Stroke is a leading cause of death and disability, with an estimated total cost of approximately €64 billion per year in Europe.
Recurrent stroke carries with it a greater risk than first-ever stroke for death and disability. In the same time, secondary stroke prevention has proved not very successful in the general population. One of the main reasons for these poor results is the fact that quality healthcare outcomes depend upon patients' adherence to recommended treatments. This adherence remains a challenge, since people do not always understand or remember well enough what they are supposed to do to follow the treatment or to improve their general health status. Furthermore, they do not feel actively involved in a collaborative decision-making process with their physician(s). On the other end of the patient-healthcare professionals relationship, healthcare professionals need to have an understanding of why, how, and when patients do not engage in optimal self-management behaviours in order to engage in a fruitful collaboration with their patients and co-manage more efficiently a person’s health condition.
Thus, better results in the prevention of stroke could be achieved if we improved patients’ adherence to treatments, the management and self-management of stroke risk factors (e.g. high blood pressure, unhealthy diet, alcohol consumption, physical inactivity) and the collaboration between patients and healthcare professionals. This is the main objective of the STARR project. We developed a modular, affordable, and easy-to-use system, which informs stroke survivors about the relation between their daily activities (e.g. medication intake, physical and cognitive exercise, diet, social contacts) and the risk of having a secondary stroke. The STARR system is based on an existing computational predictive model of stroke risk factors; a number of connected objects integrating off-the-shelf sensors for real-time sensing of proprioceptive functions and simple movements; a vision-based sensing platform for measuring the execution of more complex rehabilitation tasks, as well as for evaluating the stroke survivor’s emotional state; a Decision-Support System (DSS) integrating and processing all this information, evaluating progress towards the achievement of given rehabilitation and lifestyle change goals, and providing the basis for personalised diagnosis and prognosis of the stoke survivor’s health status and of a secondary stroke; a number of cloud services assuring the relations with informal and formal carers, peers and medical staff; a processing unit collecting and distributing the information from the sensors to the different modules; self-management services for stroke survivors giving recommendations and support for improving the adherence to prescribed treatments and adopting a healthier lifestyle.
