Facial expression and pain assessment in the pediatric patient: the primal face of pain

Comparative analysis of artificial intelligence and expert assessments in detecting neonatal procedural pain

Assessing pain in newborns in the NICU is crucial due to their frequent exposure to painful stimuli, yet it's challenging due to the subjective nature of current methods. This study aimed to evaluate the effectiveness of an AI system designed for automatic facial recognition by comparing its performance with the expert opinion of health care provider. This is a secondary analysis from an eye-tracking study, assessing neonatal pain evaluations by healthcare professionals. The performance of AI software, FaceReader 9, was compared to experts' evaluations using a visual-analog scale, focusing on identifying specific facial action units associated with different pain levels. The study found significant differences in AI-generated metrics-arousal and valence-across three stimulus types: non-noxious thermal, short-noxious, and prolonged-noxious, with p-values below 0.001. A strong correlation (r = 0.84, p ≤ .001) was observed between AI metrics and expert ratings. Eleven facial action units were identified as relevant to describe neonatal pain. The findings highlight the AI system's potential in accurately detecting and analyzing newborn facial expressions in response to varying pain intensities, demonstrating a significant correlation with healthcare professionals' assessments. This suggests that AI technology could enhance objective pain assessment in neonates.

The effect of a biofeedback-based virtual reality game on pain, fear and anxiety levels during port catheter needle insertion in pediatric oncology patients: A randomized controlled study

PURPOSE

It is essential to control pain, fear, and anxiety related to medical procedures to improve the well-being of the child and family trying to cope with the disease process. This study investigated the impact of the biofeedback-based virtual reality game (BioVirtualPed) on pain, fear, and anxiety levels during port needle insertion in pediatric oncology patients (POPs).

METHODS

This randomized controlled study was conducted at a hospital between August and December 2023 involving 62 POPs aged 6-12 and their mothers. The intervention group wore a virtual reality headset and a respiratory sensor during the procedure. Data were collected using the Descriptive Information Form, Wong-Baker Pain Assessment Scale, Child Fear Scale, Children's State Anxiety, Satisfaction Scoring-Visual Analog Scale, and ADXL354 Sensor. Statistical analysis was performed using IBM SPSS for Windows Version 24.0.

RESULTS

The intervention group showed lower mean pain scores than the control group (p < 0.001). There was no difference in pre-procedure fear and anxiety scores between groups (p > 0.05 and p > 0.05, respectively). Post-procedure fear and anxiety scores were lower in the intervention group (p < 0.001 and p < 0.001, respectively). The intervention group's mean respiratory rates were lower (p < 0.001), and their satisfaction scores were higher (p < 0.001). Agreements between POPs and mothers on pain, fear, and anxiety scores were good and excellent across groups (p < 0.001).

CONCLUSIONS

The BioVirtualPed reduced procedure-related pain, anxiety, and fear, increased care satisfaction, and had a positive effect on the mean respiratory rate, hence it shows promising results, but these findings need further comfirmation.

The Clinical Suitability of an Artificial Intelligence-Enabled Pain Assessment Tool for Use in Infants: Feasibility and Usability Evaluation Study

BACKGROUND

Infants are unable to self-report their pain, which, therefore, often goes underrecognized and undertreated. Adequate assessment of pain, including procedural pain, which has short- and long-term consequences, is critical for its management. The introduction of mobile health-based (mHealth) pain assessment tools could address current challenges and is an area requiring further research.

OBJECTIVE

The purpose of this study is to evaluate the accuracy and feasibility aspects of PainChek Infant and, therefore, assess its applicability in the intended setting.

METHODS

By observing infants just before, during, and after immunization, we evaluated the accuracy and precision at different cutoff scores of PainChek Infant, which is a point-of-care mHealth-based solution that uses artificial intelligence to detect pain and intensity based solely on facial expression. We used receiver operator characteristic analysis to assess interpretability and establish a cutoff score. Clinician comprehensibility was evaluated using a standardized questionnaire. Other feasibility aspects were evaluated based on comparison with currently available observational pain assessment tools for use in infants with procedural pain.

