Title :
Maternal ECG elimination and foetal ECG detection-comparison of several algorithms
Author :
Kam, Amit ; Cohen, Amon
Author_Institution :
Dept. of Electr. Eng. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel
fDate :
29 Oct-1 Nov 1998
Abstract :
When trying to record a foetal ECG (FECG), one of the main problems is the interference from the maternal ECG (MECG). Three algorithms for eliminating maternal ECG are compared. Two adaptive filtering techniques, LMS (least mean square) and RLS (recursive least squares), are compared to a new algorithm that uses the blind source separation (BSS) theorem to separate the FECG from signals that are recorded with a lot of MECG interference. Simulation studies were first performed. Two independent ECG signals (sources) were simulated; one was considered as the MECG while the other was the FECG. By mixing the two sources with various channels, the algorithms were checked and compared. The algorithms were tested on real data as well as that taken from DAISY (the DAtabase for the Identification of SYstems). Conclusions concerning the mixing system were drawn both from the real data and from the simulation experiments
Keywords :
adaptive filters; adaptive signal detection; digital simulation; electrocardiography; interference (signal); medical signal processing; obstetrics; signal sources; DAISY; Database for the Identification of Systems; adaptive filtering techniques; blind source separation; foetal ECG detection; independent ECG signals; least mean square algorithm; maternal ECG elimination; recursive least squares algorithm; signal interference; signal source mixing system; simulation; Adaptive filters; Blind source separation; Electrocardiography; Filtering algorithms; Interference; Least squares approximation; Least squares methods; Resonance light scattering; Source separation; System testing;
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-5164-9
DOI :
10.1109/IEMBS.1998.745866