Abstract

Movement trajectories contain important spatio-temporal information to characterise human activities that require displacements (eg grasp an object). A trajectory (dis)similarity measure is highly relevant in trajectory data analysis. The main purpose of this study was to develop a running version of the Procrustes Method to quantify dissimilarity between trajectories along time, as a method that can be used in further research. Empirical data was used to quantify changes in stroke patients’ movements in a daily life task (drinking water) after participating in a combined rehabilitation program (virtual reality plus conventional therapy). Results of the simulation study reflected the reliability of the Running Procrustes Method to quantify the dissimilarity between trajectories continuously over time. For the empirical data, this method identified critical parts of the drinking water task, providing information that might suggest beneficial effects of the combined program in stroke patients’ daily life tasks.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call