Desarrollo De Un Aplicativo Para Apoyo En La Detección De Lesiones En El Ligamento Cruzado Anterior (Lca) Usando El Método De Sonomiografía (Smg) Aplicando Técnicas De Machine Learning

Abstract

This work proposes the use of the sonomiography technique, which combines ultrasound and electromyography, for the early detection of anterior cruciate ligament (ACL) injury in lower limbs. The lack of early detection methods for this pathology in Colombia, where its presence is common in daily activities and sports, means that most diagnoses are made when ACL rupture has already occurred. To address this problem, an application was developed that uses neural networks to analyze the parameters calculated by the sonomiography technique and detect ACL injury before rupture occurs. Preliminary results show that the application is able to detect the ligament and calculate its characteristics, giving an approximation of its condition. The use of this technique and the developed app represent an important advance in the field ofsports medicine and may improve the prevention and treatment of ACL injuries. Although further research and clinical trials are needed to validate the performance of the application, the preliminary results are very promising.