This paper introduces several extensions to the architecture of current state-of-the-art personal health systems, that aim at improving their adaptability to the user needs, their scalability, and their interoperability. These extensions are/will be applied to a real system for monitoring gestational diabetes.

1. Our Approach
• Personalization
! Doctors can define medical guidelines for each
patient through a web interface
• Scalability
! Computations are moved from tier-3 to tier-2
! Use of intelligent agents deployed in an Android
smartphone to perform reasoning on patients data
! Reasoning is based on the medical guidelines defined
by doctors
• Interoperability
! Use of RuleML for sending medical guidelines from
tier-3 to tier-2
! Use of HL7 CDA to report alerts from tier-3 to tier-2
Contact and more information:
albert.brugues@hevs.ch, http://iig.hevs.ch/
Albert Brugués1,2, Stefano Bromuri1, Josep Pegueroles2,
Michael Schumacher1
1University of Applied Sciences Western Switzerland (HES–SO), Sierre, Switzerland;
2Universitat Politècnica de Catalunya – BarcelonaTech (UPC), Barcelona, Spain
Summary
1. Our work introduces several extensions to the architecture of current state-of-the-art personal health systems
2. The aim is to improve their adaptability to user needs, their scalability, and their interoperability
3. These extensions are applied to a real system for monitoring gestational diabetes
Introduction
• The paradigm of pervasive healthcare is based on the
definition of Personal Healh Systems (PHSs)
• PHSs help on the management of chronic diseases, and
are centered around the patient
• Typical PHSs usually have a 3-tier architecture
• We give a new point of view to the current PHSs
Our Focus
• Gestational diabetes mellitus (GDM)
• Architecture of the system
• Patients use a smartphone for reporting health data
related with GDM
! Physiological values
! Symptoms
! Medications
• Doctors use a web application to check patients’
conditions
Conclusions
• We propose an architecture of a PHS that is adaptive, scalable and interoperable
• The expected benefits are: support more patients without reducing system’s performance, reduce communications over the
network, allow doctors to personalize the system’s behavior according to patient’s needs
Towards a Personalizable
Health System for Diabetes
Security Proxy
Services
Business Layer
Data Access Layer
Medical
Staff
Patient
Database
REST
WEB INTERFACE
Android
Smartphones
Monitoring
Agents