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Neonatal pain scales and human visual perception: An exploratory analysis based on facial expression recognition and eye-tracking

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Tipo de produção

Artigo de evento

Data de publicação

2021-01-10

Texto completo (DOI)

Periódico

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Editor

Citações na Scopus

1

Autores

Carlini L. P.
Tamanaka F. G.
Soares J. C. A.
Silva G. V. T.
Heideirich T. M.
Balda R. C. X.
Barros M. C. M.
Guinsburg R.
Carlos E. Thomaz

Orientadores

Resumo

© Springer Nature Switzerland AG 2021.Neonates feel pain and the more premature they are, the more immature are their pain modulation system. Facial expression recognition is a non-invasive method commonly used in clinical practice to identify and assess pain in neonates. In this context, this paper firstly carries out a systematic and state-of-the-art review of several clinical pain scales based on neonatal facial features. Then, we propose and implement an eye-tracking exploratory analysis of the neonate’s facial regions described in these scales to identify the most preferred ones visually for such pain assessment by 4 distinct sample groups of volunteers: 44 physicians, 40 health professionals, 29 parents of newborns and 30 lay people. Our results show differences in all sample groups, either experts or not, between the facial regions considered clinically relevant to the ones expressed implicitly by the human visual perception.

Citação

CARLINI, L. P.; TAMANAKA, F. G.; SOARES, J. C. A.; SILVA, G. V. T.; HEIDEIRICH, T. M.; BALDA, R. C. X.; BARROS, M. C. M. GUINSBURG, R.; THOMAZ, C. E. Neonatal pain scales and human visual perception: An exploratory analysis based on facial expression recognition and eye-tracking. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), p. 62-76, Jan. 2021.

Palavras-chave

Keywords

Facial expression; Newborns; Pain scales

Assuntos Scopus

Clinical practices; Exploratory analysis; Facial expression recognition; Health professionals; Human visual perception; Modulation systems; Noninvasive methods; State-of-the art reviews

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