Monwatch : a fuzzy application to monitor the user behavior using wearable trackers

Abstract

Nowadays, the proliferation of wearable devices has enabled monitoring user behaviors and activities in a non-invasive, autonomous, and straightforward way. Moreover, new trend analysis has been boosted by biosignal sensors from wearable trackers, such as inertial or heart rate sensors. The knowledge of such user activity presents personalized monitoring to prevent any kind of physical or neurological disorders through sensor evaluation by an expert. To this end, the definition of key indicators and the display of results and relevant analyses require agile and effective tools. Therefore, this proposal presents a novel web application where the data obtained from a Fitbit Ionic smartwatch wearable are collected, synchronized, and compiled to present a summary of a user's daily activity, which is defined by a linguistic description using fuzzy logic to represent the most relevant Health Key Indicators (HKI). Moreover, an analysis of the user's behavior over time is proposed by inferring relevant patterns from a fuzzy clustering algorithm.