RESULTS

Both PainChek Infant Standard and Adaptive modes demonstrated high accuracy (area under the curve 0.964 and 0.966, respectively). At a cutoff score of ≥2, accuracy and precision were 0.908 and 0.912 for Standard and 0.912 and 0.897 for Adaptive modes, respectively. Currently available data allowed evaluation of 16 of the 17 feasibility aspects, with only the cost of the outcome measurement instrument unable to be evaluated since it is yet to be determined. PainChek Infant performed well across feasibility aspects, including interpretability (cutoff score defined), ease of administration, completion time (3 seconds), and clinician comprehensibility.

CONCLUSIONS

This work provides information on the feasibility of using PainChek Infant in clinical practice for procedural pain assessment and monitoring, and demonstrates the accuracy and precision of the tool at the defined cutoff score.

An Automatic System for Continuous Pain Intensity Monitoring Based on Analyzing Data from Uni-, Bi-, and Multi-Modality

Pain is a reliable indicator of health issues; it affects patients' quality of life when not well managed. The current methods in the clinical application undergo biases and errors; moreover, such methods do not facilitate continuous pain monitoring. For this purpose, the recent methodologies in automatic pain assessment were introduced, which demonstrated the possibility for objectively and robustly measuring and monitoring pain when using behavioral cues and physiological signals. This paper focuses on introducing a reliable automatic system for continuous monitoring of pain intensity by analyzing behavioral cues, such as facial expressions and audio, and physiological signals, such as electrocardiogram (ECG), electromyogram (EMG), and electrodermal activity (EDA) from the X-ITE Pain Dataset. Several experiments were conducted with 11 datasets regarding classification and regression; these datasets were obtained from the database to reduce the impact of the imbalanced database problem. With each single modality (Uni-modality) experiment, we used a Random Forest [RF] baseline method, a Long Short-Term Memory (LSTM) method, and a LSTM using a sample weighting method (called LSTM-SW). Further, LSTM and LSTM-SW were used with fused modalities (two modalities = Bi-modality and all modalities = Multi-modality) experiments. Sample weighting was used to downweight misclassified samples during training to improve the performance. The experiments' results confirmed that regression is better than classification with imbalanced datasets, EDA is the best single modality, and fused modalities improved the performance significantly over the single modality in 10 out of 11 datasets.

Facial expressions of pain in daily clinical practice to assess postoperative pain in children: Reliability and validity of the facial action summary score

BACKGROUND

Behavioural pain scales are recommended to assess postoperative pain for children who are too young to use self-report tools. Their main limitation is underestimation of pain in the days following an intervention. Although relevant, facial expression is not used in daily clinical practice. This prospective study aimed to assess the validity and reliability of the Facial Action Summary Score (FASS), a five-item scale, to assess postoperative pain until hospital discharge in children <7 years.

METHODS

Assessments of pain and anxiety of 123 children using FASS and validated scales were used to study the psychometric validity of the FASS in clinical practice.

RESULTS

The content validity was previously investigated in a development study. The internal validity of the FASS was high with excellent reliability (intraclass coefficient = 0.94) and a high Cronbach α (0.89). Convergent validity with pain scales (FLACC [Face, Legs, Activity, Cry, Consoling] and FPS-R [Faces Pain Scale - Revised]) was high (r > 0.8). Sensitivity to change was verified by a significant decrease in the score after rescue analgesia. For a threshold of 2/5, the FASS shows excellent specificity (97%) and sensitivity (82%). The low number of false negatives is the main strength of this tool.

CONCLUSIONS

This work highlights the interest in using facial expression in daily clinical practice to manage postoperative pain. The FASS is easy to use with excellent psychometric properties and is particularly sensitive to measure pain in the days following surgery.

SIGNIFICANCE

The aim of this study was to prove that facial expression of pain can be used in clinical practice to measure postoperative pain in children. The reduced number of false negatives is the main strength of this tool.

Assessment of pain in newborn infants

Hospitalized newborn infants experience pain that can have negative short- and long-term consequences and thus should be prevented and treated. National and international guidelines state that adequate pain management requires valid pain assessment. Nociceptive signals cause a cascade of physical and behavioral reactions that alone or in combination can be observed and used to assess the presence and intensity of pain. Units that are caring for newborn infants must adopt sufficient pain assessment tools to cover the gestational ages and pain types that occurs in their setting. Pain assessment should be performed on a regular basis and any detection of pain should be acted on. Future research should focus on developing and validating pain assessment tools for specific situations.

