An electrocardiogram (ECG) is a bioelectrical signal which records the heart’s electrical activity versus time on the body surface via contact electrodes. The recorded ECG signal is often contaminated by noise and artifacts that can be within the frequency band of interest. This noise can hide some important features of the ECG signal. The focus of this thesis is the application of new modified versions of the Universal threshold to allow additional enhancements in the reduction of ECG noise. Despite the fact that there are many types of contaminating noises in ECG signals, only white noise and baseline wandering will be considered. This type of noise is undesirable and needs to be removed prior to any additional signal processing for proper analysis and display of the ECG signal.

This thesis is focused on the analysis of fetal ECG records measured by indirect method from mother´s abdomen. The thesis consists of the theoretical part is focused on fetal, heart development and description of fetal ECG signal. This thesis also offers an overview of fECG signal processing methods used nowadays. The practical part of the thesis deals with the implementation of algorithms based on wavelet transformation and Least Mean Square LMS method in Matlab programming environment. The final part of the thesis consists of the analysis of achieved results.