Heart rate is one of the most important well-being indicators of a fetus which is recorded during a CTG examination parallel to the fetal movements observed by the mother. Dangerous states, such as fetal hypoxia, compression of the umbilical cord and abnormal function of the fetal heart can be identified on the retrieved dataset. BabyCTG is a mobile application-based fetal heart rate medical remote monitoring system which enables expectant mothers to perform CTG examination in the comfort of their homes and get feedback from their doctors.
As the result of this master thesis an automatic evaluation module was integrated in the BabyCTG system which is capable of removing measurement errors from the incoming data, specifying signal loss, baseline, baseline-variability, accelerations, decelerations and categorizing the registratum. On one hand, the calculations offer the opportunity to prioritize the incoming measurements in the evaluation center, therefore appropriate actions can be taken in time in the case of CTG measurements categorized as suspect or pathological. On the other hand, taking the values marked next to the registratum into consideration helps doctors in decision-making, thereby making the evaluation process more efficient and reliable.
The thesis demonstrates the technologies available for performing these calculations, discusses advantages and disadvantages, furthermore the selection criteria regarding the specific opportunities. The work analyzes the calculation of individual parameters based on extensive research. Comparing the completed implementation against medical evaluation in case of 216 registratum an 87\% match could be achieved.