Physionet/Cinc Challenge 2013: A Novel Noninvasive Technique to Recognize Fetal Qrs Complexes From Noninvasive Fetal Electrocardiogram Signals



Ghaffari A¹ ; Atyabi S¹ ; Mollakazemi MJ¹ ; Niknazar M² ; Niknami M³ ; Soleimani A¹ Show Affiliations
Source: Computing in Cardiology Published:2013

Abstract

The aim of this study is the intelligent recognition of the fetal heart rate and its R-R intervals from noninvasive fetal electrocardiogram signals. The non-value data was first eliminated and the missing data were regenerated based on the statistical distribution of the data. Then, the power line noise and baseline noise are removed. At the next step, a variable threshold criterion was designed to detect the maternal R-waves. By eliminating the specific ranges of the maternal R waves from signal, the remaining data describe merely the fetal QRS complexes. Next, a window with a specific length was slid on D1 signals and the envelope curves were extracted. The locations of each local maximum on the envelope curve represent the fetal R waves. Finally, in order to improve both the performance of the proposed method and the robustness of the algorithm to noise, an amendment technique with respect to the fetal and maternal R-R intervals was implemented The algorithm was applied on the test data set B consequently as the preliminary challenge scores. The average scores 108.766 and 15.480 were achieved as the best scores for the events 4 and 5, respectively, on phase 1, and 63.750 and 11.198 on phase 2. © 2013 CCAL.