Evidence map›Paper›PMID 31387292›Full record

ArticleSensors (Basel, Switzerland)2019

Smartphone-Based Platform for Affect Monitoring through Flexibly Managed Experience Sampling Methods.

Carlos Bailon, Miguel Damas, Hector Pomares, Daniel Sanabria, Pandelis Perakakis, Carmen Goicoechea, Oresti Banos

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. SEMABehavior research methods · 2024
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Ubiquitous Computing and Ambient Intelligence-UCAmI.Sensors (Basel, Switzerland) · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Carlos BailonDepartment of Computer Architecture and Technology, CITIC-UGR Research Center, University of Granada, E18071 Granada, Spain. cbailon@ugr.es.ORCID 0000-0001-5049-334X
Miguel DamasDepartment of Computer Architecture and Technology, CITIC-UGR Research Center, University of Granada, E18071 Granada, Spain.
Hector PomaresDepartment of Computer Architecture and Technology, CITIC-UGR Research Center, University of Granada, E18071 Granada, Spain.
Daniel SanabriaMind, Brain & Behavior Research Center, University of Granada, E18071 Granada, Spain.
Pandelis PerakakisMind, Brain & Behavior Research Center, University of Granada, E18071 Granada, Spain.
Carmen GoicoecheaMind, Brain & Behavior Research Center, University of Granada, E18071 Granada, Spain.
Oresti BanosDepartment of Computer Architecture and Technology, CITIC-UGR Research Center, University of Granada, E18071 Granada, Spain. oresti@ugr.es.

Funding

Ministerio de Educación, Cultura y Deporte FPU16/04376
6 · The paper itself

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.

Indexed as

AffectAdolescentAdultFemaleHumansMaleMiddle AgedSmartphoneSurveys and QuestionnairesTelemedicineYoung Adultaffective statecontextflexible esmflexible experience samplingmHealthmobile sensingmoodsmartphone

Identifiers

PMID31387292
PMCPMC6695723

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.