Gema García-Sáez

• Ph.D
• Universidad Politécnica de Madrid

Objectives A conceptual framework, called Innovation of Health Technology Assessment Methods (IHTAM), has been developed to facilitate the understanding of how to innovate methods of health technology assessment (HTA). However, the framework applicability has not been evaluated in practice. Hence, we aimed to explore framework applicability in thre...

This study aimed to investigate the transferability of novel artificial intelligence (AI) methods for prediction modelling of diabetes based on real-world data (RWD) between early and late adopters of emerging health technologies from the perspective of developers and health technology assessment (HTA) experts. A two-step approach was used. Develop...

Type 2 diabetes is a highly heterogeneous disease for which new subgroups (‘clusters’) have been proposed based on disease severity: moderate age-related diabetes (MARD), moderate obesity-related diabetes (MOD), severe insulin-deficient diabetes (SIDD) and severe insulin-resistant diabetes (SIRD). It is unknown how disease severity is reflected in...

This paper presents an artificial pancreas algorithm implemented with a discrete-time sliding-mode method combined with a nonlinear block controllable form using a unidirectional control law and a discrete adaptive observer. The algorithm is both unidirectional, using insulin as unique input, and hybrid with a percentage of the pre-meal bolus admin...

Is a graphical abstract for the scientific paper Linear Time-Varying Luenberger Observer Applied to Diabetes, published on IEEE Access. The graphical abstract summarizes the methodological implementation to develop the time-varying Luenberguer observer to estimate the unmeasurable variables of glucose-insulin dynamic based on the structure of Bergm...

Pregnancy complicated with diabetes is a growing health problem which produces adverse maternal and neonatal outcomes that can be avoided by close medical support. The burden related to diabetes in pregnancy can negatively impact a woman's psychological health and jeopardize adherence to prescribed treatments. On the other hand, the high prevalence...

Diabetes is a chronic disease that affects a high percentage of the world population and produces different and serious complications to patients. Most diabetes complications may be avoided by controlling the blood glucose levels exhaustively. Moreover, a prediction of future glucose levels has shown to be fundamental in helping patients to plan an...

Introduction Diabetes monitoring systems (DMS) are a possible approach for regular control of glucose levels in patients with Type 1 or 2 diabetes in order to improve therapeutic outcomes or to identify and modify inappropriate patient behaviors in a timely manner. Despite the significant number of studies observing the DMS, no collective evidence...

The high prevalence of drug addiction is a major health challenge that pressures healthcare systems to respond with cost-effective treatments. To improve the treatment success of drug-dependent patients, it is necessary to identify the main associated risk factors for dropping out of treatment. Previous research shows disparate results due to the w...

We describe our experience in the remote management of women with gestational diabetes mellitus during the COVID-19 pandemic. We used a mobile phone application with artificial intelligence that automatically classifies and analyses the data (ketonuria, diet transgressions, and blood glucose values), making adjustment recommendations regarding the...

Background and objective: In the last decade, several technological solutions have been proposed as artificial pancreas systems able to treat type 1 diabetes; most often they are built based on a control algorithm that needs to be validated before it is used with real patients. Control algorithms are usually tested with simulation tools that integ...

Background: The automation of glucose control has been an important goal of diabetes treatment for many decades. The first artificial pancreas experiences were in-hospital, closely supervised, small-scale, and short-term studies that demonstrated their superiority over continuous subcutaneous insulin infusion therapy. At present, long-term outpati...

We present a linear time-varying Luenberger observer (LTVLO) using compartmental models to estimate the unmeasurable states in patients with type 1 diabetes. The LTVLO proposed is based on the linearization in an operation point of the virtual patient (VP), where a linear time-varying system is obtained. LTVLO gains are obtained by selection of the...

Background: In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to their daily living conditions. Artificial intelligence applications can help people with type 1 diabetes in decision making and allow them to react at time scales shorter than the scheduled face-to-fac...

