Calculador inteligente de bolo de insulina en skill Alexa Amazon para pacientes con diabetes mellitus y deficiencia visual

  1. Solarte Orozco, Juan Camilo 1
  2. Manrique Córdoba, Juliana 2
  3. Vivas Albán, Óscar Andrés 1
  4. Romero Ante, Juan David 2
  5. Juan Poveda, Carlos Gabriel 2
  6. Vicente-Samper, José María 2
  7. Sabater-Navarro, José María 2
  1. 1 Universidad del Cauca
    info

    Universidad del Cauca

    Popayán, Colombia

    ROR https://ror.org/04fybn584

  2. 2 Universidad Miguel Hernández de Elche
    info

    Universidad Miguel Hernández de Elche

    Elche, España

    ROR https://ror.org/01azzms13

Livre:
XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja)
  1. Carlos Balaguer Bernaldo de Quirós (coord.)
  2. José Manuel Andújar Márquez (coord.)
  3. Ramon Costa Castelló (coord.)
  4. Carlos Ocampo Martínez (coord.)
  5. Jesús Fernández Lozano (coord.)
  6. Matilde Santos Peñas (coord.)
  7. José Enrique Simó Ten (coord.)
  8. Montserrat Gil Martínez (coord.)
  9. Jose Luis Calvo Rolle (coord.)
  10. Raúl Marín Prades (coord.)
  11. Eduardo Rocón de Lima (coord.)
  12. Elisabet Estévez Estévez (coord.)
  13. Pedro Jesús Cabrera Santana (coord.)
  14. David Muñoz de la Peña Sequedo (coord.)
  15. José Luis Guzmán Sánchez (coord.)
  16. José Luis Pitarch Pérez (coord.)
  17. Oscar Reinoso García (coord.)
  18. Oscar Déniz Suárez (coord.)
  19. Emilio Jiménez Macías (coord.)
  20. Vanesa Loureiro Vázquez (coord.)

Éditorial: Servizo de Publicacións ; Universidade da Coruña

ISBN: 978-84-9749-841-8

Année de publication: 2022

Pages: 148-155

Congreso: Jornadas de Automática (43. 2022. Logroño)

Type: Communication dans un congrès

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Résumé

This paper presents a functionality (skill) for the virtual voice assistant Alexa Amazon, as a support tool for patients with diabetes. The logic of the skill was developed as a bolus calculator for patients, considering a model of counting carbohydrates, fats and proteins consumed. Regarding the interaction, it was implemented considering the dialogue between a waiter and a client, the system can register each one of the foods that the user enters and regarding the number of macronutrients that each one of them contains, respond to the patient the total portions consumed and the percentages corresponding to the normal and square insulin bolus. In addition, a database was integrated where the macronutrients of more than 500 foods are found. The results of the research made it possible to validate the use of the application as a support tool for estimating macronutrients in food, being useful for glucose level management.

La source de données: Dialnet