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Enregistrement W3197599511 · doi:10.1016/s2589-7500(21)00207-7

Automated facial analysis of infant pain expressions: progress and future directions

2021· review· en· W3197599511 sur OpenAlexaboutno aff
Harriet Oster

Notice bibliographique

RevueThe Lancet Digital Health · 2021
Typereview
Langueen
DomaineMedicine
ThématiquePediatric Pain Management Techniques
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFacial expressionFacial Action Coding SystemCoding (social sciences)PsychologyMedicineComputer scienceDevelopmental psychologyArtificial intelligenceMathematicsStatistics

Résumé

récupéré en direct d'OpenAlex

PainChek Infant, a mobile application (app) based on automated facial evaluation and analysis for assessing procedural pain in infants, is a welcome addition to recently developed automated tools for coding infant facial expressions. In The Lancet Digital Health, Kreshnik Hoti and colleagues document the strong psychometric properties and performance of PainChek Infant compared with the widely used manual Neonatal Facial Coding System Revised (NFCS-R).1Hoti K Chivers PT Hughes JD Assessing procedural pain in infants: a feasibility study evaluating a point-of-care mobile solution based on automated facial analysis.Lancet Digit Health. 2021; (published online Sept 1.)https://doi.org/10.1016/S2589-7500(21)00129-1Summary Full Text Full Text PDF PubMed Google Scholar, 2Grunau R E Craig KD Neonatal facial coding system revised: training manual. University of British Columbia, Vancouver, Canada2010Google Scholar Both assessments are based on identifying a small number of facial muscle actions (six in PainChek Infant, five in NFCS-R) present in each of four 10 s video segments of infants undergoing an inoculation procedure (baseline, preparation, during, and recovery). PainChek Infant scores were highly correlated with NFCS-R scores and with the Observer Administered Visual Analogue Scale (ObsVAS). The reported results of the study are impressive, but additional work is needed to address a number of issues, discussed below. One strength of PainChek Infant is the use of the Baby FACS facial action coding system for infants and young children,3Oster H. Baby FACS: facial action coding system for infants and young children. Monograph and coding manual. 2010. New York, NY, USA.Google Scholar a fine-grained, anatomically based manual coding system for identifying the facial muscle action units (AUs) underlying infant facial expressions. Baby FACS coders can precisely and objectively specify the component AUs and AU configurations and their intensity, making it possible for other researchers to compare, replicate, and expand on their findings. Because infants' distress expressions are complex and labile, potentially involving as many as 12 co-occurring AUs and rapid changes in facial configurations, comprehensive manual coding with Baby FACS is painstaking and time consuming. Like most automated facial expression analysis tools, PainChek Infant is designed for rapid identification of pain expressions based on detection of a small number of facial muscle actions.4Zamzmi G Kasturi R Goldgof D Zhi R Ashmeade T Sun Y A review of automated pain assessment in infants: features, classification tasks, and databases.IEEE Rev Biomed Eng. 2018; 11: 77-96Crossref PubMed Scopus (29) Google Scholar A potential limitation is that the authors do not report full-face expressions of co-occurring AUs, which are crucial for research on the temporal dynamics of infant facial expressions, as shown in a 2009 study5O'Neill MC Ahola Kohut S Pillai Riddell R Oster H Age-related differences in the acute pain facial expression during infancy.Eur J Pain. 2019; 23: 1596-1607Crossref PubMed Scopus (7) Google Scholar on changes in AU configurations over the first minute following inoculation and age changes from 2 to 12 months. PainChek's reliance on a small number of AUs could result in both false negative and false positive errors, because three of the six AUs PainChek is trained to detect can occur in both hedonically positive and negative expressions, depending on the other AUs present. Such errors are unlikely in the first 10–15 s following inoculation but could occur later in the minute following inoculation or in older infants, reflecting efforts to regulate negative emotion.5O'Neill MC Ahola Kohut S Pillai Riddell R Oster H Age-related differences in the acute pain facial expression during infancy.Eur J Pain. 2019; 23: 1596-1607Crossref PubMed Scopus (7) Google Scholar A 2018 review4Zamzmi G Kasturi R Goldgof D Zhi R Ashmeade T Sun Y A review of automated pain assessment in infants: features, classification tasks, and databases.IEEE Rev Biomed Eng. 2018; 11: 77-96Crossref PubMed Scopus (29) Google Scholar emphasises the importance of coding pain