Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Theoretical and Natural Science

Vol. 5, 25 May 2023


Open Access | Article

Researches Advanced in Intubation Based on SLAM

Dongshuo Gao * 1 , Zidong Liu 2 , Qian Wang 3
1 Yan Tai University, Yantai, Shan Dong province,264000, China
2 Northeastern University, Shenyang Liao Ning Province,110000, China
3 Beijing Technology and Business University, Beijing, 10000, China

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 5, 172-177
Published 25 May 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Dongshuo Gao, Zidong Liu, Qian Wang. Researches Advanced in Intubation Based on SLAM. TNS (2023) Vol. 5: 172-177. DOI: 10.54254/2753-8818/5/20230373.

Abstract

Intubation is an emergency medical procedure used to rescue people who are unconscious or unable to breathe on their own. In the process of tracheal intubation, traditional intubation is difficult due to narrow viewing angle, trachea bending, and occlusion of internal structures. Thanks to the rapid development of simultaneous localization and mapping (SLAM) and virtual reality (AR) technologies, intubation aids are also developing towards intelligence and automation. Based on the collection and analysis of a large number of literatures, this paper conducts an in-depth study of the existing SLAM-based intubation-assisted technology. Specifically, on the basis of analyzing the current research on the application of equipment, visualization schemes, and algorithm schemes in tracheal intubation and intubation training, this paper studies the application progress in terms of efficiency, versatility, accuracy, and user feedback. Further, we summarize the existing key issues and discuss future developments.

Keywords

Visual SLAM, Augmented reality, Intubation.

References

1. Wanigasekara, R. M. R., S. D. M. H. Siyambalapitiya, and S. D. S. H. Dissanayake. Generate Navigations to Guide and Automate Endotracheal Intubation Process. Diss. 2021.

2. Williamson, J. A., et al. "Difficult intubation: an analysis of 2000 incident reports." Anaesthesia and intensive care 21.5 (1993): 602-607.

3. Matek, Jan, et al. "Optical Devices in Tracheal Intubation—State of the Art in 2020." Diagnostics 11.3 (2021): 575.

4. Alismail, Abdullah, et al. "Augmented reality glasses improve adherence to evidence-based intubation practice." Advances in Medical Education and Practice 10 (2019): 279.

5. Sielhorst, Tobias, et al. "Depth perception–a major issue in medical AR: evaluation study by twenty surgeons." International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Berlin, Heidelberg, 2006.

6. Huang, Cynthia Y., et al. "The use of augmented reality glasses in central line simulation:“see one, simulate many, do one competently, and teach everyone”." Advances in medical education and practice 9 (2018): 357.

7. Wu, Haibin, et al. "Semantic SLAM Based on Deep Learning in Endocavity Environment." Symmetry 14.3 (2022): 614.

8. Dias, Patricia L., et al. "Augmented Reality–Assisted Video Laryngoscopy and Simulated Neonatal Intubations: A Pilot Study." Pediatrics 147.3 (2021).

9. Long, Yonghao, et al. "Integrating Artificial Intelligence and Augmented Reality in Robotic Surgery: An Initial dVRK Study Using a Surgical Education Scenario." arXiv preprint arXiv:2201.00383 (2022).

10. Yao, Wenlong, et al. "Emergency tracheal intubation in 202 patients with COVID-19 in Wuhan, China: lessons learnt and international expert recommendations." British journal of anaesthesia 125.1 (2020): e28-e37.

11. Rodríguez, Juan J. Gómez, et al. "Sd-defslam: Semi-direct monocular slam for deformable and intracorporeal scenes." arXiv preprint arXiv:2010.09409 (2020).

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2023)
ISBN (Print)
978-1-915371-53-9
ISBN (Online)
978-1-915371-54-6
Published Date
25 May 2023
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/5/20230373
Copyright
25 May 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated