Non-Invasive Health Control through Guided Shopping: A Rule-Based Approach

Monitoring life-long diseases involves not only direct observation and control of patient's vital signs but also the monitoring and the control of the lifestyle and food intake that is proven to have a direct impact on the fluctuation of these vital signs. In this paper, we propose an approach to complement the preventive health monitoring with reactive and proactive monitoring by controlling patient's food intake through customized, entertained, informative guidance, and recommendations that fit their health profile. We adopt a data mining approach to classify different health profiles, and develop two algorithms: the first algorithm supports profile and class constructions, automatic recommendation, and personalization of advices and the second algorithm tailors portion consumption to manage the food intake in an effective way. We also develop a mobile-based virtual reality application to support shopping and make the person experience entertaining. We evaluate our monitoring approach on different health profiles and the results suggest that our guided proactive health monitoring and recommendations lead to a better management of chronic diseases.