Alessio Fioravanti

Comparative assessment of glucose prediction models for patients with type 1 diabetes mellitus applying sensors for glucose and physical activity monitoring

The present work presents the comparative assessment of four glucose prediction models for patients with type 1 diabetes mellitus (T1DM) using data from sensors monitoring blood glucose concentration. The four models are based on a feedforward neural network (FNN), a self-organizing map (SOM), a neuro-fuzzy network with wavelets as activation functions (WFNN), and a linear regression model (LRM), respectively. For the development and evaluation of the models, data from 10 patients with T1DM for a 6-day observation period have been used. The models’ predictive performance is evaluated considering a 30-, 60- and 120-min prediction horizon, using both mathematical and clinical criteria. Furthermore, the addition of input data from sensors monitoring physical activity is considered and its effect on the models’ predictive performance is investigated. The continuous glucose-error grid analysis indicates that the models’ predictive performance benefits mainly in the hypoglycemic range when additional information related to physical activity is fed into the models. The obtained results demonstrate the superiority of SOM over FNN, WFNN, and LRM with SOM leading to better predictive performance in terms of both mathematical and clinical evaluation criteria.

Integration of heterogeneous biomedical sensors into an ISO/IEEE 11073 compliant application

Current trends in healthcare technology include mobile-based applications. Relevant advances in the integration of vital signs monitoring devices with mobile platforms are widely reported nowadays. In this context, conceiving and designing an interoperable application is essential due to the growing necessity of integrating a huge and heterogeneous amount of biomedical data, coming from a wide range of devices and sensors. In this paper the key research issues associated with such integration are presented as well as a specific proposal to solve these problems. It is based on a middleware architecture for the integration of biomedical sensors with mobile devices, derived from the ISO/IEEE 11073 standards family. The application has been developed in the framework of an EU-funded R&D project called METABO.

A user centered design approach for patient interfaces to a diabetes IT platform

Improving patient self-management can have a greater impact than improving any clinical treatment (WHO). We propose here a systematic and comprehensive user centered design approach for delivering a technological platform for diabetes disease management. The system was developed under the METABO research project framework, involving patients from 3 different clinical centers in Parma, Modena and Madrid.

A mobile feedback system for integrated E-health platforms to improve self-care and compliance of diabetes mellitus patients

Exploiting the full potential of telemedical systems means using platform based solutions: data are recovered from biomedical sensors, hospital information systems, care-givers, as well as patients themselves, and are processed and redistributed in an either centralized or, more probably, decentralized way. The integration of all these different devices, and interfaces, as well as the automated analysis and representation of all the pieces of information are current key challenges in telemedicine. Mobile phone technology has just begun to offer great opportunities of using this diverse information for guiding, warning, and educating patients, thus increasing their autonomy and adherence to their prescriptions. However, most of these existing mobile solutions are not based on platform systems and therefore represent limited, isolated applications. This article depicts how telemedical systems, based on integrated health data platforms, can maximize prescription adherence in chronic patients through mobile feedback. The application described here has been developed in an EU-funded R&D project called METABO, dedicated to patients with type 1 or type 2 Diabetes Mellitus.

Experience in Evaluating AAL Solutions in Living Labs

Ambient assisted living (AAL) is a complex field, where different technologies are integrated to offer solutions for the benefit of different stakeholders. Several evaluation techniques are commonly applied that tackle specific aspects of AAL; however, holistic evaluation approaches are lacking when addressing the needs of both developers and end-users. Living labs have been often used as real-life test and experimentation environments for co-designing AAL technologies and validating them with relevant stakeholders. During the last five years, we have been evaluating AAL systems and services in the framework of various research projects. This paper presents the lessons learned in this experience and proposes a set of harmonized guidelines to conduct evaluations in living labs.

Integration of Personalized Healthcare Pathways in an ICT Platform for Diabetes Managements: A Small-Scale Exploratory Study

The availability of new tools able to support patient monitoring and personalized care may substantially improve the quality of chronic disease management. A personalized healthcare pathway (PHP) has been developed for diabetes disease management and integrated into an information and communication technology system to accomplish a shift from organization-centered care to patient-centered care. A small-scale exploratory study was conducted to test the platform. Preliminary results are presented that shed light on how the PHP influences system usage and performance outcomes.

Adaptive Healthcare Pathway for Diabetes Disease Management

The current clinical pathway in health facilities is affected by two strong limitations in care delivery: the absence of ICT tools that may let the physician monitor continuously patient’s clinical evolution and the impossibility of managing in an effective way the complex parameters that could lead to a patient’s care personalization. The Adaptive Healthcare Pathway (AHP) concept developed and integrated in a technological platform for diabetes disease management, implements a shift from a healthcare organization-centred care to patient-centred care. The system was tested in a small-scale exploratory study. Results, focused on how the AHP may have influenced the system usage and outcomes, are provided.