Evidence map›Paper›PMID 30894584›Full record

ArticleScientific reports2019

Detecting changes in facial temperature induced by a sudden auditory stimulus based on deep learning-assisted face tracking.

Saurabh Sonkusare, David Ahmedt-Aristizabal, Matthew J Aburn, Vinh Thai Nguyen, Tianji Pang, Sascha Frydman, Simon Denman, Clinton Fookes, Michael Breakspear, Christine C Guo

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  13. Face Alignment in Thermal Infrared Images Using Cascaded Shape Regression.International journal of environmental research and public health · 2021
    Article
  14. Article
  15. Review
  16. Where Do We Stand in the Domestic Dog (Frontiers in psychology · 2020
    Review
  17. 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

10 authors.

Saurabh SonkusareQIMR Berghofer Medical Research Institute, Brisbane, Australia.
David Ahmedt-AristizabalImage and Video Research Laboratory, SAIVT, Queensland University of Technology, Brisbane, Australia.ORCID 0000-0003-1598-4930
Matthew J AburnQIMR Berghofer Medical Research Institute, Brisbane, Australia.
Vinh Thai NguyenQIMR Berghofer Medical Research Institute, Brisbane, Australia.ORCID 0000-0001-7265-671X
Tianji PangSchool of Automation, Northwestern Polytechnical University, Xi'an, China.
Sascha FrydmanQIMR Berghofer Medical Research Institute, Brisbane, Australia.
Simon DenmanImage and Video Research Laboratory, SAIVT, Queensland University of Technology, Brisbane, Australia.
Clinton FookesImage and Video Research Laboratory, SAIVT, Queensland University of Technology, Brisbane, Australia.
Michael BreakspearQIMR Berghofer Medical Research Institute, Brisbane, Australia.
Christine C GuoQIMR Berghofer Medical Research Institute, Brisbane, Australia. christine.cong@gmail.com.ORCID 0000-0003-1530-0172

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thermal Imaging (Infrared-Imaging-IRI) is a promising new technique for psychophysiological research and application. Unlike traditional physiological measures (like skin conductance and heart rate), it is uniquely contact-free, substantially enhancing its ecological validity. Investigating facial regions and subsequent reliable signal extraction from IRI data is challenging due to head motion artefacts. Exploiting its potential thus depends on advances in analytical methods. Here, we developed a novel semi-automated thermal signal extraction method employing deep learning algorithms for facial landmark identification. We applied this method to physiological responses elicited by a sudden auditory stimulus, to determine if facial temperature changes induced by a stimulus of a loud sound can be detected. We compared thermal responses with psycho-physiological sensor-based tools of galvanic skin response (GSR) and electrocardiography (ECG). We found that the temperatures of selected facial regions, particularly the nose tip, significantly decreased after the auditory stimulus. Additionally, this response was quite rapid at around 4-5 seconds, starting less than 2 seconds following the GSR changes. These results demonstrate that our methodology offers a sensitive and robust tool to capture facial physiological changes with minimal manual intervention and manual pre-processing of signals. Newer methodological developments for reliable temperature extraction promise to boost IRI use as an ecologically-valid technique in social and affective neuroscience.

Indexed as

Acoustic StimulationDeep LearningAlgorithmsBody TemperatureElectrocardiographyFaceGalvanic Skin ResponseHumansResearch DesignSpectroscopy, Near-Infrared

Identifiers

PMID30894584
PMCPMC6426955

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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.