@misc{10481/110039,
year = {2020},
url = {https://hdl.handle.net/10481/110039},
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.},
organization = {EU Horizon 2020},
organization = {Pharaon Project Pilots for Healthy and Active Ageing, 85718},
organization = {Spanish Ministry of Science, Innovation and Universities and the European Regional},
organization = {Development Fund, PGC2018-096156-B-I00},
organization = {Andalusian Health Service, PI-0387-2018},
organization = {University of Jaen, EI TIC01},
publisher = {IEEE},
keywords = {Fuzzy logic},
keywords = {Health Key Indicators},
keywords = {Activity recognition},
title = {Monwatch: A fuzzy application to monitor the user behavior using wearable trackers},
doi = {10.1109/FUZZ48607.2020.9177748},
author = {Martínez Cruz, Carmen and Medina Quero, Javier and Gramajo, Sergio and Serrano, José María},
}