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

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 car...

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Bibliographic Details
Published inInternational journal of interactive multimedia and artificial intelligence Vol. 7; no. 2; pp. 27 - 33
Main Authors Bareño-Castellanos, E.F., Gaona-García, Paulo Alonso, Ortiz-Guzmán, J.E., Montenegro-Marin, Carlos Enrique
Format Journal Article
LanguageEnglish
Published IMAI Software 01.12.2021
Universidad Internacional de La Rioja (UNIR)
Subjects
Algorithms
Body mass index
c-means
Cardiovascular diseases
k-means
prehensile strength
risk
Risk factors
support vector machine
Colombia
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Summary: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. KEYWORDS Body Mass Index, C-Means, K-Means, Percentage F Fat, Prehensile Strength, Risk Indicator, Support Vector Machine.
ISSN:1989-1660
1989-1660
DOI:10.9781/ijimai.2021.05.004