Saltar al contenido
República del Perú · Observatorio de la producción científica universitaria
OApol.org Observatorio de Inteligencia Científica Universitaria del Perú
OApol.org
Inicio Universidades Publicaciones Investigadores
Repositorios
Tesis y trabajos académicosRevistas
Indicadores
Ranking trimestralRanking por carreraObjetivos de Desarrollo SostenibleReporte OCDERed neuronal 3D
Acerca
MetodologíaPrivacidad

Optical and physical processing for the analysis of pre-existing muscle injuries in the upper extremities

Moya-Salazar J.; Sabino I.P.; Rojas-Zumaran V.; Espinoza-Morriberon D. · Revista Cubana de Medicina Militar (2024)

Resumen

Introduction: Diagnosing muscle injuries is a challenge in low-access healthcare contexts. Integrating motion analysis techniques can favor and comprehensively improve these injuries analysis. Objective: To develop an optical and physical processing approach for analyzing pre-existing muscle injuries in the upper body extremities. Methods: An exploratory observational study was designed involving 7 Peruvian adults. Maneuvers were conducted to assess specific segments of the upper limb (conventional method), and the Skillspector software was used to collect and analyze biomechanical data based on optical and physical processing. Two methods were compared using 5 parameters of the Six Sigma methodology. Results: 71.4% of participants had injuries in the forearm, and 42.9% showed a significant change in biomechanical variability. The conventional method had a lower Sigma (3.45) than the alternative method (5.55). Despite its advantages, the complexity in data manipulation and susceptibility to variables were limitations of the alternative method during patient digital modeling. Conclusions: Optical and physical processing with Skillspector is highly effective in analyzing muscle injuries, surpassing the biomechanical maneuvers method.

Instituciones: Universidad Tecnológica del Perú; Universidad Privada del Norte