title: Cancellation of artifacts in ECG signals using block adaptive filtering techniques.
abstract: In this chapter, various block-based adaptive filter structures are presented, which estimate the deterministic components of the electrocardiogram (ECG) signal and remove the noise. The familiar Block LMS algorithm (BLMS) and its fast implementation, Fast Block LMS (FBLMS) algorithm, is proposed for removing artifacts preserving the low frequency components and tiny features of the ECG. The proposed implementation is suitable for applications requiring large signal-to-noise ratios with fast convergence rate. Finally, we have applied these algorithms on real ECG signals obtained from the MIT-BIH database and compared its performance with the conventional LMS algorithm. The results show that the performance of the block-based algorithms is superior than the LMS algorithm.
authors: Instrumentation Engineering, Andhra University, Visakhapatnam, 530003, India. mdzr55@gmail.com
authors: Mohammad Zia Ur
authors: MZ
authors: Rahman
authors: Rafi Ahamed
authors: RA
authors: Shaik
authors: D V Rama Koti
authors: DV
authors: Reddy
mesh_terms: D000465:Algorithms; D016477:Artifacts; D019295:Computational Biology; D003198:Computer Simulation; D016208:Databases, Factual; D004562:Electrocardiography / Q000706:statistics & numerical data*; D006801:Humans; D009068:Movement / Q000502:physiology; D009132:Muscles / Q000502:physiology; D012815:Signal Processing, Computer-Assisted