A New Approach to the Analysis of Nystagmus: An Application for Order-Statistic Filter
Abstract
A computer program has been designed for the analysis of nystagmus. This program employs a class of nonlinear digital filters called order-statistic (OS) filters. Two OS filters and one linear filter are used. First, the eye-movement signal is smoothed using a predictive FIR-median hybrid filter. Then the smoothed signal is processed by a linear band-limited differentiating filter to calculate eye velocity. And, finally, the slow-phase velocity (SPV) envelope is extracted from the eye-velocity signal using an adaptive asymmetrically trimmed-mean filter. This approach yields an evenly sampled SPV estimate without resorting to the various interpolation or extrapolation schemes generally used. The adaptive filter estimates SPV based on the local statistical properties of the eye-velocity signal. The adaptive strategy works under the assumption that, on the average, the eyes spend more time in slow-phase than in fast-phase. No assumptions are made about the directions of the nystagmus or the nature of the stimulus used to elicit the nystagmus. This method eliminates all the usual threshold tests and decision logic common to other nystagmus analysis programs. The robust performance of OS filters and the use of adaptive filter structures totally eliminates the need to custom 'tune' the program parameters for atypical data sets. Keywords: Nonlinear mathematical filters; Adaptive filters.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 23, 1989
- Accession Number
- ADA218722
Entities
People
- Edward J. Engelken
- Kennith W. Stevens
Organizations
- United States Air Force School of Aerospace Medicine