Abstract
Anterior cruciate ligament injury is a condition that requires physical rehabilitation therapy. Due to the problems of the COVID-19 pandemic and the patient’s mobility problems, it is difficult to attend the rehabilitation sessions. The developed mobile application uses color recognition through the OpenCV library, with which a virtual goniometer can be generated by capturing the specific anatomical points of the lower limb through the camera of the device. It also allows controlling and monitoring the exercises prescribed by a specialist. The exercises performed by the patient are registered by the mobile application which captures the series and repetitions, the flexion and extension movements, and their maximum and minimum angles respectively; Thanks to this, proper performance can be tracked. The results of four test subjects of different ages and sexes were obtained by submitting them to rehabilitation exercises and recording their respective measurements, thus verifying the effectiveness of the mobile application.
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Contreras-Alcázar, I., Contreras-Alcázar, K., Cornejo-Aparicio, V. (2021). Mobile Application for Movement Recognition in the Rehabilitation of the Anterior Cruciate Ligament of the Knee. In: Lossio-Ventura, J.A., Valverde-Rebaza, J.C., Díaz, E., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2020. Communications in Computer and Information Science, vol 1410. Springer, Cham. https://doi.org/10.1007/978-3-030-76228-5_16
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