En la actualidad, la prevalencia de las enfermedades no transmisibles (Non-communicable diseases NCD) y la cantidad de muertes causadas por éstas es muy elevada, en su mayoría, consecuencia del envejecimiento de la población, el aumento de la obesidad y los hábitos de vida sedentarios. En este trabajo se describen el funcionamiento y los resultados...

We present a linear time-varying Luenberger observer (LTVLO) using compartmental models to estimate the unmeasurable states in patients with type 1 diabetes. The LTVLO proposed is based on the linearization in an operation point of the virtual patient (VP), where a linear time-varying system is obtained. LTVLO gains are obtained by selection of the...

We present a linear time-varying Luenberger observer (LTVLO) using compartmental models to estimate the unmeasurable states in patients with type 1 diabetes. The LTVLO proposed is based on the linearization in an operation point of the virtual patient (VP), where a linear time-varying system is obtained. LTVLO gains are obtained by selection of the...

http://www.sciencedirect.com/science/article/pii/S1386505617300539 The growth of diabetes prevalence is causing an increasing demand in health care services which affects the clinicians’ workload as medical resources do not grow at the same rate as the diabetic population. Decision support tools can help clinicians with the inspection of monitorin...

MobiGuide is a ubiquitous, distributed and personalized evidence-based decision-support system (DSS) used by patients and their care providers. Its central DSS applies computer-interpretable clinical guidelines (CIGs) to provide real-time patient-specific and personalized recommendations by matching CIG knowledge with a highly-adaptive patient mode...

In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geo...

Gestational diabetes (GDM) burden has been increasing progressively over the past years. Knowing that intrauterine exposure to maternal diabetes confers high risk for macrosomia as well as for future type 2 diabetes and obesity of the offspring, health care organizations try to provide effective control in spite of the limited resources. Artificial...

Objectives: The MobiGuide project aimed to establish a ubiquitous, user-friendly, patient-centered mobile decision-support system for patients and for their care providers, based on the continuous application of clinical guidelines and on semantically integrated electronic health records. Patients would be empowered by the system, which would enab...

INTRODUCCIÓN:PREDIRCAM2 es una plataforma para facilitar el tratamiento y seguimiento de personas con obesidad, con módulos de registro alimentario, análisis nutricional, monitorización de actividad física, variables antropométricas y algoritmos de ayuda a la decisión. Actualmente se está evaluando su eficacia en el tratamiento multidisciplinario e...

Expert systems for diabetes care need to automatically evaluate glycaemia measurements in relationship to meals to correctly determine patients’ metabolic condition and generate recommendations about ther- apy adjustments. Most glucose meters allow patients to manually label each measurement with a meal tag, but as this utility is not always used,...

Los nuevos criterios de diagnóstico de la diabetes gestacional recomendados por la IADPSGC disminuyen los efectos adversos de la hiperglucemia tanto en la madre como en el recién nacido, pero su aplicación supondría un aumento de la prevalencia llegando a triplicar el número de casos actual. Para que los Servicios de Endocrinología y Nutrición pued...

En la actualidad, la prevalencia de las enfermedades no transmisibles (Non-communicable diseases NCD) y la cantidad de muertes causadas por éstas es muy elevada, en su mayoría, consecuencia del envejecimiento de la población, el aumento de la obesidad y los hábitos de vida sedentarios. En este trabajo se describe el funcionamiento y las característ...

En este trabajo se propone un método de comunicaciones para la monitorización de pacientes diabéticos basado en el patrón publicador/suscriptor el cual potencia la escalabilidad de dispositivos y usuarios y posee un alto nivel de flexibilidad. Con el fin de realizar una primera validación de la propuesta, se ha implementado un escenario simulado de...

Gestational diabetes (GD) confers an increased risk of complications as well as future type 2 diabetes. We assess the safety and efficacy of an artificial intelligence (AI)-augmented telemedicine system (ruled-based reasoning) that includes a blood glucose (BG) classifier (C4.5 Quinlan decision tree) in comparison with the standard care in the mana...

