Multifractal analysis of ECG time series of stress tests in healthy subjects

Abstract

Multifractal analysis of heartbeat intervals time series or tachograms has become an important technique to characterize them and has the potential to support the cardiologist diagnosis. When subjects perform physical activity, their cardiovascular system can present alterations that are not present at rest, therefore, physicians can know whether they have or not heart disease. Exercise testing (ET) sometimes called treadmill test is used to evaluate the body’s reaction to exercise stress. ET can show if the blood supply is reduced in the arteries that supply the heart. It also helps doctors to know the kind and level of exercise appropriate for a patient. In previous works we have found that multifractal spectra show significant differences between heathy persons and congestive heart failure (CHF) patients. In this work, we study electrocardiograms (ECG) of healthy subjects and obtain inter-beat (RR) interval time series. We calculate multifractal spectra by using the Chhabra and Jensen algorithm for these time series, at rest and in exercise on the treadmill at different speeds. Multifractal spectra of the tachograms at rest are wider, biased to the right and their curvature around the maximum is small. In contrast, when subjects do exercise, multifractal spectra are skewed to the left and their curvature around the maximum increases, these features are observed in tachograms of CHF patients.