The autonomic nervous system plays an important role in various pathological situations such as myocardial infarction, congestive heart failure or diabetic neuropathy and is strongly implicated in the pathogenesis of arrhythmogenesis and sudden cardiac death. Changes in the activity of autonomic nervous system can unveil the progression of several pathologies or act as a predictor of adverse events in selected subgroups of patients. Among different available techniques for the assessment of the autonomic status, heart rate variability has emerged as a simple, noninvasive method to evaluate sympathovagal balance at the sinoatrial level. Traditionally, heart rate variability has been calculated by linear analyses, utilizing statistics and Euclidean geometry. Lately, novel nonlinear analyses based on the mathematics of complex dynamics, chaos theory and fractal dimension have gained popularity in scientific community. The aim of the present article is to systematically describe conventional linear and novel nonlinear heartrate variability parmeters to provide the basic information about their calculation and to clarify the clinical usability of heartrate variability parameters in various physiological and pathological conditions.