Fractional order calculus-based filters for biomedical signal processing

Abstract

The goal of this paper is to give a review of some applications of fractional order calculus to biomedical signal processing with emphasis on the ability of this mathematical tool to remove noise, enhance useful information, and generate fractal signals. Three types of digital filters are considered, namely, lowpass differentiation filter, smoothing filter, and 1/f <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">β</sup> -noise generation filter. The filter impulse responses are function of the fractional order and the sampling period only, and thus can be computed easily. Application examples are presented for illustrations.