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

Authors

E.F. Bareño-Castellanos
Paulo Alonso Gaona-García
J.E. Ortiz-Guzmán
Carlos Enrique Montenegro-Marin

DOI

10.9781/ijimai.2021.05.004

Abstract

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.

Source Publication

International Journal of Interactive Multimedia and Artificial Intelligence

Recommended Citation

Bareño-Castellanos, E.F.; Gaona-García, Paulo Alonso; Ortiz-Guzmán, J.E.; and Montenegro-Marin, Carlos Enrique (2021) "Using Grip Strength as a Cardiovascular Risk Indicator Based on Hybrid Algorithms," International Journal of Interactive Multimedia and Artificial Intelligence: Vol. 7: Iss. 2, Article 20.
DOI: 10.9781/ijimai.2021.05.004
Available at: https://ijimai.researchcommons.org/ijimai/vol7/iss2/20