG). The EHG signal measures the electrical activity which triggers the contraction of the uterine muscle. In this paper, a non-invasive method for intrauterine pressure (IUP) estimation by EHG signal analysis is proposed. The EHG signal is regarded as a non-stationary signal whose frequency and amplitude characteristics are related to the IUP. After acquisition in a multi-channel configuration, the EHG signal is therefore analyzed in the time–frequency domain. A first estimation of the IUP is then derived by calculation of the unnormalized first statistical moment of the frequency spectrum. The estimation accuracy is finally increased by identification of a second-order polynomial model. The proposed method is compared to root mean squared analysis and optimal linear filtering and validated by simultaneous measurement of the IUP on nine women during labor. The results suggest that the proposed EHG signal analysis provides an accurate estimate of the IUP.

Low-complexity R-peak detection for ambulatory fetal monitoring

Abstract: Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

Using Multivariate Statistics

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Handbook Of Psychological Testing

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