A machine-to-machine based framework for diabetes lifestyle management

Diabetes is a chronic disease, from which millions of people suffer. To effectively treat diabetes, daily cares such as diet control, physical activities, and glucose measurement should be taken as part of diabetes patients´ daily routine. To alleviate patients from such tedious but crucial daily cares, we propose a machine-to-machine based diabetes lifestyle management system. Our system can permeate patients´ daily life and provide contextual advices based on their current health conditions and the surrounding environments. The essence of the proposed system is an event-triggered rule evaluation mechanism, which provides a flexible and scalable framework for caring diabetes patients in various aspects of daily life. Moreover, the adoption of the sensor-based technologies makes our system require minimal user intervention. With the proposed system, patients can be alerted before doing something harmful for their treatment, even if they are unaware of it. Furthermore, constructive advices can be pushed to patients at the right time, helping them manage lifestyle in a healthy way.