Adaptive Walsh estimation of time-varying evoked potential signal

Xinrong Guo, Nitish Thakor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A novel method, the adaptive Walsh function model (WFM), to estimate time-varying evoked potential (EP) signals is presented. Using real EP signals and real noise as inputs to the model, the performances of two models are compared: WFM and Fourier series model (FSM). Both models are used to trace EP signal during experimental and clinical procedures. The results show: (1) both WFM and FSM perform satisfactorily in detecting and tracing time-varying EP signals in high levels of noise; (2) WFM needs less memory and calculations than FSM; (3) for the same adaptive step size, WFM traces faster transients than FSM, but WFM attains lower steady-state signal-to-noise ratio; (4) the WFM and FSM are suitable for the detection of EP signals and other periodic or quasi-periodic signals.

Original languageEnglish (US)
Title of host publicationBiomedical Engineering Perspectives
Subtitle of host publicationHealth Care Technologies for the 1990's and Beyond
PublisherPubl by IEEE
Pages866-867
Number of pages2
Editionpt 2
ISBN (Print)0879425598
StatePublished - Dec 1 1990
EventProceedings of the 12th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Philadelphia, PA, USA
Duration: Nov 1 1990Nov 4 1990

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 2
ISSN (Print)0589-1019

Other

OtherProceedings of the 12th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CityPhiladelphia, PA, USA
Period11/1/9011/4/90

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ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Guo, X., & Thakor, N. (1990). Adaptive Walsh estimation of time-varying evoked potential signal. In Biomedical Engineering Perspectives: Health Care Technologies for the 1990's and Beyond (pt 2 ed., pp. 866-867). (Proceedings of the Annual Conference on Engineering in Medicine and Biology; No. pt 2). Publ by IEEE.