Multifractal Detrended Analysis

Multifractal analysis serves as a powerful method for examining time series signals, including electrocardiogram (ECG) and electroencephalogram (EEG) signals. This analytical approach enables researchers to quantify signal complexity and identify underlying variation patterns through fractal dimension spectrum calculations. The implementation typically involves detrending procedures using polynomial fitting algorithms (commonly MF-DFA method) to remove local trends, followed by scaling analysis to compute multifractal spectra. By applying multifractal analysis, investigators can conduct comprehensive examinations of signal characteristics across different scales, yielding detailed insights into signal irregularity and multifractal properties. Consequently, multifractal analysis plays a vital role in signal processing and biomedical engineering applications, particularly for detecting pathological patterns in physiological signals through quantitative complexity measures.