D1.1 Analysis of current practices

The main objective of WP1 “User needs, system requirements, architecture” of the MyAirCoach project is the definition of the overall user needs, the architecture and the system specifications of the myAirCoach infrastructure, in order to define and deliver a number of representative use cases and user scenarios, exemplifying the novelties of the myAirCoach framework. The first deliverable of WP1 provides the baseline definition for commencing the work of the project, by reporting on the latest developments in the specific areas that myAirCoach will address. The presented work is divided into three parts that cover the current advances in the areas of : i) inhaler devices and sensors for asthma’s disease, ii) computational modelling of lung behaviour and iii) self-management, decision support and personal guidance systems for patients with asthma disease.

Initially, we provide a short technical summary of the available asthma related devices and more specifically of the products that could offer crucial insights for the development of the sensing capabilities of the myAirCoach system. This summary is then complemented, by describing other critical parameters that could be monitored, (e.g., physiological, environmental) along with the corresponding hardware components that need to be integrated to the proposed system. Special attention is given to the role of fractional exhaled nitric oxide (FeNO), that is capable of providing additional information regarding the level of bronchial inflammation.

The second part of this deliverable is devoted on the review of the methods for developing computational models that simulate the behaviour of the pulmonary system including structure, mechanical representation, computational fluid dynamics and biological/chemical properties of the lung. Different methods for linking those models with the different environmental and physiological sensing parameters, is also described in order to provide all necessary means for integrating the Computational Model results with the measurements of the different sensors and self-reports, providing predictions that could be used to alarm patient on potential upcoming dangerous events, like asthma exacerbations. This information could also supplement the input to the personal guidance system that will be the main topic of discussion in the last part of this document.

Finally, we focus on providing a review of personal guidance applications and virtual community platforms that could be essential for producing the final myAirCoach integrated system, explicitly taking into account security and privacy issues. A short description of different interactive information visualization techniques that allow the representation of medical information and the end user (e.g., patients, caregivers) interaction with the system is presented. This deliverable is concluded by summarizing different cloud-based software modules responsible for the customization and co-design of both the myAirCoach application and the Virtual Community Platform ensuring the effective communication and collaboration between patients and their caregivers.