Multichannel electrocardiogram decomposition using periodic component analysis.
In this letter, we propose the application of the generalized eigenvalue decomposition for the decomposition of multichannel electrocardiogram (ECG) recordings. The proposed method uses a modified version of a previously presented measure of periodicity and a phase-wrapping of the RR-interval, for extracting the "most periodic" linear mixtures of a recorded dataset. It is shown that the method is an improved extension of conventional source separation techniques, specifically customized for ECG signals. The method is therefore of special interest for the decomposition and compression of multichannel ECG, and for the removal of maternal ECG artifacts from fetal ECG recordings.
Sameni
Reza
R
Biomedical Signal and Image Processing Laboratory (BISIPL), School of Electrical Engineering, Sharif University of Technology, 11365-9313 Tehran, Iran. reza.sameni@gmail.com
Jutten
Christian
C
Shamsollahi
Mohammad B
MB
D000465:Algorithms; D001185:Artificial Intelligence; D015148:Cardiotocography / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D009991:Oscillometry / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010507:Periodicity; D025341:Principal Component Analysis