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Detection of brainstem auditory evoked potential by adaptive filtering

  • F. H. Y. Chan
  • F. K. Lam
  • P. W. F. Poon
  • W. Qiu
Physiological Measurement

Abstract

A method of detecting brainstem auditory evoked potential (BAEP) using adaptive signal enhancement (ASE) is proposed and tested in humans and cats. The ASE in this system estimates the signal component of the primary input, which is correlated with the reference input to the adaptive filter. The reference input is carefully designed to make an optimal and rapid estimation of the signal corrupted with noise, such as ongoing EEG. With a good choice of reference input, it is possible to track the variability of BAEP efficiently and rapidly. Moreover, the number of repetitions required could be markedly reduced and the result of the system is superior to that of ensemble averaging (EA). To detect BAEP in cats, only 30 ensemble averages are needed to obtain a reasonable reference input to the adaptive filter, and, for humans, 350–750 ensemble averages are sufficient for a satisfactory result. Using the LMS adaptive algorithm, individual BAEP can be obtained in real-time.

Keywords

Adaptive signal enhancement Brainstem auditory evoked potential Convergence Correlation coefficient 

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Copyright information

© IFMBE 1995

Authors and Affiliations

  • F. H. Y. Chan
    • 1
  • F. K. Lam
    • 1
  • P. W. F. Poon
    • 2
  • W. Qiu
    • 1
  1. 1.Department of Electrical & Electronic EngineeringThe University of Hong KongHong Kong
  2. 2.Department of PhysiologyThe University of Hong KongHong Kong

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