Abstract: In the field of physiotherapy, the recognition of the poses of the human body is obtaining more research so that the patient has an accelerated recovery rate in his rehabilitation. Nowadays, it is not so challenging to have devices like Microsoft Kinect that allow us to interact with the user for the recognition of poses and body gestures. The objective of this work to capture the data of the joints of a person's body through a set of angles using the Kinect device, then artificial neural networks with the Back-Propagation algorithm were used for machine learning, and their precision was determined. The results found on the performance of the neural network show that 99.70% accuracy was achieved in the classification of the patients' postures, which can be used as an alternative in the rehabilitation therapies of patients with knee injuries.

Bisset Gonzales Loayza, Alberto Calla Bendita, Mario Huaypuna Cjuno and Jose Sulla-Torres, “Application of Kinect Technology and Artificial Neural Networks in the Control of Rehabilitation Therapies in People with Knee Injuries” International Journal of Advanced Computer Science and Applications(IJACSA), 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110864

@article{Loayza2020,
title = {Application of Kinect Technology and Artificial Neural Networks in the Control of Rehabilitation Therapies in People with Knee Injuries},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110864},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110864},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {8},
author = {Bisset Gonzales Loayza and Alberto Calla Bendita and Mario Huaypuna Cjuno and Jose Sulla-Torres}
}