Aprendizaje automático para la clasificación de la competencia motora con tecnología vestible en escolares

José Sulla-Torres, Alexander Paul Calla Gamboa, Christopher Avendaño Llanque, Manuel Zúñiga Carnero

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Personal health can be determined by adequate physical activity; Motor competence is an important aspect to help this and must be carried out from school days. The objective of this study was to assess motor competence with wearable technology, generate the percentiles of the evaluation metrics, and classify motor performance using machine learning techniques in primary and secondary school children. For this, smart bands were used as wearable technologies for data capture during the evaluation of motor skills tests in schoolchildren from educational centers. The CRISP-DM methodology was followed, the data set consisted of 485 schoolchildren between 7 and 18 years of age. As a result of the application of machine learning algorithms, the best precision was achieved with the decision tree with 96.97% in the classification of motor performance in these students. It is concluded that the use of smart bands allows better precision in data capture and processing to better classify motor skills tests in schoolchildren and can be used by interested persons.

Título traducido de la contribuciónMachine learning for the classification of motor competence with wearable technology in schoolchildren
Idioma originalEspañol
Título de la publicación alojadaProceedings of the 21st LACCEI International Multi-Conference for Engineering, Education and Technology
Subtítulo de la publicación alojadaLeadership in Education and Innovation in Engineering in the Framework of Global Transformations: Integration and Alliances for Integral Development, LACCEI 2023
EditoresMaria M. Larrondo Petrie, Jose Texier, Rodolfo Andres Rivas Matta
EditorialLatin American and Caribbean Consortium of Engineering Institutions
ISBN (versión digital)9786289520743
EstadoPublicada - 2023
Publicado de forma externa
Evento21st LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2023 - Buenos Aires, Argentina
Duración: 19 jul. 202321 jul. 2023

Serie de la publicación

NombreProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volumen2023-July
ISSN (versión digital)2414-6390

Conferencia

Conferencia21st LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2023
País/TerritorioArgentina
CiudadBuenos Aires
Período19/07/2321/07/23

Nota bibliográfica

Publisher Copyright:
© 2023 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

Palabras clave

  • Machine Learning
  • Motor competence
  • Smart Band
  • Wearable Technology

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