Publication Type : Conference Paper
Publisher : Progress in Intelligent Computing Techniques: Theory, Practice, and Applications, Springer Singapore, Singapore .
Source : Progress in Intelligent Computing Techniques: Theory, Practice, and Applications, Springer Singapore, Singapore (2018)
ISBN : 9789811033766
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Center for Computational Engineering and Networking (CEN)
Year : 2018
Abstract : Accurate analysis and proper interpretation of electrophysical recordings like ECG is a real necessity in medical diagnosis. Presence of artifacts and other noises can corrupt the ECG signals and can lead to an improper disease diagnosis. Power line interferences (PLI) occurring at 50/60 Hz is a major source of noises which could corrupt the ECG signals. This motivates the removal of PLI from ECG signals and is a foremost preprocessing task in ECG signal analysis. In this paper, we deal an \$\${\backslashell _1}\$\$ℓ1norm based optimization approach for PLI removal in ECG signals. The sparsity inducing property of \$\${\backslashell _1}\$\$ℓ1norm is used for efficient removal of power noises. The effectiveness of this approach is evaluated on ECG signals corrupted with power line interferences and random noises.
Cite this Research Publication : Neethu Mohan, S. Kumar, S., and Dr. Soman K. P., “An ℓ1 -Norm Based Optimization Approach for Power Line Interference Removal in ECG Signals”, in Progress in Intelligent Computing Techniques: Theory, Practice, and Applications, Singapore, 2018.