Real‐Time Holographic Feedback via Mixed Reality Sensorized Laryngoscope Training System Enhances Pediatric Intubation Training

Pediatric endotracheal intubation (ETI) is a technically demanding procedure in which novices apply excessive force and torque. Traditional manikin training and instructor feedback lack quantitative, real‐time performance data. This work introduces a Mixed Reality Sensorized Laryngoscope Training System, integrating a sensorized laryngoscope with head‐mounted holographic feedback to visualize torque in real time. In Study 1, six subjects performed a force‐tracking task with a simplified laryngoscope while viewing three holographic visualizations (bar, ring, and line graphs). Bar‐graph feedback yielded the lowest tracking error ( p < 0.05). Eye‐tracking showed ring graphs elicited significantly more saccades than line graphs ( p < 0.05), consistent with higher visual demand, while bar and line graphs produced comparable saccade behavior. In Study 2, ten novices, split into mixed‐reality and control groups, performed pediatric ETI on a manikin with or without real‐time torque feedback during training. In post‐training trials without feedback, the feedback‐trained group maintained torque more consistently within expert‐defined ranges without increasing intubation time. These results suggest real‐time mixed‐reality feedback can produce lasting improvement in torque regulation during simulated pediatric ETI while preserving procedural efficiency. As a pilot study ( and ), these findings motivate larger‐scale validation and inform future telesimulation‐based training.

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Publication Details

Journal
Advanced Robotics Research
Published
2026-06-13
DOI
https://doi.org/10.1002/adrr.202600005
Primary Topic
Simulation-Based Education in Healthcare
Type
article
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article

Real‐Time Holographic Feedback via Mixed Reality Sensorized Laryngoscope Training System Enhances Pediatric Intubation Training

Ryman Hashem, Ningzhe Hou, Perla Maiolino, Liang He et al.
Advanced Robotics Research
Simulation-Based Education in Healthcare
article

Real‐Time Holographic Feedback via Mixed Reality Sensorized Laryngoscope Training System Enhances Pediatric Intubation Training

Ryman Hashem, Ningzhe Hou, Perla Maiolino, Liang He, Louis Halamek, Jiaqi Li
article en

Abstract

Pediatric endotracheal intubation (ETI) is a technically demanding procedure in which novices apply excessive force and torque. Traditional manikin training and instructor feedback lack quantitative, real‐time performance data. This work introduces a Mixed Reality Sensorized Laryngoscope Training System, integrating a sensorized laryngoscope with head‐mounted holographic feedback to visualize torque in real time. In Study 1, six subjects performed a force‐tracking task with a simplified laryngoscope while viewing three holographic visualizations (bar, ring, and line graphs). Bar‐graph feedback yielded the lowest tracking error ( p < 0.05). Eye‐tracking showed ring graphs elicited significantly more saccades than line graphs ( p < 0.05), consistent with higher visual demand, while bar and line graphs produced comparable saccade behavior. In Study 2, ten novices, split into mixed‐reality and control groups, performed pediatric ETI on a manikin with or without real‐time torque feedback during training. In post‐training trials without feedback, the feedback‐trained group maintained torque more consistently within expert‐defined ranges without increasing intubation time. These results suggest real‐time mixed‐reality feedback can produce lasting improvement in torque regulation during simulated pediatric ETI while preserving procedural efficiency. As a pilot study ( and ), these findings motivate larger‐scale validation and inform future telesimulation‐based training.

Advanced Robotics Research
University of Oxford (GB), Science Oxford (GB), Oxford Institute for Energy Studies (GB), Stanford University (US)
Openalex Percentile: Top 6%
Simulation-Based Education in Healthcare
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Real‐Time Holographic Feedback via Mixed Reality Sensorized Laryngoscope Training System Enhances Pediatric Intubation Training — Ryman Hashem, Ningzhe Hou, et al. · Advanced Robotics Research (2026) | TGRS Research Map | TGRS