Title :
A signal separation algorithm for fetal heart-rate estimation
Author :
Lai, Kuei-Chiang ; Shynk, John J.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
fDate :
Oct. 29 2000-Nov. 1 2000
Abstract :
In this paper we describe an adaptive algorithm for separating fetal and maternal heart beats from data containing both fetal and maternal QRS complexes. The algorithm classifies the combined heart-rate data as a series of fetal maternal, and noise events using a technique of template matching. Peak detection is first employed to locate the potential fetal and maternal QRS complexes (referred to as candidate events). Fetal and maternal templates are generated automatically from the candidate events in the initialization period, and are used to classify the remaining candidate events based on certain similarity criteria. Once the fetal and maternal complexes are successfully detected and separated, a counting mechanism can be utilized to derive the corresponding heart rates. Computer simulations using real data demonstrate the effectiveness of the algorithm.
Keywords :
adaptive signal processing; electrocardiography; medical signal processing; paediatrics; signal classification; time series; QRS complexes; adaptive algorithm; computer simulations; counting mechanism; event classification; fetal heart-rate estimation; maternal heart beats; peak detection; signal separation algorithm; similarity criteria; template matching; Abdomen; Electrocardiography; Electrodes; Event detection; Fetal heart rate; Fetus; Heart rate; Signal processing; Signal processing algorithms; Source separation;
Conference_Titel :
Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-6514-3
DOI :
10.1109/ACSSC.2000.910976