Biosignal Denoising via Wavelet Thresholds

Abstract

Biopotential signal is an electric quantity (voltage or current or field strength), caused by chemical reactions of charged ions. In experimental data collection, a signal of data points does not represent a perfect theoretical expectation. It always contains some noise due to various consequences. Denoising of the ECG wave and MRI image based upon the discrete wavelet transform (DWT) and discrete stationary wavelet transform (SWT) with different threshold techniques has been applied and presented in this paper.

Keywords:

• ECG
• MRI
• Denoising
• Threshold
• Wavelet transform

Additional information

Notes on contributors

Parmod Kumar

Parmod Kumar received the B.Sc. degree in Electrical Engineering from Calicut University, Calicut, India, in 1972, M.E degree from Roorkee University, Roorkee, in 1975, and Ph.D degree from IIT Delhi, New Delhi in 1982. He joined the M.P. Electricity Board, India, as Assistant Engineer and commissioned telemetry and SCADA instruments at substations, powerstations, and central control rooms. In 1983, he joined the Central Electricity Authority as a Deputy System Engineer and designed and configured the load dispatch centers for electric utilities. Subsequently, he served in various capacities for the Indian Railway Construction Company, ERCON, ESPL, and ESTC, and then entered academics in 1991. His areas of interest are smart and intelligent system design, operation, and control. Currently, he is a Professor in the Department of Electrical Engineering at Delhi Technological University, Delhi (formerly Delhi College of Engineering). E-mail: [email protected]

Devanjali Agnihotri

Devanjali Agnihotri received B.Tech. degree in Instrumentation and Control from Kurukshetra University, in 2002 and M.E degree in Control and Instrumentation from Delhi College of Engineering (Now Delhi Technological University) in 2006. She joined Maharaja Agrasen Institute of Technology in 2006 and presently working as Sr. Lecturer in Electrical and Electronics Engineering Department. Her interests include, Medical Image Processing, Optimization and Soft Computing Techniques. E-mail: [email protected]