Role of Dental Discomfort Questionnaire-Based Approach in Recognition of Symptomatic Expressions Due to Dental Pain in Children with Autism Spectrum Disorders

AIM

The aim of this study is to investigate whether the Dental Discomfort Questionnaire (DDQ) could help to identify toothaches in children with autism spectrum disorder (ASD).

MATERIALS AND METHODS

This study involved sixty children between the age groups of 6-16 years, attending the day-care schools diagnosed with ASD. Five different groups of children were identified based on the presence of a toothache and/or carious teeth. The DDQ-8 was completed by parents and evaluated by a single examiner. Data were analyzed using descriptive statistics (SPSS version 17), and a correlation was observed between the total DDQ score and the decayed, missing, and filled teeth (dmft-DMFT) score.

RESULTS

Analysis of the data showed that DDQ-8 had a significant correlation with that of DMFT score in a group "with carious teeth but no toothache" (r = 0.497, P = 0.019) and group "with carious teeth and a toothache" (r = 0.682 P = 0.043). A group "without carious teeth where the parents were not sure whether or not the child had a toothache" had higher mean compared to other groups with DDQ-8 scores.

CONCLUSION

There was a significant difference in the total mean DDQ scores when they were compared with that of the control group. Children with high DDQ-8 often had a high DMFT/dmft score. A significant correlation was found when the total DDQ-8 scores were compared with that of the DMFT score.

Objectively measuring pain using facial expression: is the technology finally ready?

Currently, clinicians observe pain-related behaviors and use patient self-report measures in order to determine pain severity. This paper reviews the evidence when facial expression is used as a measure of pain. We review the literature reporting the relevance of facial expression as a diagnostic measure, which facial movements are indicative of pain, and whether such movements can be reliably used to measure pain. We conclude that although the technology for objective pain measurement is not yet ready for use in clinical settings, the potential benefits to patients in improved pain management, combined with the advances being made in sensor technology and artificial intelligence, provide opportunities for research and innovation.

A Quantitative Examination of Extreme Facial Pain Expression in Neonates: The Primal Face of Pain across Time

Many pain assessment tools for preschool and school-aged children are based on facial expressions of pain. Despite broad use, their metrics are not rooted in the anatomic display of the facial pain expression. We aim to describe quantitatively the patterns of initiation and maintenance of the infant pain expression across an expressive cycle. We evaluated the trajectory of the pain expression of three newborns with the most intense facial display among 63 infants receiving a painful stimulus. A modified "point-pair" system was used to measure movement in key areas across the face by analyzing still pictures from video recording the procedure. Point-pairs were combined into "upper face" and "lower face" variables; duration and intensity of expression were standardized. Intensity and duration of expression varied among infants. Upper and lower face movement rose and overlapped in intensity about 30% into the expression. The expression reached plateau without major change for the duration of the expressive cycle. We conclude that there appears to be a shared pattern in the dynamic trajectory of the pain display among infants expressing extreme intensity. We speculate that these patterns are important in the communication of pain, and their incorporation in facial pain scales may improve current metrics.

Exploring the association between pain intensity and facial display in term newborns

BACKGROUND

Facial expression is widely used to judge pain in neonates. However, little is known about the relationship between intensity of the painful stimulus and the nature of the expression in term neonates.

OBJECTIVES

To describe differences in the movement of key facial areas between two groups of term neonates experiencing painful stimuli of different intensities.

METHODS

Video recordings from two previous studies were used to select study subjects. Four term neonates undergoing circumcision without analgesia were compared with four similar male term neonates undergoing a routine heel stick. Facial movements were measured with a computer using a previously developed 'point-pair' system that focuses on movement in areas implicated in neonatal pain expression. Measurements were expressed in pixels, standardized to percentage of individual infant face width.

RESULTS

Point pairs measuring eyebrow and eye movement were similar, as was the sum of change across the face (41.15 in the circumcision group versus 40.33 in the heel stick group). Point pair 4 (horizontal change of the mouth) was higher for the heel stick group at 9.09 versus 3.93 for the circumcision group, while point pair 5 (vertical change of the mouth) was higher for the circumcision group (23.32) than for the heel stick group (15.53).

CONCLUSION

Little difference was noted in eye and eyebrow movement between pain intensities. The mouth opened wider (vertically) in neonates experiencing the higher pain stimulus. Qualitative differences in neonatal facial expression to pain intensity may exist, and the mouth may be an area in which to detect them. Further study of the generalizability of these findings is needed.