Marginal Component Analysis of ECG Signals for Beat-to-Beat Detection of Ventricular Late Potentials

被引:13
作者
Guaragnella, Cataldo [1 ]
Rizzi, Maria [1 ]
Giorgio, Agostino [1 ]
机构
[1] Politecn Bari, DEI Dept Elect & Informat Engn, I-70126 Bari, Italy
关键词
HR-ECG; electrocardiography; high resolution cardiography; ventricular late potentials; VLP; detection; beat-to-beat; singular value decomposition; marginal component analysis; signal processing; parameter estimation; computer aided detection (CAD); WAVELET TRANSFORM; HIGH-RESOLUTION; COMPLEX;
D O I
10.3390/electronics8091000
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Heart condition diagnosis based on electrocardiogram signal analysis is the basic method used in prevention of cardiovascular diseases, which are recognized as the leading cause of death globally. To anticipate the occurrence of ventricular arrhythmia, the detection of Ventricular Late Potentials (VLPs) is clinically worthwhile. VLPs are low-amplitude and high-frequency signals appearing at the end part of QRS complexes in the electrocardiogram, which can be considered as a robust feature for arrhythmia risk stratification in patients with cardiac diseases. This paper proposes a beat-to-beat VLP detection method based on the the marginal component analysis and investigates its performance taking into account different ratios between QRS and VLP power. After a denoising phase, performed adopting the singular vector decomposition technique, heartbeats characterized by VLP onsets are identified and extracted taking into account the vector magnitude of each high resolution ECG (HR-ECG) record. To evaluate the proposed method performance, a 15-lead HR-ECG database consisting of real VLP-negative and simulated VLP-positive patterns was used. The achieved results highlight the method validity for VLP detection.
引用
收藏
页数:15
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