A visual perception framework to analyse neonatal pain in face images

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2020-06-05
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CARLINI, L. P.
SOARES, J. C. A.
SILVA, G. V. T.
HEIDEIRICH, T. M.
BALDA, R. C. X.
BARROS, M. C .M.
GUINSBURG, R.
Carlos E. Thomaz
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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CARLINI, L. P.; SOARES, J. C. A.; SILVA, G. V. T.; HEIDEIRICH, T. M.; BALDA, R. C. X.; BARROS, M. C .M.; GUINSBURG, R.; THOMAZ, C. E. A visual perception framework to analyse neonatal pain in face images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 12131 LNCS, p. 233-243, jun. 2020.
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© Springer Nature Switzerland AG 2020.Neonatal pain assessment by facial expressions are currently among the most used methods in the clinical practice, due to the fact that the human being, at an early stage of life, is not able to verbally communicate pain. Therefore, the pain assessment and its subsequently treatment are carried out by an indirect and non-objective analysis of reactions of the neonate when facing a painful procedure. This work proposes a computational framework to investigate the visual perception patterns of adults when assessing pain in order to better understand the relevance of neonate facial features commonly used by health professionals when evaluating pain in newborn babies. The results showed that there is no statistical difference of visual fixation among all groups of volunteers, whether they are health professionals or not.

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