Multimodal Assessment of Neonatal Pain Using Computer Vision


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Abstract

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 longterm outcomes. The main aim of this project is to develop a robust and comprehensive automatic system that generates a standardized pain assessment comparable to those obtained by conventional nurse-derived pain scores. The continuous monitoring of pain, using affordable, non-invasive, and easily integrable devices, provides immediate pain detection and intervention, and therefore, contribute to improved long term outcomes; i.e., reduce the outcomes of under- and over-treatment. It can also decrease caregivers’ bias and assessment burden.
While further research is needed, the preliminary results of our research showed that the automatic assessment of neonatal pain is a viable and more efficient alternative to the manual assessment.


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Talk / Presentation


Engineering Team:

Dr. Yu Sun, Professor, Computer Science and Engineering, USF
Dr. Dmitry Goldgof, Professor, Computer Science and Engineering, USF
Md Sirajus Salekin, PhD Student, Computer Science and Engineering, USF
Jacqueline Hausmann, PhD Student, Computer Science and Engineering, USF


Medical Team:

Dr. Thao Ho, Assistant Professor, College of Medicine Pediatrics, USF Health, USF
Dr. Stephanie Prescott, Assistant Professor, College of Nursing, USF Health, USF
Dr. Denise Maguire, Associate Professor, College of Nursing, USF Health, USF
Dr. Yangxin Huang, Professor, College of Public Health, USF Health, USF
Marcia Kneusel, RN, Clinical Research Nurse, College of Medicine Pediatrics, USF Health, USF
Sandra Sanchez, RN, Clinical Research Nurse, College of Medicine Pediatrics, USF Health, USF


Collaborators:

Dr. Ghada Zamzmi, Research Fellow, NLM, NIH
Dr. Peter Mouton, Director and Chief Scientific Officer, SRC Biosciences
Dr. Mark Last, Professor and Director of Data Science Research Center, Ben-Gurion University of the Negev, Israel
Dr. Kanwaljeet S. Anand, Professor of Pediatrics, Stanford University, CA, United States


Previous Team Members:

Dr. Terri Ashmeade, Professor, College of Medicine Pediatrics, USF Health, USF
Dr. Rangachar Kasturi, Professor, CSE, USF
Chih-Yun Pai, Master's Student, CSE, USF



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