intensity for assessing the severity of injury or illness and differences in pain responses related to age, ethnicity, or medical conditions. PainChek Infant does not directly assess the intensity of infants' pain elicited distress. The authors instead report a higher number of individual target AUs and higher pain scores (average 5–6 out of 6), in the 10 s inoculation segment than in the other three segments, suggesting greater distress. However, this approach treats all target AUs as interchangeable, potentially ignoring key features of the most and least intense distress expressions and clinically relevant individual differences illustrated in the 2009 study on changes in AU configurations.5O'Neill MC Ahola Kohut S Pillai Riddell R Oster H Age-related differences in the acute pain facial expression during infancy.Eur J Pain. 2019; 23: 1596-1607Crossref PubMed Scopus (7) Google Scholar PainChek Infant developers acknowledge the absence of convincing evidence for the specificity of pain-elicited facial expressions distinct from cry faces shown in non-pain-eliciting contexts, as reviewed by a previous study.6Ahola Kohut S Pillai Riddell R Does the neonatal facial coding system differentiate between infants experiencing pain-related and non-pain-related distress?.J Pain. 2009; 10: 214-220Summary Full Text Full Text PDF PubMed Scopus (33) Google Scholar As acknowledged in the paper use of PainChek Infant should be viewed in the context of verifying and quantifying pain when a source of pain is known or suspected. This absence of evidence is not because infants are generally incapable of showing differentiated facial expressions, as shown in a study of infants aged 2 h and their differential facial responses to sweet, sour, salty, and bitter tastes.7Rosenstein D Oster H Differential facial responses to four basic tastes in newborns.Child Dev. 1988; 59: 1555-1568Crossref PubMed Google Scholar A study involving both Baby FACS coding and automatic detection of nine AUs8Hammal Z Chu WS Cohn JF Heike C Speltz ML automatic action unit detection in infants using convolutional neural network.Int Conf Affect Comput Intell Interact Workshops. 2017; 2017: 216-221PubMed Google Scholar found that infants showed clearly differentiated pleasure and frustration expressions. However, comprehensive Baby FACS coding in a 2007 study9Camras LA Oster H Bakeman R Meng Z Ujiie T Campos J Do infants show distinct negative facial expressions for fear and anger? Emotional expression in 11-month-old European-American, Chinese, and Japanese infants.Infancy. 2007; 11: 131-155Crossref Scopus (41) Google Scholar failed to show the specificity of infants' distress expressions in fear versus frustration-eliciting situations. Other researchers have also failed to show differentiated facial expressions of specific negative emotions. One possible explanation for the apparent absence of specific, differentiated facial expressions of physical pain and intense distress from other causes is that intense cry faces and vocalisations are evolutionary adaptations that serve as general alarm calls, demanding immediate attention from caregivers to identify and remove the source of pain, threat, or anxiety. This view is supported by evidence that intense physical and psychological pain are represented in the same brain area, the dorsal subdivision of the anterior cingulate cortex, in infants and adults.10Eisenberger NI Lieberman MD Why rejection hurts: a common neural alarm system for physical and social pain.Trends Cogn Sci. 2004; 8: 294-300Summary Full Text Full Text PDF PubMed Scopus (771) Google Scholar In summary, PainChek Infant can be a valuable, time saving tool for assessing procedural pain in infants, especially in the first 10–15 s following inoculation. Addressing the issues noted above will require detailed observation by human eyes of variations in pain-elicited responses and changes over time, as well as sophisticated automated facial evaluation and analysis instruments. I declare no competing interests. Assessing procedural pain in infants: a feasibility study evaluating a point-of-care mobile solution based on automated facial analysisPainChek Infant's use of automated facial expression analysis could offer a valid and reliable means of assessing and monitoring procedural pain in infants. Its clinical utility in clinical practice requires further research. Full-Text PDF Open Access

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,977
Score d'incertitude au seuil0,665

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0030,000
Bibliométrie0,0000,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,046
Tête enseignante GPT0,398
Écart entre enseignants0,352 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2021
Routes d'admission1
Résumé présentoui

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