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Technical Brief

High-Fidelity Medical Training Model Augmented With Virtual Reality and Conformable Sensors1

[+] Author and Article Information
Yunhe Shen, Zichen Zhao, David Hananel, Daniel Burke, Troy Reihsen, Robert Sweet

CREST,
University of Minnesota,
Minneapolis, MN 55455

Jack Norfleet

RDECOM,
Army Research Laboratory,
Adelphi, MD 20783

DOI: 10.1115/1.4033847Manuscript received March 1, 2016; final manuscript received March 17, 2016; published online August 1, 2016. Editor: William Durfee.

J. Med. Devices 10(3), 030915 (Aug 01, 2016) (3 pages) Paper No: MED-16-1125; doi: 10.1115/1.4033847 History: Received March 01, 2016; Revised March 17, 2016

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References

Schebesta, K. , Hüpfl, M. , Rössler, B. , Ringl, H. , Müller, M. P. , and Kimberger, O. , 2012, “ Degrees of Reality: Airway Anatomy of High-Fidelity Human Patient Simulators and Airway Trainers,” Anesthesiology, 116(6), pp. 1204–1209. [CrossRef] [PubMed]
Goldmann, K. , and Steinfeldt, T. , 2006, “ Acquisition of Basic Fiberoptic Intubation Skills With a Virtual Reality Airway Simulator,” J. Clin. Anesth., 18(3), pp. 173–178. [CrossRef] [PubMed]
Mayrose, J. , Kesavadas, T. , Chugh, K. , Joshi, D. , and Ellis, D. G. , 2003, “ Utilization of Virtual Reality for Endotracheal Intubation Training,” Resuscitation, 59(1), pp. 133–138. [CrossRef] [PubMed]
Rolland, J. , Davis, L. , Hamza-Lup, F. , Daly, J. , Ha, Y. , Glenn, M. , Norfleet, J. , Thumann, R. , and Imielinska, C. , 2003, “ Development of a Training Tool for Endotracheal Intubation: Distributed Augmented Reality,” Stud. Health Technol. Inf., 94, pp. 288–294.
Samosky, J. T. , Baillargeon, E. , Bregman, R. , Brown, A. , Chaya, A. , Enders, L. , Nelson, D. A. , Robinson, E. , Sukits, A. L. , and Weaver, R. A. , 2011, “ Real-Time ‘X-Ray Vision’ for Healthcare Simulation: An Interactive Projective Overlay System to Enhance Intubation Training and Other Procedural Training,” Stud. Health Technol. Inform., 163, pp. 549–551. [PubMed]
Kennedy, C. C. , Cannon, E. K. , Warner, D. O. , and Cook, D. A. , 2014, “ Advanced Airway Management Simulation Training in Medical Education: A Systematic Review and Meta-Analysis,” Crit. Care Med., 42(1), pp. 169–178. [CrossRef] [PubMed]
7-Sigma, and CREST, 2014, “ Smart Anatomical Airway Training Modules Conformable Sensor Technology,” University of Minnesota, Minneapolis, MN.
Konchada, V. , Shen, Y. , Burke, D. , Argun, O. B. , Weinhaus, A. , Erdman, A. G. , and Sweet, R. M. , 2011, “ The Minnesota Pelvic Trainer: A Hybrid VR/Physical Pelvis for Providing Virtual Mentorship,” Stud. Health Technol. Inf., 163, pp. 280–282.
Salud, L. H. , Peniche, A. R. , Salud, J. C. , de Hoyos, A. L. , and Pugh, C. M. , 2011, “ Toward a Simulation and Assessment Method for the Practice of Camera-Guided Rigid Bronchoscopy,” Stud. Health Technol. Inform., 163, pp. 535–541. [PubMed]
Chan, S.-M. , Wong, C.-S. , and Cherng, C.-H. , 2009, “ Determining an Optimal Tracheal Tube Cuff Pressure by the Feel of the Pilot Balloon: A Training Course for Trainees Providing Airway Care,” Acta Anaesthesiol. Taiwan, 47(2), pp. 79–83. [CrossRef] [PubMed]

Figures

Grahic Jump Location
Fig. 1

Virtual and physical models. Upper: airway anatomy versus head–neck position captured in MRI; middle: overlay with reconstructed features; and lower: physical models with a replaceable patch for cricothyrotomy.

Grahic Jump Location
Fig. 2

Learning with motion tracking, see-through animation, and quantitative measurements

Grahic Jump Location
Fig. 3

Prototype simulators

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