Fig. 1From: Understanding personalized dynamics to inform precision medicine: a dynamic time warp analysis of 255 depressed inpatientsFor a single patient, the individual HRSD-17 item scores over time are shown (a). The DTW method uses a dynamic (i.e., stretching and compressing) programming approach to minimize a predefined distance measure (e.g., Euclidean distance), in order for the two time-series to become optimally aligned through a warping path (b). The optimal warping route between items 1 and 7 is shown (c). Using the “symmetricP0” step pattern and a Sakoe-Chiba Band of 2, this yields a final DTW distance of 13 (d)Back to article page