Monwatch: A fuzzy application to monitor the user behavior using wearable trackers
Year: 2020
Type: conference-paper
Abstract: Nowadays, the proliferation of wearable devices has enabled monitoring user behaviours 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 a personalized monitoring to prevent any kind of physical or neurological disorders through the sensor evaluation by an expert. To this end, the definition of key indicators and the display of results and relevant analyses require of 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 an 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 behaviour over time is proposed by inferring relevant patterns from a fuzzy clustering algorithm.
Institutions: Universidad de Jaén, National Technological University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3082885076