Multistage enhancement of surface recordings of canine gastric electrical signals.

Abstract

This article describes a multistage signal processing scheme to enhance the quality of canine gastric signals recorded from the abdominal surface. The scheme involves a cascade application of linear prediction followed by a nonlinear processing known as alpha-TM filtering. The linear prediction is used to separate, in the minimum mean square error sense, the slow wave from other uncorrelated interference signals. We make novel use of the order versus frequency response characteristics of linear predictors to achieve this separation. The nonlinear filtering is used to suppress the residual wide band impulsive noise. Our studies have indicated that such an optimized signal enhancement scheme produces a clean time domain signal, which is easy to interpret visually. It not only preserves the periodicity of the slow wave, but also seems to track any irregularities in the periods. We believe that this last feature, namely the potential to track nonstationarities in the signal, is the main contribution of our approach.