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BoostEMD: An extension of EMD method and its application for denoising of EMG signals

  • Kaunas University of Technology

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

The paper presents a novel extension of the Huang's Empirical Mode Decomposition (EMD) method, called BoostEMD, that allows calculating higher order Intrinsic Mode Functions (IMFs) that capture higher frequency empirical mode oscillations (empiquencies) in the EMG (electromyography) data. We describe the use of the second order IMFs for denoising physical action EMG signals. We demonstrate the efficiency of denoising by performing classification of EMG data before and after application of the denoising procedure as well as by evaluating properties of the extracted noise signal.

Original languageEnglish
Pages (from-to)57-61
Number of pages5
JournalElektronika ir Elektrotechnika
Volume21
Issue number6
DOIs
Publication statusPublished - 2015

Keywords

  • Electromyography
  • Empirical mode decomposition
  • Filtering
  • Signal denoising

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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