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

  1. E. F. Bareño-Castellanos 1
  2. P. A. Gaona-García 1
  3. J. E. Ortiz-Guzmán 2
  4. C. E. Montenegro-Marin 1
  1. 1 Faculty of Engineering, Universidad Distrital Francisco José de Caldas, Bogotá (Colombia)
  2. 2 Facultad de Ciencias de la Salud, Universidad de Ciencias Aplicadas y Ambientales, Bogotá (Colombia)
Revista:
IJIMAI

ISSN: 1989-1660

Año de publicación: 2021

Volumen: 7

Número: 2

Páginas: 27-33

Tipo: Artículo

DOI: 10.9781/IJIMAI.2021.05.004 DIALNET GOOGLE SCHOLAR

Otras publicaciones en: IJIMAI

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.

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Fuente de los datos: Dialnet