We propose a novel two-dimensional warping technique to match two one-dimensional patterns. Our approach, referred to as two-dimensional signal warping (2DSW), extends the basic ideas of known warping techniques such as dynamic time warping and correlation optimized warping. By employing two-dimensional piecewise stretching 2DSW is able to capture inhomogeneous variations of one-dimensional signals in direction of abscissa and ordinate. In order to prove the applicability of our method we apply 2DSW for tracking changes in beat-to-beat variability in QT intervals (QTV). Using simulated data we demonstrate the robustness of our approach. Analysis of long-term ECG from the DEFINITE trial on circadian rhythms demonstrated the sensitivity of the proposed algorithm to track changes in the QT interval. Using repeated measure ANOVA and Holm-Bonferroni corrected paired Student's t-test for post-hoc analysis we found statistically significant differences in QTV between 1 a.m. to 8 a.m. and 10 a.m. to 11 p.m.