AN ASSESSMENT OF THE ORTHOGONAL AND BIORTHOGONAL DISCRETE WAVELET TRANSFORM BASED DENOISING OF BIOLOGICAL SIGNALS − A STUDY BASED ON ECG

Divya Shenoy Purushothama, Anoop Kishore, Tom Devasia, Pawan Ganesh Nayak*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Wavelets transforms are effective mathematical tools useful in compression and denoising of n-D signals. Subjecting a signal to discrete wavelet transforms (DWT) generates approximation and detailed coefficients that are similar to the coefficients generated by passing the signal through lowpass and high pass filters respectively. Multilevel decomposition (filtering) can be carried out which can successively filter the signal at each bandpass. In this work, a normal sinus rhythm ECG signal noised with a sinewave was denoised by DWT using by members of mother wavelets like coiflet, symlet and biorthogonal families. The denoising performance of the wavelets were evaluated by comparing the signal characteristics of the original and the denoised signals.

Original languageEnglish
Pages (from-to)113-122
Number of pages10
JournalGlobal and Stochastic Analysis
Volume11
Issue number4
Publication statusPublished - 09-2024

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Discrete Mathematics and Combinatorics

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