Evidence map›Paper›PMID 38610510›Full record

ArticleSensors (Basel, Switzerland)2024

Facial Expression Recognition for Measuring Jurors' Attention in Acoustic Jury Tests.

Reza Jamali, Andrea Generosi, Josè Yuri Villafan, Maura Mengoni, Leonardo Pelagalli, Gianmarco Battista, Milena Martarelli, Paolo Chiariotti, Silvia Angela Mansi, Marco Arnesano and 1 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Reza JamaliDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.
Andrea GenerosiDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.ORCID 0000-0001-6173-9616
Josè Yuri VillafanDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.ORCID 0000-0001-6475-2533
Maura MengoniDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.
Leonardo PelagalliDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.
Gianmarco BattistaDepartment of Engineering and Architecture, Università di Parma, Parco Area delle Scienze 181/A, 43124 Parma, Italy.
Milena MartarelliDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.ORCID 0000-0002-7447-6541
Paolo ChiariottiDepartment of Mechanical Engineering, Politecnico di Milano, Via Privata Giuseppe La Masa, 1, 20156 Milano, Italy.ORCID 0000-0001-6287-5521
Silvia Angela MansiUniversità Telematica eCampus, via Isimbardi 10, 22060 Novedrate, Italy.
Marco ArnesanoUniversità Telematica eCampus, via Isimbardi 10, 22060 Novedrate, Italy.ORCID 0000-0003-1700-3075
Paolo CastelliniDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.ORCID 0000-0003-2564-856X

Funding

European Union's Framework Programme for Research and Innovation Horizon 2020 (2014-2020) under the Marie Sklodowska-Curie Grant 858018
6 · The paper itself

Abstract

The perception of sound greatly impacts users' emotional states, expectations, affective relationships with products, and purchase decisions. Consequently, assessing the perceived quality of sounds through jury testing is crucial in product design. However, the subjective nature of jurors' responses may limit the accuracy and reliability of jury test outcomes. This research explores the utility of facial expression analysis in jury testing to enhance response reliability and mitigate subjectivity. Some quantitative indicators allow the research hypothesis to be validated, such as the correlation between jurors' emotional responses and valence values, the accuracy of jury tests, and the disparities between jurors' questionnaire responses and the emotions measured by FER (facial expression recognition). Specifically, analysis of attention levels during different statuses reveals a discernible decrease in attention levels, with 70 percent of jurors exhibiting reduced attention levels in the 'distracted' state and 62 percent in the 'heavy-eyed' state. On the other hand, regression analysis shows that the correlation between jurors' valence and their choices in the jury test increases when considering the data where the jurors are attentive. The correlation highlights the potential of facial expression analysis as a reliable tool for assessing juror engagement. The findings suggest that integrating facial expression recognition can enhance the accuracy of jury testing in product design by providing a more dependable assessment of user responses and deeper insights into participants' reactions to auditory stimuli.

Indexed as

Facial RecognitionAcousticsEmotionsHumansReproducibility of ResultsSoundaffective computingattention recognitiondeep learningfacial expression recognitionjury testing

Identifiers

PMID38610510
PMCPMC11014261

What OpenQuestion holds

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Registered trials

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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.