Noise reduction in biological step signals: application to saccadic EOG

I. N. Bankman, Nitish V Thakor

Research output: Contribution to journalArticle

Abstract

A weighted filter for noise reduction in nonrecurrent step signals where adaptive filtering cannot be applied is described. An optimal correction of a conventional finite impulse response (FIR) filter is achieved by using a priori knowledge of noise variance and a continuous estimation of the error signal's power. The weighted filter provides an optimal compromise between noise filtering and distortionless tracking. The prior knowledge required is that of the noise power and the lowest frequency in the noise spectrum. Application of the weighted filter to the saccadic electro-oculogram (EOG) results in better estimations of saccade duration and velocity.

Original languageEnglish (US)
Pages (from-to)544-549
Number of pages6
JournalMedical & Biological Engineering & Computing
Volume28
Issue number6
DOIs
Publication statusPublished - Nov 1990

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Keywords

  • EOG
  • Filtering
  • Noise reduction
  • Saccade

ASJC Scopus subject areas

  • Health Information Management
  • Health Informatics
  • Biomedical Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics

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