Artificial Intelligence Based Pain Assessment Technology in Clinical Application of Real-World Neonatal Blood Sampling

Abstract

Background: Accurate neonatal pain assessment (NPA) is the key to neonatal pain management, yet it is a challenging task for medical staff. This study aimed to analyze the clinical practicability of the artificial intelligence based NPA (AI-NPA) tool for real-world blood sampling. Method: We performed a prospective study to analyze the consistency of the NPA results given by a self-developed automated NPA system and nurses’ on-site NPAs (OS-NPAs) for 232 newborns during blood sampling in neonatal wards, where the neonatal infant pain scale (NIPS) was used for evaluation. Spearman correlation analysis and the degree of agreement of the pain score and pain grade derived by the NIPS were applied for statistical analysis. Results: Taking the OS-NPA results as the gold standard, the accuracies of the NIPS pain score and pain grade given by the automated NPA system were 88.79% and 95.25%, with kappa values of 0.92 and 0.90 (p < 0.001), respectively. Conclusion: The results of the automated NPA system for real-world neonatal blood sampling are highly consistent with the results of the OS-NPA. Considering the great advantages of automated NPA systems in repeatability, efficiency, and cost, it is worth popularizing the AI technique in NPA for precise and efficient neonatal pain management.

Video-Based versus On-Site Neonatal Pain Assessment in Neonatal Intensive Care Units: The Impact of Video-Based Neonatal Pain Assessment in Real-World Scenario on Pain Diagnosis and Its Artificial Intelligence Application

“…The results in Table 3 show that compared with the on-site evaluation, the accuracy of the NIPS pain grade given by the VB-NPA with neonatal pain videos captured in a real-world NICU scenario was 96.98%, and the agreement between the two groups was compared, with a kappa value of 0.926 ( p < 0.001), thus indicating that, although the accuracy of VB-NPA was affected by real-world noises in the videos, it was not inferior to OS-NPA. Previous studies have shown that compared to OS-NPA, VB-NPA could significantly reduce the time spent on pain evaluation [ 22 , 23 , 24 , 25 ]. Meanwhile, with the advances in technology and operating equipment, it is easier to video-record painful procedures.…”

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

“… Identify the specific signals and patterns from each facial sensor that correlate with the pain stimulus. 34 Cheng, X et al . (2022) / China Artificial Intelligence Based Pain Assessment Technology in Clinical Application of Real-World Neonatal Blood Sampling.…”

“… Tests will be performed in further studies. 34 It was implemented with the client-server model and designed to run on the mobile nursing personal digital assistant device. /Scale: NIPS Own Base (232 newborns with a mean gestational age of 33.93 ± 4.77 weeks).…”

“… Evaluate the intensity of the pain, classifying it as mild, moderate, or severe pain; Future applications may also include patient populations incapable of expressing pain (children with disability, adults with dementia, or mechanically ventilated patients). 34 It is not possible to accurately assess pain scores or pain grades with AI technology; The automated NPA system currently requires an additional nurse to record the video; Does not report whether the system will be able to evaluate faces with medical devices. Automate the entire process by recording video with bedside cameras in the future.…”

Human vs machine towards neonatal pain assessment: a comparison of the facial features extracted by adults and convolutional neural networks

“…In Cheng et al (2022), it is provided three approaches to generate explanations: directly from a transparent machine learning algorithm (e.g., Decision Trees), or from an algorithm that creates a post-hoc modelling, or visualisation tool. We benefit from the third approach, using mechanisms external to the main classification model to help describe the decision-making process of it.…”