Assessment of Anthropometric Measurements for Obesity and Abnormal Body Fat Percentage Diagnosis Using k-means as Clustering Technique

Alexandra La Cruz, Erika Severeyn, Jesús Velásquez, Héctor Herrera, Sara Wong

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

The increased prevalence of overweight and obesity has become a major factor in public spending in countries around the world. The diagnosis of overweight and obesity is based on body mass index (BMI) and body fat percentage (BFP). The World Health Organization proposed BMI cut-off points to define overweight and obesity. Recently epidemiological studies established as normal BFP a BFP < 25 for men and BFP < 30 for women. A high correlation between a high BMI, abnormal BFP and skin thinness have been found in numerous studies. The aim of this work is to evaluate the k-means clustering algorithm using anthropometric measurements for the classification of subjects with overweight/obesity and abnormal BFP. Precision (P), accuracy (Acc) and recall (R) were calculated to evaluate the efficiency of the method to classify overweight/obesity and abnormal BFP. Results of this research suggest that the k-means method applied to anthropometric measurements can make an acceptable classification of overweight/obesity and abnormal BFP. The arm circumferences values show the best Acc, P and R (0.79, 0.84 and 0.71) compared to all other measurements for overweight/obesity diagnosis, otherwise, suprailiac and abdominal skinfolds values show the best Acc, P and R (0.73, 0.73 and 0.64) compared to all other measurements for abnormal BFP diagnosis. Results that are supported by studies asserting a strong relationship between arm circumferences, abdominal skinfold, suprailiac skinfold, BFP and BMI. Other machine learning techniques, such as neural networks and the support vector machine, will be studied in the future to assess the relationship between BMI, BFP and anthropometric measurements.

Idioma originalInglés
Título de la publicación alojadaInformation and Communication Technologies - 8th Conference, TICEC 2020, Proceedings
EditoresGermania Rodriguez Morales, Efraín R. Fonseca C., Juan Pablo Salgado, Pablo Pérez-Gosende, Marcos Orellana Cordero, Santiago Berrezueta
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas177-191
Número de páginas15
ISBN (versión impresa)9783030628321
DOI
EstadoPublicada - 2020
Evento8th Conference on Information and Communication Technologies of Ecuador, TICEC 2020 - Guayaquil, Ecuador
Duración: 25 nov 202027 nov 2020

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen1307
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

Conferencia8th Conference on Information and Communication Technologies of Ecuador, TICEC 2020
País/TerritorioEcuador
CiudadGuayaquil
Período25/11/2027/11/20

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