Fractal Characterization of ECG signals: Indian Classical Music as stimulus

Music elicits a wide range of effects on human physiology. The diverse effects of musical stimuli on cardiovascular and autonomic nervous-system dynamics are characterized by the analysis of Electrocardiography (ECG) signals. ECG reflects the electrical activity of the heart. Studies suggest that human heart and ECG is non-linear and chaotic in nature, therefore needs to be studied using non-linear methods. In this paper, monofractal Detrended Fluctuation Analysis or DFA method will be first used, followed by subsequent multifractal method - Multifractal Detrended Fluctuation Analysis (MFDFA). Using these methods, we will be studying the non-linear characteristics of ECG while listening to Indian Classical Music. Very few studies have been performed to characterize how Indian Classical Music affects the non-linear nature of ECG signals using multifractal tools. In our experiment, the presence of long-range scale-invariant structure in ECG signals is initially studied using DFA. The scaling behaviour of ECG signals is characterized by more than one scaling exponent, suggesting the multifractal nature of ECG. MFDFA is performed to study the multifractal nature of ECG. Width of multifractal spectrum while listening to music is compared with resting condition. Results show that the range of multifractality increases while listening to music.