Title :
Fetal ECG extraction from abdominal recordings using array signal processing
Author :
Haghpanahi, Masoumeh ; Borkholder, David A.
Author_Institution :
Rochester Inst. of Technol., Rochester, NY, USA
Abstract :
An algorithm to automatically locate QRS complexes in noninvasive fetal ECG signals is described and was entered in the PhysioNet/CinC 2013 “Noninvasive Fetal ECG” challenge. The algorithm is based on an iterative subspace decomposition and filtering of the maternal ECG components from the recordings of a set of electrodes placed on the mother´s abdomen. Once the maternal components are removed, a novel merging technique is applied to merge the recordings and generate a signal with a higher SNR to perform fetal peak detection. The algorithm produces an annotation file for each data set containing the location of the fetal QRS complexes in that set. The final results indicate that the algorithm is able to detect fetal peaks under different scenarios and for variety of devices and signals encountered in clinical practice.
Keywords :
array signal processing; biomedical electrodes; electrocardiography; feature extraction; filtering theory; iterative methods; medical signal detection; obstetrics; Noninvasive Fetal ECG challenge; PhysioNet/CinC 2013; SNR; abdominal recording; annotation file; array signal processing; clinical practice; electrode recordings; fetal ECG extraction; fetal QRS complexes; fetal peak detection; iterative subspace decomposition; maternal ECG component filtering; maternal component removal; merging technique; mother abdomen; noninvasive fetal ECG signals; Electrocardiography; Indexes; Kalman filters; Merging; Noise; Signal processing algorithms; Time-frequency analysis;
Conference_Titel :
Computing in Cardiology Conference (CinC), 2013
Conference_Location :
Zaragoza
Print_ISBN :
978-1-4799-0884-4