A Fuzzy-Based IoMT Intelligent Data Platform for Enhanced Glucose Data Interpretation and Healthcare Assistance

Diabetes has become one of the most relevant concerns of the century due to the large number of users who are affected by it. Devices that control blood glucose are very diverse and the user and the healthcare professionals in charge need to analyze their output to help them in the most agile way possible. In this proposal, an intelligent data platform based on IoMT devices is presented to retrieve data from diabetic patients in real time. This data is processed and summarized using generation of linguistic descriptions of time series (GLiDTS) techniques, together with Fuzzy Logic and the Computation with Words paradigm, to highlight the most relevant information for a full day. In the application layer of the platform, a web application is provided to visualize raw glucose data and summaries generated for each patient's Time series (TS) of glucose data. This service is intended to serve users as a help to understand their condition and health professionals to speed up the detection of possible problems or wrong habits in their patients using natural language (NL).