Application of Multi-Scaling Complexity Indices of Heart Rate Variability in Sex Discrimination of Healthy Subjects

• Published in: 2024 13th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO) pp. 1 - 2
• Main Authors: Matic, Zoran, Kalauzi, Aleksandar, Suljovrujic, Edin, Bojic, Tijana
• Format: Conference Proceeding
• Language: English
• Published: IEEE 23.10.2024
• Subjects: Complexity theory; entropy; fractality; Heart rate variability; MATLAB; Noise; Oscillators; Physiology; Rail to rail inputs; Regulation; Sensitivity; sex; Time series analysis
• DOI: 10.1109/ESGCO63003.2024.10767001

Background. Nonlinear indices of heart rate variability (HRV) like detrended fluctuation analysis (DFA) and multiscaling entropy (MSE) proved to be very sensitive and suitable for data discrimination. In this research, we decided to test these indices in the statistical differentiation of the RRI intervals of Hypol database subjects by sex. Method. The indices of DFA \alpha_{1}, \alpha_{2} and \alpha_{1} / \alpha_{2} and MSE 1-4 and MSE _{5-10} were obtained using the Matlab algorithms; inter-fractal angle (\theta) was obtained by the graphical-analytical method. Results. \alpha_{1}, \alpha_{1} / \alpha_{2} and the \theta had a higher value in male compared to female subjects. The \theta angle had a significantly lower p value (when comparing sex using the Mann Whitney test) in respect to \alpha 1 and \alpha 2, and slightly higher in respect to \alpha_{1} / \alpha_{2}. MSE indices showed no sex differences. Conclusion. DFA fractal scaling indices possess sufficient sensitivity to discriminate data by sex.