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Abstract
Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate (FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to identifying fetuses which suffer from lack of oxygen, i.e. hypoxia. This situation is defined as fetal distress and requires fetal intervention in order to prevent fetus death or other neurological disease causedby hypoxia. Fetal heart rate and uterine contraction are 2 vital parameters that require continuous monitoring during the intrapartum period. These two parameters are used to detect the fetal distress condition. Cardiotocography is the most widely used tool for monitoring FHR and UC. It gives output in graphical format which is interpreted by health care professionals to detect fetal distress cases. Currently these interpretations are subjective and vary from expert to expert and guideline to guideline. We propose to develop an application that takes time series CTG data that classifies them as normal and distress as output.