@misc{10481/61705,
year = {2019},
month = {8},
url = {http://hdl.handle.net/10481/61705},
abstract = {The identification of daily life events that trigger significant changes on our affective state
has become a fundamental task in emotional research. To achieve it, the affective states must be
assessed in real-time, along with situational information that could contextualize the affective data
acquired. However, the objective monitoring of the affective states and the context is still in an early
stage. Mobile technologies can help to achieve this task providing immediate and objective data
of the users’ context and facilitating the assessment of their affective states. Previous works have
developed mobile apps for monitoring affective states and context, but they use a fixed methodology
which does not allow for making changes based on the progress of the study. This work presents a
multimodal platform which leverages the potential of the smartphone sensors and the Experience
Sampling Methods (ESM) to provide a continuous monitoring of the affective states and the context
in an ubiquitous way. The platform integrates several elements aimed to expedite the real-time
management of the ESM questionnaires. In order to show the potential of the platform, and evaluate
its usability and its suitability for real-time assessment of affective states, a pilot study has been
conducted. The results demonstrate an excellent usability level and a good acceptance from the users
and the specialists that conducted the study, and lead to some suggestions for improving the data
quality of mobile context-aware ESM-based systems.},
organization = {This work has been partially supported by the Spanish Ministry of Science, Innovation and Universities
(MICINN) Projects PGC2018-098813-B-C31 and RTI2018-101674-B-I00 together with the European Fund for
Regional Development (FEDER). This work has also been partially supported by the FPU Spanish Grant
FPU16/04376 and the Dutch UT-CTIT project HoliBehave.},
publisher = {MDPI},
keywords = {Affective state},
keywords = {Flexible experience sampling},
keywords = {Flexible esm},
keywords = {Mobile sensing},
keywords = {Mood},
keywords = {Context},
title = {Smartphone-Based Platform for Affect Monitoring through Flexibly Managed Experience Sampling Methods},
doi = {10.3390/s19153430},
author = {Bailón Romacho, Carlos and Damas Hermoso, Miguel and Pomares Cintas, Héctor Emilio and Sanabria Lucena, Daniel and Perakakis, Pandelis and Goicoechea, Carmen and Ubago Jiménez, José Luis},
}