Open-loop linear parametric models were exploited to describe ventricular repolarization duration (VRD) variability during graded head-up tilt. Surface ECG and thoracic movements were recorded in 15 healthy humans (age: 24-54 yr, median: 28 yr; 6 women and 9 men). Tilt table inclinations ranged from 15 to 90 degrees and were varied in steps of 15 degrees . All subjects underwent recordings at every step in random order. Heart period was assessed as the time difference between two consecutive R-wave peaks (RR) and the respiratory signal (R) as the sampling of the thoracic movement signal at the R-wave peaks. VRD was measured automatically as the temporal difference between the R-wave peak and T-wave apex (RT(a)) or T-wave end (RT(e)). The best model decomposed RT variability as due to RR changes (RR-related RT variability) to direct respiratory-related inputs (R-related RT variability) and to unknown rhythmical sources unrelated to RR changes and R (RR-R-unrelated RT variability). Using this model, RT(e) variability was found to be less predictable than RT(a) variability and composed of a smaller fraction of RR-related RT variability and a larger fraction of RR-R-unrelated RT variability. Predictability progressively decreased with tilt table angles, suggesting increased complexity of RT regulation. RT variance progressively increased with tilt table inclination. This increase was characterized by a gradual rise of the amount of RR-R-unrelated RT variability, whereas the amount of RR-related RT variability remained unchanged. These results suggest that the amount of RT variability, complexity of RT dynamics, and amount of RR-R-unrelated RT variability increase with the magnitude of the sympathetic drive directly related to tilt table inclination. We propose the utilization of the amount of RR-R-unrelated RT variability instead of overall RT variability as an indirect measure of autonomic regulation directed to ventricles.