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Augmented Reality (AR) Assisted Laryngoscopy for Endotracheal Intubation Training

Publication ,  Conference
Qian, M; Nicholson, J; Tanaka, D; Dias, P; Wang, E; Qiu, L
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2019

Medical trainees require sufficient practice to gain the experience and confidence needed to safely and reliably perform endotracheal intubations. While video laryngoscopy has been used to provide an advanced glottic view that can reduce intubation failure, prevent prolonged intubation time, and reduce repeated intubation attempts, most current devices require visualization on external monitors, disrupting the direct line-of-sight view. These devices also present a deep intra-oral view of the airway that may not be visible during a typical unassisted intubation attempt. As a result, these differences create new challenges to gaining competency in the standard, direct laryngoscopy technique when using video laryngoscopy as a learning tool. To address these challenges, Lenovo Research and the Duke Neonatal Intensive Care Unit jointly developed an Augmented Reality-Assisted Laryngoscopy (ARAL) system using a head-mounted device (HMD). Healthcare providers with minimal intubation experience wore an HMD while performing intubations on an infant manikin with a camera attached to the laryngoscope blade. An enhanced image of the patient’s airway was projected onto the visual field of the HMD, giving the intubators improved oral and glottic visualization while still maintaining focus on the direct line-of-sight view. Our user survey evaluates the effectiveness of the ARAL system, the configuration of the AR view, and the users’ behaviors and preferences when switching their attention between the AR view and the direct line-of-sight view. The approach of using an AR HMD to provide live camera feeds to assist health care providers in performing medical procedures is novel and can be expanded to many other areas of medicine. The advantages of maintaining the direct line-of-sight view during a procedure, in addition to improved supervisory capabilities, have the potential to improve efficacy and efficiency of a wide range of medical and surgical procedures.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783030215644

Publication Date

January 1, 2019

Volume

11575 LNCS

Start / End Page

355 / 371

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

APA
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MLA
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Qian, M., Nicholson, J., Tanaka, D., Dias, P., Wang, E., & Qiu, L. (2019). Augmented Reality (AR) Assisted Laryngoscopy for Endotracheal Intubation Training. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11575 LNCS, pp. 355–371). https://doi.org/10.1007/978-3-030-21565-1_24
Qian, M., J. Nicholson, D. Tanaka, P. Dias, E. Wang, and L. Qiu. “Augmented Reality (AR) Assisted Laryngoscopy for Endotracheal Intubation Training.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11575 LNCS:355–71, 2019. https://doi.org/10.1007/978-3-030-21565-1_24.
Qian M, Nicholson J, Tanaka D, Dias P, Wang E, Qiu L. Augmented Reality (AR) Assisted Laryngoscopy for Endotracheal Intubation Training. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019. p. 355–71.
Qian, M., et al. “Augmented Reality (AR) Assisted Laryngoscopy for Endotracheal Intubation Training.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11575 LNCS, 2019, pp. 355–71. Scopus, doi:10.1007/978-3-030-21565-1_24.
Qian M, Nicholson J, Tanaka D, Dias P, Wang E, Qiu L. Augmented Reality (AR) Assisted Laryngoscopy for Endotracheal Intubation Training. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019. p. 355–371.
Journal cover image

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783030215644

Publication Date

January 1, 2019

Volume

11575 LNCS

Start / End Page

355 / 371

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences