Techniques To Remove Power Line Interference From ECG Signal

Chandra Mohan Reddy Sivappagari

ISBN 10: 620230216X / ISBN 13: 9786202302166

Published by Scholars' Press Okt 2017, 2017

About this Item

Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.

Seller Inventory # 9786202302166

Bibliographic Details

• Title: Techniques To Remove Power Line Interference From ECG Signal
• Publisher: Scholars' Press Okt 2017
• Publication Date: 2017
• Language: English
• ISBN 10: 620230216X
• ISBN 13: 9786202302166
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 4D millimeters 220 millimeters width by 150 millimeters height by 4 millimeters depth
• Weight: 102 grams

About this title

Synopsis

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.

About the Author

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.