A two stages fuzzy logic approach for Internet of Things (IoT) wearable devices
Amilcare Francesco Santamaria, Pierfrancesco Raimondo, Floriano De Rango, Abdon Serianni · 2016
In the last few years the process of monitoring people health status has grown in interest in the researcher community and led to the develop of new devices able to detect and analyse information gathered from many kind of sensors. These devices are commonly designed to monitor or diagnose disease in the medical field. Moreover, a remarkable interest is growing in the field of sports. In amateur activities such as jogging, running, climbing a set of smart devices are used to improve and monitor performances. Another field of interest is represented by those people that wants to monitor their health status by using low cost devices. In this work we propose a two stage fuzzy logic approach in which the device tries to learn and fit customer habits in order to discover outlier warning signals. The two stages approach proposed consists of monitoring the normal activities of the user in order to build a reference of its condition; Then a real-time monitoring and analysis of gathered data from body sensors is accomplished. User status is carried out using a Fuzzy Logic based network. First stage will give us the current activity of the user while second stage will provide information about health status in terms of heart rate.