We have developed a computer-based smart telemedicine system to give automated support to GD patients while insulin is not required. The system combines a platform for remote monitoring of diabetes-related parameters with a decision-support system based on expert knowledge that generates automatic feedback to patients. Blood glucose (BG) data downl...

We introduce the need for a distributed guideline-based decision support (DSS) process, describe its characteristics, and explain how we implemented this process within the European Union's MobiGuide project. In particular, we have developed a mechanism of sequential, piecemeal projection, i.e., 'downloading' small portions of the guideline from th...

Background The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients’ self-management capabilities, and potentiall...

Automatic blood glucose classification may help specialists to provide a better interpretation of blood glucose data, downloaded directly from patients glucose meter and will contribute in the development of decision support systems for gestational diabetes. This paper presents an automatic blood glucose classifier for gestational diabetes that com...

The MobiGuide system provides patients with personalized decision support tools, based on computerized clinical guidelines, in a mobile environment. The generic capabilities of the system will be demonstrated applied to the clinical domain of Gestational Diabetes (GD). This paper presents a methodology to identify personalized recommendations, obta...

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient's data using two different strategies to control nocturnal and postpra...

Healthy diet and regular physical activity are powerful tools in reducing diabetes and cardiometabolic risk. Various international scientific and health organizations have advocated the use of new technologies to solve these problems. The PREDIRCAM project explores the contribution that a technological system could offer for the continuous monitori...

Este trabajo presenta un clasificador de medidas de glucemia en función de las ingestas asociadas para pacientes con diabetes gestacional. Se presentan los resultados obtenidos al comparar la relevancia de diferentes atributos así como del uso de dos de los algoritmos más populares en el mundo del aprendizaje automático: las redes neuronales y los...

In this paper we present TRHIOS: a Trust and Reputation system for HIerarchical and quality-Oriented Societies. We focus our work on hierarchical medical organizations. The model estimates the reputation of an individual, RTRHIOS, taking into account information from three trust dimensions: the hierarchy of the system; the source of information; an...

En este artículo presentamos un sistema de videoconferencia web de bajo coste cuyo objetivo es mejorar la comunicación entre Atención Primaria y Atención Especializada optimizando los recursos y la calidad de la atención en enfermedades con alta prevalencia en la actualidad. En este caso se utiliza para problemas metabólicos como la diabetes o pa...

Aims: This work presents the evaluation of an on-line glucose prediction algorithm based on a neural network model (NNM) during a cross-correlation clinical study. Material and methods: The on-line prediction algorithm was implemented on a portable personal digital assistant (PDA) where the patient types manually the last 5 continuous glucose monit...

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activit...

The main aim was to improve communication between general practitioners (GPs) and endocrinologist optimizing the resources and the quality of care regarding high prevalence pathologies such as diabetes and other metabolic disturbances. Thus, we have developed a new application for real-time communication between endocrinologist and GP’s through low...

Aims: This work presents the PredEval web tool that aims to help researchers in the evaluation of glucose predictor algorithms by implementing a complete evaluation methodology for comparing any glucose predictor output versus the original continuous glucose monitoring (CGM) profile. Methods: PredEval estimates the mean model behaviour by the root...

The aim of our study was to test the effectiveness and security of an on-line artificial neural network (ANN) algorithm for glucose prediction (30 min) from RT-CGM applied to correct interprandial hyperglycaemia. Materials and methods: Twelve DM1 patients treated with insulin pumps were included in this randomized cross-over clinical study. In both...

The combination of telemedicine systems integrating mobile technologies with the use of continuous glucose monitors improves patients' glycemic control but demands a higher interaction with information technology tools that must be assessed. In this article, we analyze patients' behavior from the use-of-the-system point of view, identifying how con...

PREDIRCAM es una innovadora plataforma tecnológica, cuyo objetivo es el proporcionar a pacientes y profesionales de la salud una herramienta para mejorar la eficacia de la modificación de la conducta por medio de la utilización intensiva de las nuevas tecnologías. Un estudio piloto se llevó a cabo, con 15 voluntarios durante dos semanas, con el fin...

