A Comprehensive and Context-Sensitive Neonatal Pain Monitoring Using Artificial Intelligence- WIE ILC 2021

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Speaker: Ghada Zamzmi Alzamzmi, Research Fellow, National Institutes of Health

Infants receiving care in the Neonatal Intensive Care Unit (NICU) experience several painful procedures during their hospitalization. Assessing neonatal pain is difficult because the current standard for assessment is subjective, inconsistent, and discontinuous. The intermittent and inconsistent assessment can induce poor treatment and, therefore, cause serious long-term outcomes. In this talk, I will present a comprehensive pain assessment system that utilizes facial expressions along with crying sounds, body movement, and vital sign changes. The proposed automatic system monitors 24/7 and generates a standardized pain assessment. The system achieved 95.56% accuracy when applied to 53 infants hospitalized in a challenging real-world NICU environment. I will also discuss the impact of different demography and contextual factors on pain, and how the proposed system integrates these factors while assessing pain. The excellent performance of the system in monitoring and assessing neonatal pain provides an evidence of the feasibly of using AI for monitoring and accurately assess neonatal pain. Further, the usage of continuous system has the potential to predict pain prior to onset, which provides a window that could support proactive use of non-pharmaceutical pain interventions.

Speaker: Ghada Zamzmi Alzamzmi, Research Fellow, National Institutes of Health

Infants receiving care in the Neonatal Intensive Care Unit (NICU) experience several painful procedures during their hospitalization. Assessing neonatal pain is difficult because the current standard for assessment is subjective, inconsistent, and discontinuous...

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