Using Grip Strength as a Cardiovascular Risk Indicator Based on Hybrid Algorithms

• E. F. Bareño-Castellanos ^[1] ; P. A. Gaona-García ^[1] ; J. E. Ortiz-Guzmán ^[2] ; C. E. Montenegro-Marin ^[1]
  1. [1] Universidad Distrital Francisco José de Caldas

     Universidad Distrital Francisco José de Caldas

     Colombia

     
  2. [2] Universidad de Ciencias Aplicadas y Ambientales

     Universidad de Ciencias Aplicadas y Ambientales

     Colombia

     
• Localización: IJIMAI, ISSN-e 1989-1660, Vol. 7, Nº. 2, 2021, págs. 27-33
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • This article shows the application and design of a hybrid algorithm capable of classifying people into risk groups using data such as prehensile strength, body mass index and percentage of fat. The implementation was done on Python and proposes a tool to help make medical decisions regarding the cardiovascular health of patients. The data were taken in a systematic way, k-means and c-means algorithms were used for the classification of the data, for the prediction of new data two vectorial support machines were used, one for the k-means and the other for the c-means, obtaining as a result a 100% of precision in the vectorial support machine with c-means and a 92% in the one of k-means.