Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2021 Jul;16(7):1171-1180.
doi: 10.1007/s11548-021-02408-y. Epub 2021 May 23.

Comparing the effectiveness of augmented reality-based and conventional instructions during single ECMO cannulation training

Julian Wolf  1 , Viviane Wolfer  2 , Maximilian Halbe  3 , Francesco Maisano  4 , Quentin Lohmeyer  2 , Mirko Meboldt  2
Affiliations
Comparative Study

Comparing the effectiveness of augmented reality-based and conventional instructions during single ECMO cannulation training

Julian Wolf et al. Int J Comput Assist Radiol Surg. 2021 Jul.

Abstract

Purpose: Effective training of extracorporeal membrane oxygenation (ECMO) cannulation is key to fighting the persistently high mortality rate of ECMO interventions. Though augmented reality (AR) is a promising technology for improving information display, only a small percentage of AR projects have addressed training procedures. The present study investigates the potential benefits of AR-based, contextual instructions for ECMO cannulation training as compared to instructions used during conventional training at a university hospital.

Methodology: An AR step-by-step guide was developed for the Microsoft HoloLens 2 that combines text, images, and videos from the conventional training program with simple 3D models. A study was conducted with 21 medical students performing two surgical procedures on a simulator. Participants were divided into two groups, with one group using the conventional instructions for the first procedure and AR instructions for the second and the other group using instructions in reverse order. Training times, a detailed error protocol, and a standardized user experience questionnaire (UEQ) were evaluated.

Results: AR-based execution was associated with slightly higher training times and with significantly fewer errors for the more complex second procedure ([Formula: see text], Mann-Whitney U). These differences in errors were most present for knowledge-related errors, resulting in a 66% reduction in the number of errors. AR instructions also led to significantly better ratings on 5 out of the 6 scales used in the UEQ, pointing to higher perceived clarify of information, information acquisition speed, and stimulation.

Conclusion: The results extend previous research on AR instructions to ECMO cannulation training, indicating its high potential to improve training outcomes as a result of better information acquisition by participants during task execution. Future work should investigate how better performance in a single training session relates to better performance in the long run.

Keywords: Medical training; Mixed reality; User guidance; User study.

PubMed Disclaimer

Conflict of interest statement

The authors Julian Wolf, Viviane Wolfer, Maximilian Halbe, Quentin Lohmeyer, and Mirko Meboldt declare no conflict of interest. The author Francesco Maisano declares active grants and institutional support for research and/or receives consulting fees from Abbott, Medtronic, Edwards Lifesciences, Biotronik, Boston Scientific Corporation, NVT, Terumo, Xeltis, and Cardiovalve. He is a shareholder (including stock options) of Cardiogard, Magenta, SwissVortex, Transseptalsolutions, Occlufit, 4Tech, and Perifect and receives royalty income from Edwards Lifesciences.

Figures

Fig. 1
Fig. 1
The two procedures investigated during the study. Each procedure is performed on a different side of the simulator
Fig. 2
Fig. 2
Experimental setup consisting of a simulator, tools for procedure 1 and 2, and a desktop computer. Paper instructions are placed on the left-hand side of the simulator
Fig. 3
Fig. 3
Three information representation types complementing the text-based step-by-step instructions in AR
Fig. 4
Fig. 4
User Experience Questionnaire (UEQ) consisting of 26 questions for the six scales attractiveness (A), perspicuity (P), efficiency (E), dependability (D), stimulation (S), and novelty (N)
Fig. 5
Fig. 5
Training times and error counts for procedure 1 (P1) and 2 (P2)
Fig. 6
Fig. 6
Full error protocol for P2 showing errors of each participant during AR-supported training (blue, n=11) and conventional training (brown, n=10). The rightmost column for each training type shows the error total. Total error counts are calculated by multiplying the errors in each row with the error severity factor, ranging from 1 to 3. The last column shows the error categorization into handling errors (H), knowledge errors (K), or a combination of both (K/H)
Fig. 7
Fig. 7
Point means per UEQ scale
See this image and copyright information in PMC

References

    1. Aldisi M, Alsalemi A, Alhomsi Y, Ahmed I, Bensaali F, Alinier G, Amira A. Design and implementation of a modular ECMO simulator. Qatar Med J. 2017 doi: 10.5339/qmj.2017.swacelso.62. - DOI
    1. Allan CK, Pigula F, Bacha EA, Emani S, Fynn-Thompson F, Thiagarajan RR, Imprescia A, Hayes G, Weinstock P. An extracorporeal membrane oxygenation cannulation curriculum featuring a novel integrated skills trainer leads to improved performance among pediatric cardiac surgery trainees. Simul Healthc. 2013;8(4):221–228. doi: 10.1097/SIH.0b013e31828b4179. - DOI - PubMed
    1. Azimi E, Winkler A, Tucker E, Qian L, Sharma M, Doswell J, Navab N, Kazanzides P (2018)Evaluation of optical see-through head-mounted displays in training for critical care and trauma, pp 1–9 . 10.1109/VR.2018.8446583
    1. Barsom EZ, Graafland M, Schijven MP. Systematic review on the effectiveness of augmented reality applications in medical training. Surg Endosc. 2016;30(10):4174–4183. doi: 10.1007/s00464-016-4800-6. - DOI - PMC - PubMed
    1. Blum T, Heining SM, Kutter O, Navab N (2009) Advanced training methods using an augmented reality ultrasound simulator. In: 2009 8th IEEE international symposium on mixed and augmented reality. IEEE, pp 177–178. 10.1109/ISMAR.2009.5336476

Publication types

MeSH terms

LinkOut - more resources