BRAVEHEALTH proposes a patient-centric vision to CVD management and treatment, providing people already diagnosed as subjects at risk with a sound solution for continuous and remote monitoring and real time prevention of malignant events. The solution proposed will be made up of the following sub-systems:

1. WEARABLE UNIT: it is an innovative concept of miniaturised multi-parameter sensor, able to continuously monitoring the most critical parameters needed to perform a thorough diagnosis by means of specific diagnostic and prognostic algorithms running on it. It will be possible both to perform scheduled analysis of critical parameters and to remotely trigger the screening of specific vital signs.
2. REMOTE MANAGEMENT UNIT: it represents the main interface between physicians and the system, providing both automated support, in the form of text messages with information or suggestions to the patient directly generated by the system, and doctor managed supervision, allowing direct communication with the patients with voice/text/chat messages. The most important added value of the this unit is the possibility to be interfaced with existing National Health Records and Physiological Data Banks in order to generating and verifying risk prediction models using advanced data mining approaches.
3. LIFE! GATEWAY: Data acquired by the wearable unit will be relayed to a gateway which represents the means by which the information flow from the user to the Central Supervision Unit. This unit will provide the user with the following functionalities:
    a) Real time communications: in case of anomalies, or simply to suggest specific drugs to be taken, or to advice some particular activity to be performed;
    b) Location aware information, exploiting the positioning capabilities of GPS.
    c) Mobile virtual community for education and support.

The BraveHealth (and Hull) lead on Decision Support in BraveHealth is Dr Darryl N.Davis, the Post Doctoral Research Assistant in Medical DataMining is Dr Jan Bohacik. Dr Chandrasekhar Kambhampati is a co-investigator. The research at the Department of Computer Science, University of Hull addresses Data Mining and Decision Support, in collaboration with university and clinical partners in Finland, Italy and Poland. We will look to providing a standardised approach for Dynamic Decision Support to Clinicians and Risk Assessment of Cardiovascular Disease, across a variety of platforms, guided by the needs of the medical community within the context of e-Health solutions. Data will be gathered from a wearable diagnostic unit (on patients) and clinical records (both National Health Records, and Electronic Patient Records) in both Poland and across Italy. In BRAVEHEALTH, the combination of data mining and more traditional decision support techniques with real-time physiological data from a wearable device will provide reliable advance indication of Aneurysm, Angina, Atherosclerosis, Cerebro-vascular Accident (Stroke), Cerebro-vascular disease, Congestive Heart Failure, Coronary Artery Disease or Myocardial infarction (Heart Attack). The final Decision Support Tool will embody clinical expertise (gathered from our clinical partners) plus embody many types of classifiers including clinical models (e.g. POSSUM and/or APACHE models), neural nets and more graphical tools (e.g. Bayesian Networks and Fuzzy Decision Trees). Specific tasks involved will be:

• Developing specifications for decision support system with context and location awareness provisions, and diagnostic and prognostic algorithms
• Decision Support and Data Mining Strategy Definition. This will establish the interface to other aspects of the BraveHealth project and the data/decision interfaces to other software. It will define the detailed objectives in performing the data mining and define the specific requirements of the Decision Support system.
• Data Analysis and Knowledge Engineering. Explore existing data and biosensor data specifications and establish a data ontology for Data Mining and Decision Support System.
• Data Exploration. And Definition for Data Mining. Formalising a Patient Data Ontology prior to full Data Mining. The data Ontology will also be used as filter system in interfacing Decision Support system to the multitude of data sources available in the BRAVEHEALTH project.
• Data Mining and Classifier Definition. Investigate the parameterisation of data mining techniques to suit each task and classifier type required.
• Decision Support Development. Knowledge engineering of all data mining outcomes, classifiers and built decision models (based on clinical and accepted medical risk analysis models) to work within a Decision Support system.
• Data Mining and Decision Support System Deployment Building of the Decision Support System and subsequent embedding in the BRAVEHEALTH software.