Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/10953/1740
Título: Monwatch: A fuzzy application to monitor the user behavior using wearable trackers
Autoría: Martínez-Cruz, Carmen
Medina-Quero, Javier
Serrano, José M.
Gramajo, Sergio
Resumen: 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.
Palabras clave: Biomedical monitoring
Heart rate
Synchronization
Linguistics
Monitoring
Authorization
Databases
Fecha: jul-2020
Editorial: IEEE
Citación: C. Martínez-Cruz, J. M. Quero, J. M. Serrano and S. Gramajo, "Monwatch: A fuzzy application to monitor the user behavior using wearable trackers," 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Glasgow, UK, 2020, pp. 1-8, doi: 10.1109/FUZZ48607.2020.9177748.
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