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dc.contributor.authorMartínez-Cruz, Carmen-
dc.contributor.authorMedina-Quero, Javier-
dc.contributor.authorSerrano, José M.-
dc.contributor.authorGramajo, Sergio-
dc.identifier.citationC. 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.es_ES
dc.description.abstractNowadays, 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.es_ES
dc.relation.ispartofIEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Glasgow, UK, 2020es_ES
dc.subjectBiomedical monitoringes_ES
dc.subjectHeart ratees_ES
dc.titleMonwatch: A fuzzy application to monitor the user behavior using wearable trackerses_ES
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