Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publisher : Progress in Intelligent Computing Techniques: Theory, Practice, and Applications
Campus : Amritapuri
School : School of Engineering
Department : Electronics and Communication
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 50/60nbsp;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.