A Complexity Measure Based on Modified Zero-Crossing Rate Function for Biomedical Signal Processing

Abstract

A complexity measure is a mathematical tool for analyzing time-series data in many research fields. Various measures of complexity were developed to compare time series and distinguish whether input time-series data are regular, chaotic, and random behavior. This paper proposes a simple technique to measure fractal dimension (FD) values on the basis of zero-crossing function with detrending technique or is called modified zero-crossing rate (MZCR) function. The conventional method, namely, Higuchi's method has been selected to compare output accuracies. We used the functional Brownian motion (fBm) signal which can easily change its FD for assessing performances of the proposed method. During experiment, we tested the MZCR-based method to determine the FD values of the EEG signal of motor movements. The obtained results show that the complexity of fBm signal is measured in the form of a negative slope of log-log plot. The Hurst exponent and the FD values can be measured effectively.