The integration of continuous subcutaneous insulin infusion (CSII) (insulin pump therapy) and continuous interstitial glucose monitoring (CGM) appears to be an excellent solution for obtaining the desirable metabolic control for most insulin-treated subjects (1–4). Several studies have suggested that CGM with readings in real-time (CGM-RT) further...

The use of telemedicine for diabetes care has evolved over time, proving that it contributes to patient self-monitoring, improves glycemic control, and provides analysis tools for decision support. The timely development of a safe and robust ambulatory artificial pancreas should rely on a telemedicine architecture complemented with automatic data a...

The accurate interpretation of Blood Glucose (BG) values is essential for diabetes care. However, BG monitoring data does not provide complete information about associated meal and moment of measurement, unless patients fulfil it manually. An automatic classification of incomplete BG data helps to a more accurate interpretation, contributing to Kno...

Advanced information technologies joined to the increasing use of continuous medical devices for monitoring and treatment, have made possible the definition of a new telemedical diabetes care scenario based on a hand-held Personal Assistant (PA). This paper describes the architecture, functionality and implementation of the PA, which communicates d...

This paper presents the modelling and formal specification of a telemedicine system for diabetes care. In such scenario, the multiagent technology supports the distributed autonomy of several Personal Assistants; the communications between them and the hospital's agents; the control of the system's access and multitask functionality; scalability; a...

This work presents a generic tool based on a client-server architecture that generates electronic reports helping the evaluation process of any information system. For the specific evaluation of telemedicine systems the defined reports cover four dimensions: auditory of the system; evolution of clinical protocols; results from the questionnaires fo...

Se ha realizado un estudio del algoritmo de calibración y representación de los valores de glucosa del monitor continuo de glucosa en tiempo real Guardian RT®, con el fin de valorar la incertidumbre de sus medidas. Se ha utilizado una patente relacionada con dicho sistema para obtener el algoritmo más aproximado posible al ejecutado por el disposit...

The growing availability of continuous data from medical devices in diabetes management makes it crucial to define novel information technology architectures for efficient data storage, data transmission, and data visualization. The new paradigm of care demands the sharing of information in interoperable systems as the only way to support patient c...

Biomedical engineering research efforts have accomplished another level of a ldquotechnological solutionrdquo for diabetes: an artificial pancreas to be used by patients and supervised by healthcare professionals at any time and place. Reliability of continuous glucose monitoring, availability of real-time programmable insulin pumps, and validation...

Real-time continuous glucose monitoring (CGM) has recently been incorporated into routine diabetes management because of the potential advantages it offers for glycemic control. The aim of our study was to evaluate the impact of the use of real-time CGM together with a telemedicine system in hemoglobin A1c and glucose variability in patients with t...

Diabetes Mellitus is nowadays one of the most frequent non-contagious diseases in the world and remains a major health problem for the national health care programs. It is well proved that Telemedicine helps diabetic patients controlling their glucose levels, facilitating their day to-day therapy management and the communication with health care pe...

Diabetes mellitus is nowadays one of the most frequent noncontagious diseases in the world and remains a major health problem for national health care programs. It is well proved that telemedicine helps diabetic patients control their glucose levels, facilitating their day-to-day therapy management and communication with health care personnel. The...

The DIABTel system, a Web-based telemedicine application, integrates a whole communication system (glucometer, insulin pump, wireless hand-held assistant) for medical remote advice. We sought to evaluate, in terms of glycemic control, the DIABTel system in a randomized crossover clinical study. Ten patients with type 1 diabetes [5 women, age 40.6 (...

ABSTRACT: This paper describes the development of an intelligent agent that interprets blood glucose monitoring data received by a telemedicine-based diabetes management service. The agent generates automatic alarms when some deviations in the patient status are detected. The agent combines different methods to produce data summaries and automatic...

The rapid growth and development of information technologies over recent years, in the areas of mobile and wireless technologies is shaping a new technological scenario of telemedicine in diabetes. This telemedicine scenario can play an important role for further acceptance by diabetic patients of the existing continuous glucose monitoring systems...