Analysis, Modelling and Sensing of both Physiological and Environmental Factors for the Customized and Predictive Self-Management of Asthma
Asthma is a life-long chronic inflammatory disease of the airways that is very common worldwide, affecting people of all ages, race and gender. The knowledge and understanding on what triggers an asthma attack and how this triggers can be avoided are critical features for maintaining a good quality of life. As a result, it is important to provide mHealth personalized asthma monitoring services empowering and guiding patients with asthma to manage their own health. To this end, a novel architecture consisting of an ergonomic, compact and efficient sensor-based inhaler device that communicates with a mobile device is proposed. This personal mHealth guidance system can empower patients with asthma to optimize their treatment towards personalized preset goals and guidelines (healthy lifestyle, exercise, dietary habits).
The proposed system will allow asthma patients to manage their disease in their home or at work, eliminating the need to have frequent face-to-face contact with healthcare.
K. Votis, A. Lalos, K. Moustakas, D. Tzovaras. "Analysis, Modelling and Sensing of both Physiological and Environmental Factors for the Customized and Predictive Self-Management of Asthma". In proceedings of the 6th Panhellenic Conference of Biomedical Technology. Athens, Greece, 6-8 May 2015.