A new method for QRS complex detection in multichannel ECG: Application to self-monitoring of fetal health. (1st June 2017)

• Record Type: Journal Article
• Authors: Varanini, Maurizio; Tartarisco, Gennaro; Balocchi, Rita; Macerata, Alberto; Pioggia, Giovanni; Billeci, Lucia
• Is Part Of: Computers in biology and medicine. Volume 85(2017)
• Page Start: 125
• Page End: 134
• Publication Date: 2017-06-01
• Subjects: Fetal QRS detection -- Multichannel ECG processing -- Self-monitoring -- Fetal electrocardiography -- Optimization -- Nelder–Mead simplex -- Independent component analysis (ICA); Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2016.04.008
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: This paper proposes a new approach for QRS complex detection in multichannel ECG and presents its application to fetal QRS (fQRS) detection in signals acquired from maternal abdominal leads. The method exploits the characteristics of pseudo-periodicity and time shape of QRS, it consists of devising a quality index (QI) which synthesizes these characteristics and of finding the linear combination of the acquired ECGs, which maximizes this QI. In the application for fQRS detection two QIs are devised, one QI ( mQI ) for maternal ECG (mECG) and one QI ( fQI ) for fetal ECG (fECG). The method is completely unsupervised and based on the following steps: signal pre-processing; maternal QRS-enhanced signal extraction by finding the linear combination that maximize the mQI ; detection of maternal QRSs; mECG component approximation and canceling by weighted Singular Value Decomposition (SVD); fQRS-enhanced signal extraction by finding the linear combination that maximize the fQI and fQRS detection. The proposed method was compared with our previously developed Independent Component Analysis (ICA) based method as well as with simple mECG canceling and simple ICA methods. The comparison was carried out by evaluating the performances of the procedures in fQRS detection. The new method outperformed the results of the other approaches on the annotated open set of the Computing in Cardiology Challenge 2013 database. The proposed method seems to be promising for its implementation on portable device and for use in self-monitoring of fetal health in pregnant women. Highlights: Novel unsupervised approach for enhanced QRS signal extraction from multichannel ECG. Application to fetal QRS detection from abdominal recordings. The method exploits the pseudo-periodicity of maternal and fetal QRS. Overcomes the limitation of methods based on the independence of signal sources. The approach foresees the application to self-monitoring of fetal in pregnant women.