ADMAN: An Alarm-Based Mobile Diabetes Management System for Mobile Geriatric Teams

Kukhun, Dana Al; Soukkarieh, Bouchra; Sèdes, Florence

doi:10.1007/978-3-319-23201-0_53

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…El riesgo de hipoglucemia es una preocupación esencial en el tratamiento de la diabetes. La gestión móvil de la diabetes basada en alarmas (ADMAN) se propuso más adelante [33]. La monitorización a distancia ayuda a los pacientes ancianos a regular su diabetes.…”

Section: Métodos Basados En Iomt Para Enfermedades Crónicas Y Dmt1unclassified

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

Rodríguez‐Rodríguez¹,

Rodríguez²,

Campo-Valera³

2023

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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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Section: Métodos Basados En Iomt Para Enfermedades Crónicas Y Dmt1unclassified

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

Rodríguez‐Rodríguez¹,

Rodríguez²,

Campo-Valera³

2023

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“…An alternative approach is identified via the ADMAN platform [9], which is an alarm-based mobile control system for diabetes. The application of machine learning and remote monitoring methods can allow for enhancing diabetes regulation among older people.…”

Section: The Use Of Ida In Iot Platforms For Dm1 Managementmentioning

confidence: 99%

A Comparison of Different Models of Glycemia Dynamics for Improved Type 1 Diabetes Mellitus Management with Advanced Intelligent Analysis in an Internet of Things Context

et al. 2020

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The metabolic disease Type 1 Diabetes Mellitus (DM1) is caused by a reduction in the production of pancreatic insulin, which causes chronic hyperglycemia. Patients with DM1 are required to perform multiple blood glucose measurements on a daily basis to monitor their blood glucose dynamics through the use of capillary glucometers. In more recent times, technological developments have led to the development of cutting-edge biosensors and Continuous Glucose Monitoring (CGM) systems that can monitor patients’ blood glucose levels on a real-time basis. This offers medical providers access to glucose oscillations modeling interventions that can enhance DM1 treatment and management approaches through the use of novel disruptive technologies, such as Cloud Computing (CC), big data, Intelligent Data Analysis (IDA) and the Internet of Things (IoT). This work applies some advanced modeling techniques to a complete data set of glycemia-related biomedical features—obtained through an extensive, passive monitoring campaign undertaken with 25 DM1 patients under real-world conditions—in order to model glucose level dynamics through the proper identification of patterns. Hereby, four methods, which are run through CC due to the high volume of data collected, are applied and compared within an IoT context. The results show that Bayesian Regularized Neural Networks (BRNN) offer the best performance (0.83 R2) with a reduced Root Median Squared Error (RMSE) of 14.03 mg/dL.

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“…In fact, in diabetes management, this is an important issue, mainly due to the risk that is involved in a hypoglycemia. In [21], an alarm-based mobile diabetes management system (ADMAN) is proposed. By using remote monitoring, it is aimed at improving diabetes control in elderly patients.…”

Section: Telemedicinementioning

confidence: 99%

Towards an ICT-Based Platform for Type 1 Diabetes Mellitus Management

2018

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Type 1 Diabetes Mellitus (DM1) is a metabolic disease that is characterized by chronic hyperglycemia due to a lack of pancreatic insulin production. This forces patients to perform several blood glucose measurements per day-by means of capillary glucometers-in order to infer a trend and try to predict future values. In this way, a decision about the insulin dosage that has to be exogenously injected to maintain glycemia within the desirable levels is made. Unfortunately, this method usually suffers from relatively high imprecision. However, recent advances in information and communication technologies (ICT), along with novel biosensors that could provide a real-time comprehensive condition of the patient, offer a new perspective in DM1 management. In this sense, new disruptive technologies like Big Data, the Internet of Things (IoT), and Cloud Computing, as well as Machine Learning (ML) can play an important role in managing DM1. In this work, firstly, an analysis of previously published ICT-based methods for the management of diabetes continuous monitoring is carried out. In this way, an assessment of the possible lack of such proposals is presented, along with the challenges to be overcome in forthcoming smart DM1 management systems. Finally, an overview of a holistic ICT-based platform for DM1 management that try to solve the limitations of previous works, while at the same time, taking advantage of the abovementioned disruptive technologies is hereby proposed.Appl. Sci. 2018, 8, 511 2 of 15 either by multiple daily injections or by continuous infusion, using a pump, which permeates under the skin.In this context, new technological possibilities offer a new horizon in diabetes management. Although the first steps towards an artificial pancreas (AP) were undertaken 50 years ago [1], when the concept of a computer-supported system emulating the behavior of a pancreas by using a control algorithm was introduced, promising that technological advances achieved in recent years are supposed to bring a revolution in this field. Nowadays, an AP (which has not been completely achieved yet) is presumed to be composed of a Continuous Glucose-Monitoring (CGM) device aimed at checking the patient's glucose levels in real time (a feature that is already available) and injecting (a feature that is not yet commercially available) insulin (and glucagon, if applicable) into his or her body, along with a control system based on a closed loop, which must decide the amount of hormone (insulin or glucagon) to be injected [2,3].2017 was a particularly significant year regarding the AP [4]. Clinical trials were performed and their results were published, showing a good performance under real and demanding situations. Even a commercial hybrid closed-loop system is commercially available at present, Medtronic MiniMed 670G, which automatically adjusts basal insulin every five minutes based on CGM readings and is able to stop insulin up to 30 min before reaching a preset low limit. It also automatically restarts insulin when patient's lev...

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ADMAN: An Alarm-Based Mobile Diabetes Management System for Mobile Geriatric Teams

Cited by 4 publications

References 9 publications

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

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

A Comparison of Different Models of Glycemia Dynamics for Improved Type 1 Diabetes Mellitus Management with Advanced Intelligent Analysis in an Internet of Things Context

Towards an ICT-Based Platform for Type 1 Diabetes Mellitus Management

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