# Neonatal Endotracheal Intubation: Enhancing Training Through Computer Simulation and Automated Evaluation

> **NIH NIH R01** · GEORGE WASHINGTON UNIVERSITY · 2021 · $314,927

## Abstract

Project Summary
Neonatal endotracheal intubation (ETI) is a time-sensitive resuscitation procedure! essential for ventilation of
newborns. It requires an unusually high level of skill due to the narrow airways, relatively large tongue, anterior
glottic position, and low respiratory reserve of neonates (Bercic, Pocajt et al. 1978). Given the difficulty of the
procedure and the high rate of complications in untrained hands, effective training is crucial. However,
intubation success rates for pediatric residents are low under current resuscitation training programs and show
little improvement between years 1-3 of residency (23-25%) (O'Donnell, Kamlin et al. 2006; Haubner, Barry et
al. 2013). There is a pressing need to understand the factors that lead to poor training results and for
innovative training modalities that can bridge the gap left by traditional training and thereby allow rapid skill
acquisition.
We hypothesize that current training and assessment methods suffer from 4 key weaknesses: (1) Poor
realism: manikin and simulator-based training typically provide little variation in anatomy or difficulty level—key
requirements for developing expertise (Dreyfus, Athanasiou et al. 1986)—and do not realistically model the
look, feel, and motions of real tissue. (2) Subjective, highly variable, and resource-intensive assessment
methods: training opportunities are limited by the availability of expert instructors. (3) Poor visualization:
learners have poor knowledge about what went wrong and how to improve; they cannot see exactly what is
going on inside the manikin or the patient and cannot directly monitor their actions relative to idealized, expert
performance. (4) Assessment under artificially ideal conditions: assessments of ETI performance in classroom
settings likely overestimate trainees' skill level because they do not mimic the stressors and distractions that
are inherent in the real clinical environment.
Technology-enhanced ETI simulators can resolve all of these key weaknesses: We have conducted
preliminary work (Hahn, Li et al. 2016; Soghier, Li et al. 2014) on an augmented reality (AR (Azuma 1997))
manikin simulator driven by the motions of the trainee and physical manikin in real time that 1) provides a
quantitative assessment of ETI technique and 2) allows the trainee to visualize the motion of the laryngoscope
inside the manikin. The assessment score can provide feedback during the performance, as well as constitute
part of the evaluation of the trainee's skill. Work under this proposal will build on this preliminary work. The
specific aims are to: extend the current augmented reality (AR) manikin simulator to a virtual reality (VR)
computer simulator and validate, extend and validate automated assessment and visualization algorithm for
ETI, study training effectiveness by testing groups of pediatric residents across 3 years to quantify the effect of
technology-enhanced methods relative to the current training regimen in terms of bo...

## Key facts

- **NIH application ID:** 10194566
- **Project number:** 5R01HD091179-05
- **Recipient organization:** GEORGE WASHINGTON UNIVERSITY
- **Principal Investigator:** JAMES K HAHN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $314,927
- **Award type:** 5
- **Project period:** 2017-08-22 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10194566

## Citation

> US National Institutes of Health, RePORTER application 10194566, Neonatal Endotracheal Intubation: Enhancing Training Through Computer Simulation and Automated Evaluation (5R01HD091179-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10194566. Licensed CC0.

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