Resumen
The analysis of the human gait is of great importance for the diagnosis and the choice of the type of treatment that the patient must obtain. In this work, we report a proposal of the capture of the movement and an interpretation of the signal obtained by means of artificial intelligence and computer vision. Results were obtained by means of the acquisition of quantitative parameters characteristic of a gait pattern, in order to be able to group patients according to their characteristics by applying clustering with the use of the k-means algorithm. Markers were placed on the knee of the patient and through them the acquisition of the data was performed in real time. These data are plotted in 2D and 3D for a better understanding of the analysis. The main objective of this article is to propose a technique of pre-diagnosis by grouping and recognition of patterns so that, in turn, this can be used to make decisions about professional intervention in the patient.