Research themes


People involved


From Human Sensory-Motor Function to Patient-Practitioner Interaction

  • Remote Monitoring and Treatment / Telemedicine

5.4 M € total funding

580 k € to RMT/BSS


Principal Investigator tracks

Dr. Val Jones


Project website



MobiGuide investigates, develops and evaluates a novel Patient Guidance System (PGS) which gives patients personalized clinical-guideline-based guidance anytime and anywhere and so supports them in day-to-day management of their health condition.

MobiGuide is a four year Integrated Project funded by the European Commission under Call 7 of the 7th Framework Programme (Objective: ICT-2011.5.3a: Patient guidance services (PGS) for personalized management of health status).

MobiGuide addresses EU priorities: increasing patient safety, ubiquitous secure access to health care, patient empowerment, developing a common platform for healthcare services and European competitiveness.

The consortium includes universities and industrial and clinical partners from five countries. The partners are: University of Haifa, Israel (Coordinator); Ben-Gurion University, Israel; University of Pavia, Italy; University of Twente, The Netherlands; Vienna University of Technology, Austria; MobiHealth BV, The Netherlands; Fondazione Salvatore Maugeri Clinica Del Lavoro e della Riabilitazione, Italy; University Polytechnic of Madrid, Spain; Corporació Sanitaria Parc Tauli, Spain; ATOS Origin, Spain; Beacon Tech Ltd., Israel; ZorgGemak BV, The Netherlands; and Catalonia Diabetic Association, Spain


MobiGuide will research and develop a patient guidance system that integrates hospital EMRs and telemonitoring data into a Personal Health Record (PHR) which is ubiquitously accessible by patients and care providers, so enabling personalized, secure distributed decision support tailored to the patient’s current situation as well as to the technological context. MobiGuide will develop guidance services amongst others for patients with atrial fibrillation and for women with complications of pregnancy (gestational diabetes and hypertension).

Decision Support will be evidence-based, utilizing CIGs (Computer Interpretable Clinical Guidelines) in real time in a mobile and distributed environment.

MobiGuide's ubiquity will be achieved by having a Decision Support System (DSS) at the back end, and at the front end by utilizing Body Area Network (BAN) technology and developing a coordinated light-weight mobile DSS to run on the BAN that can operate independently if needed (eg in case of communications failure). Personalization will be achieved by considering patient preferences and context. Retrospective data analysis will be used to assess compliance and to indicate care pathways shown to be beneficial for certain patient contexts.

The research contribution of the Telemedicine Group of BSS revolves around mobile patient monitoring and mobile clinical decision support using Body Area Networks (smartphones or tablets equipped with the relevant sensors needed for monitoring patients with the selected clinical conditions).

The goals of our work in MobiGuide are:

  • To investigate, develop and evaluate context-awareness provisioning for a decision support system which gives personalized and context-aware guidance to the ambulatory patient in alignment with medical best practice
  • To investigate, design, develop and evaluate generic mechanisms for implementing evidence-based Clinical Decision Support (CDS) on a mobile platform in the context of a larger distributed system.

Our research themes include:

  • How best to provide safe mobile and distributed Clinical Decision Support to patients
  • How to incorporate streaming biosignals and context data into a Clinical Decision Support System
  • How to model and select appropriate subsets of the Clinical Guidelines for projection onto the patient’s personal mobile device (BAN)
  • How to ensure semantic equivalence between: the formalized Clinical Guidelines on the back end; with the projected Clinical Guidelines on the front end; with the patient’s internal cognitive model of their condition and treatment plan
  • How to achieve spatio-temporal reconciliation of back-end (heavy weight) decisions with front end (lightweight) decisions
  • How to ensure appropriate timeliness, quality of context and quality-of-service in distributed Clinical Decision Support.