The heart rate (HR) exhibits various behavior patterns in different postures and during physical activities, whereas a conventional long-term analysis of HR variability has the confounding effect whether the subject was physically active or immobilized. A specially designed ambulatory recorder that simultaneously measures the electrocardiogram and body accelerations was used to study the short-term (< or =11 beats, alpha1) fractal correlation property and the approximate entropy (ApEn) of RR interval data during sleep, sitting and standing (passive standing or mild walking) levels and immediately after rising in the morning in 15 healthy subjects. The alpha1 exponent that increased from sleep to sitting to standing implies an increased correlation of HR dynamics, which is concomitant with an increased ratio of low-frequency power to high-frequency power (LF/HF) that is usually linked with an increased sympathetic activity. A lower ApEn value during standing and after rising implies a reduced complexity of HR dynamics. Compared to the HR measures during the standing level, the LF/HF ratio showed a quick autonomic shift and alpha1 showed a rapid recruitment of fractal HR behavior after rising, whereas the ApEn value had a slower recovery of HR complexity. In conclusion, both linear and nonlinear HR behaviors during different unsupervised physical activities can be better interpreted with the aid of the recorded movement data.