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.

Pediatricians' focus of sight at pain assessment during a neonatal heel puncture.

Objective: To evaluate the focus of pediatricians' gaze during the heel prick of neonates.

Methods: Prospective study in which pediatricians wearing eye tracker glasses evaluated neonatal pain before/after a heel prtick. Pediatricians scored the pain they perceived in the neonate in a verbal analogue numerical scale (0=no pain; 10=maximum pain).

Looking through Providers' Eyes: Pain in the Neonatal Intensive Care Unit.

Objective: Evaluate the pain of critically ill newborns is a challenge because of the devices for cardiorespiratory support. This study aim to verify the adults' gaze when assessing the critically ill neonates' pain at bedside.

Study Design: Cross-sectional study in which pediatricians, nursing technicians, and parents evaluated critically ill neonates' pain at bedside, for 20 seconds with eye-tracking glasses.

Face-based automatic pain assessment: challenges and perspectives in neonatal intensive care units.

Objective: To describe the challenges and perspectives of the automation of pain assessment in the Neonatal Intensive Care Unit.

Data Sources: A search for scientific articles published in the last 10 years on automated neonatal pain assessment was conducted in the main Databases of the Health Area and Engineering Journal Portals, using the descriptors: Pain Measurement, Newborn, Artificial Intelligence, Computer Systems, Software, Automated Facial Recognition.

Summary Of Findings: Fifteen articles were selected and allowed a broad reflection on first, the literature search did not return the various automatic methods that exist to date, and those that exist are not effective enough to replace the human eye; second, computational methods are not yet able to automatically detect pain on partially covered faces and need to be tested during the natural movement of the neonate and with different light intensities; third, for research to advance in this area, databases are needed with more neonatal facial images available for the study of computational methods.

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.