Human vs machine towards neonatal pain assessment: A comprehensive analysis of the facial features extracted by health professionals, parents, and convolutional neural networks.

Neonates are not able to verbally communicate pain, hindering the correct identification of this phenomenon. Several clinical scales have been proposed to assess pain, mainly using the facial features of the neonate, but a better comprehension of these features is yet required, since several related works have shown the subjectivity of these scales. Meanwhile, computational methods have been implemented to automate neonatal pain assessment and, although performing accurately, these methods still lack the interpretability of the corresponding decision-making processes.

Looking at neonatal facial features of pain: do health and non-health professionals differ?

Objective: To analyze the regions that trigger the attention of adults' gaze when assessing pain in newborn infants' pictures and to verify if there are differences between health and non-health professionals.

Method: Experimental study with 84 health professionals and 59 non-health professionals, who evaluated two images of 10 neonates, one at rest and the other during a painful procedure. Each image was shown for 7 seconds on a computer screen, while eye movements were tracked by the Tobii TX300 EyeTracker.

Identification of pain in neonates: the adults' visual perception of neonatal facial features.

Objective: To verify the visual attention of adults when assessing neonatal pain.

Study Design: 143 adults (59% health professionals) evaluated 20 pictures (2 pictures of 10 neonates' faces: at rest; during a painful procedure). Tobii-TX300 tracked the participants' eyes movement.

What Facial Features Does the Pediatrician Look to Decide That a Newborn Is Feeling Pain?

Objective: The study aimed to analyze the gaze fixation of pediatricians during the decision process regarding the presence/absence of pain in pictures of newborn infants.

Study Design: Experimental study, involving 38 pediatricians (92% females, 34.6 ± 9.