Descripción del movimiento humano basado en el marco de Frenet Serret y datos tipo MOCAP
DOI:
https://doi.org/10.33571/rpolitec.v17n34a11Keywords:
Movimiento humano; Dinámica; Kinect; Captura de movimiento; Rehabilitación física; Frenet SerretAbstract
Classify human movement has become a technological necessity, where defining the position of a subject requires identifying the trajectory of the limbs and trunk of the body, having the ability to differentiate this position from other subjects or movements, which generates the need to have data and algorithms that help their classification. Therefore, the discriminant capacity of motion capture data in physical rehabilitation is evaluated, where the position of the subjects is acquired with the Microsoft Kinect and optical markers. Attributes of the movement generated with the Frenet Serret framework. Evaluating their discriminant capacity by means of support vector machines, neural networks, and k nearest neighbors algorithms. The obtained results present an accuracy of 93.5% in the classification with data obtained from the Kinect, and success of 100% for movements where the position is defined with optical markers.
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