Smart Kiosk for Nutritional Management of People With Diabetes in Underserved Communities: Development and Technical Evaluation

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AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-10-05T16:32:20Z
Fecha de publicación2026-01-01
ResumenBackground: Diabetes is a chronic disease with a high global prevalence, increasing from 200 million people in 1990 to 830 million in 2022, with a higher burden in low-and middle-income regions and high mortality in Mexico and Veracruz. These inequalities limit access to treatment and nutritional education, requiring technological solutions such as interactive kiosks based on artificial intelligence (AI) that contribute to the nutritional management of people with diabetes in marginalized communities. Objective: This study aimed to design and evaluate an interactive kiosk based on AI that generates culturally relevant and personalized meal plans for people with diabetes in marginalized communities. Methods: A low-cost prototype was developed, with a database of local foods and a multilayer perceptron trained with synthetic data based on national clinical guidelines. Performance was tested through an experimental evaluation that measured specialIntscript the accuracy of nutritional recommendations compared with ideal meal plans (accuracy, precision, sensitivity, and F 1-score); specialIntscript performance, measured by recording response time with 1 to 50 simultaneous requests; and specialIntscript usability, assessed using heuristic evaluation and the System Usability Scale (SUS). Results: The smart kiosk was experimentally evaluated in three dimensions: nutritional recommendations, system efficiency, and usability. The model achieved AI metrics of 87.3\% overall accuracy, 90.5\% precision, 92.1\% sensitivity, and 91.3\% F 1-score. The average response time was 2.36 (SD 0.24) seconds in all load tests. A maximum time of 4 seconds was obtained in the simulation of 50 concurrent users. In the usability evaluation, an average score of 89 (SD 2.89) out of 100 was obtained on the SUS, which is considered excellent, along with a success rate of 98.3\%. Conclusions: The AI-based kiosk demonstrated technical feasibility, adequate performance, and satisfactory usability. Its ability to operate without the need for internet and its low cost make it an equitable option for diabetes self-management and a replicable model in public health.es_ES
Doihttps://doi.org/10.2196/76936es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/4188
Idiomaenes_ES
EditorialJMIR PUBLICATIONS, INCes_ES
RelaciónJMIR Formative Researches_ES
URL relacionadohttps://doi.org/10.2196/76936es_ES
DerechosAcceso abierto (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_abf2es_ES
FuenteJMIR Formative Research
Palabra clavesmart health kioskes_ES
Palabra clavediabetes managementes_ES
Palabra clavenutritional recommendation systemes_ES
Palabra claveartificial intelligencees_ES
Palabra claveunderserved communitieses_ES
TítuloSmart Kiosk for Nutritional Management of People With Diabetes in Underserved Communities: Development and Technical Evaluationes_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorRivera-Garcia, Guadalupe Esmeralda
AutorRamirez-Vazquez, Juan Carlos
AutorCruz-Casados, Jaime
AutorCervantes-Lopez, Miriam Janet
AutorLlanes-Castillo, Arturo
AutorDiaz-Martinez, Marco Antonio
AutorRivera-Garcia, Guadalupe Esmeraldaes_ES
AutorRamirez-Vazquez, Juan Carloses_ES
AutorCruz-Casados, Jaimees_ES
AutorCervantes-Lopez, Miriam Janetes_ES
AutorLlanes-Castillo, Arturoes_ES
AutorDiaz-Martinez, Marco Antonioes_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
URL relacionadahttps://doi.org/10.2196/76936
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen10es_ES

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