Beschreibung
The ElectroCardioGram (ECG) signal is a graphical representation of the human heart activity. The acquired ECG signal is interfered with different artefacts. Power Line Interference (PLI) is the main source of noise to affect the ECG signal. Adaptive filtering techniques like Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Error Nonlinearity Least Mean Square (ENLMS) are used to remove the noise from ECG signal. The three algorithms are developed and the performance the three algorithms are analyzed. Among the three algorithms, ENLMS algorithm effectively removes the PLI from ECG signals and gives better results compared to LMS and NLMS.
Autorenporträt
Dr. Chandra Mohan Reddy Sivappagari is working as Associate Professor in Jawaharlal Nehru Technological University Ananatapur (JNTUA), Ananthapuramu, Andhra Pradesh, India. He completed his Ph.D from JNTUA in the year 2014. He is a member of IEEE, Life member of Institution of Engineers India (IEI), ISTE and IAENG.
Herstellerkennzeichnung:
OmniScriptum SRL
Str. Armeneasca 28/1, office 1
2012 Chisinau
MD
E-Mail: info@omniscriptum.com
