Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

The fetal heart rate (FHR) is monitored during labor to assess fetal health. Both visual and computerized interpretations of the FHR depend on assigning a baseline to detect key features such as accelerations or decelerations. However, it is sometimes impossible to assign a baseline reliably, by eye or by numerical methods. To address this issue, we used the Oxford Intrapartum FHR Database to derive an algorithm based on the distribution of the FHR that detects heart rate intervals without a clear baseline. We aimed to recognize when a fetus cannot maintain its heart rate baseline and use this to assist computerized FHR analysis. Twenty-three FHR windows (15 min long) were used to develop the method. The algorithm was then validated by comparison with experts who classified 50 FHR windows into two groups: baseline assignable or un-assignable. The average agreement between experts (κ = 0.76) was comparable to the agreement between method and experts (κ = 0.67). The algorithm was used in 22 559 patients with intrapartum FHR records to retrospectively determine the incidence of intervals (defined as 15 min windows) that had un-assignable baselines. Sixty-six percent had one or more such episodes at some stage, most commonly after the onset of pushing (55%) and least commonly pre-labor (16%). These episodes are therefore relatively common. Their detection should improve the reliability of computerized analysis and allow further studies of what they signify clinically.

Original publication

DOI

10.1088/0967-3334/32/10/004

Type

Journal article

Journal

Physiol Meas

Publication Date

10/2011

Volume

32

Pages

1549 - 1560

Keywords

Female, Heart Rate, Fetal, Humans, Labor, Obstetric, Pregnancy, Reproducibility of Results, Signal Processing, Computer-Assisted, Time Factors