El Internet de las Cosas Médicas (IoMT): Una Revolución Tecnológica aplicable a la Gestión de la Diabetes Mellitus Tipo 1

Autores/as

Ignacio Rodríguez Rodríguez
Departamento de Ingeniería de las Comunicaciones, Universidad de Málaga , Avda. Cervantes, 2, 29071 Málaga
https://orcid.org/0000-0002-0118-3406
José-Victor Rodríguez
Universidad Politécnica de Cartagena
https://orcid.org/0000-0002-3298-6439
María Campo Valera
Universidad Politécnica de Cartagena
https://orcid.org/0000-0003-0084-3844

Palabras clave:

Diabetes, IoMT, Machine Learning, Comunicaciones, Internet de las Cosas, Biosensores

Sinopsis

La diabetes mellitus de tipo 1 (DMT1) es una afección metabólica caracterizada por una hiperglucemia persistente como consecuencia de una síntesis pancreática insuficiente de insulina. Esto obliga a los pacientes a ser conscientes de sus oscilaciones diarias del nivel de glucosa en sangre para deducir un patrón y anticipar la glucemia futura y, por tanto, decidir la cantidad de insulina que debe inyectarse exógenamente para mantener la glucemia dentro del intervalo objetivo. Este enfoque suele adolecer de una imprecisión relativamente alta, que puede resultar peligrosa. Sin embargo, los recientes avances en las tecnologías de la información y la comunicación (TIC) y los innovadores biosensores que podrían permitir una evaluación completa y en tiempo real de la salud del paciente ofrecen un nuevo punto de vista sobre el tratamiento de la DMT1. En este sentido, las tecnologías disruptivas emergentes como Big Data, Internet de las Cosas Médicas (IoMT), Cloud Computing y Machine Learning (ML) pueden desempeñar un papel importante en la gestión de la DMT1. En este trabajo, se realiza una explicación de los enfoques basados en IoMT publicados anteriormente para la gestión de la diabetes, evaluando también los obstáculos que los futuros sistemas inteligentes de gestión IoMT deben superar. Por último, proporcionamos una visión general de una propuesta integral basada en IoMT para la gestión de la DM1 que pretende abordar los límites de los estudios anteriores y, al mismo tiempo, utilizar las tecnologías disruptivas destacadas anteriormente.

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