Extraction of short-latency evoked potentials using a combination of wavelets and evolutionary algorithms

Scott John Turner*, Philip Picton, Jacqueline Ann Campbell

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Somatosensory evoked potentials, recorded at the spine or scalp of a patient, are contaminated by noise. It is common practice to use ensemble averaging to remove the noise, which usually requires a large number of responses to produce one averaged signal. In this paper a post-processing technique is shown which uses a combination of wavelets and evolutionary algorithms to produce a representative waveform with fewer responses. The most suitable wavelets and a set of weights are selected by an evolutionary algorithm to form a filter bank, which enhances the extraction of evoked potentials from noisy recordings.
Original languageEnglish
Pages (from-to)407-412
Number of pages6
JournalMedical Engineering & Physics
Volume25
Issue number5
Early online date25 Mar 2003
DOIs
Publication statusPublished - 1 Jun 2003

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Keywords

  • Wavelets
  • Evolutionary algorithms
  • Evoked potentials

Cite this

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AB - Somatosensory evoked potentials, recorded at the spine or scalp of a patient, are contaminated by noise. It is common practice to use ensemble averaging to remove the noise, which usually requires a large number of responses to produce one averaged signal. In this paper a post-processing technique is shown which uses a combination of wavelets and evolutionary algorithms to produce a representative waveform with fewer responses. The most suitable wavelets and a set of weights are selected by an evolutionary algorithm to form a filter bank, which enhances the extraction of evoked potentials from noisy recordings.

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