Enhancement of Surgical Training Practice with the Spring Tensor Heuristic Model

Authors

  • Christopher Chiu Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia
  • Zenon Chaczko Faculty of Engineering and Information Technology, University of Technology, Sydney, Australia

Abstract

The enhancement of surgical simulation tools is an important research study, to assist in the assessment and feedback of medical training practice. In this research, the Spring Tensor Model (STEM) has been used for laparoscopic end-effector navigation through obstacles and high-risk areas. The modelling of the surgical trainer as part of the laparoscopic simulator seeks to emulate the physical environment as a virtualised representation in the integrated infrastructure. Combining sensor network framework paradigms to a surgical knowledge-based construct demonstrates how STEMcan enhance medical practice. The architectural hybridisation of the training framework has enabled the adaptation of STEM modelling techniques for a simulated laparoscopic training methodology. The primary benefit of the architecture is that this integration strategy has resulted in a seamless transition of the heuristic framework to be applied to surgical training.

References

C. Feng, J. W. Rozenblit, A. J. Hamilton, and A. Wytyczak-Partyka, “Defining spatial regions in computer-assisted laparoscopic surgical training,” in Proceedings of the 16th IEEE International Conference andWorkshops on the Engineering of Computer Based Systems (ECBS), San Francisco, California, 2009, pp. 176-183.

C. Feng, J. W. Rozenblit, and A. J. Hamilton, “A hybrid view in a laparoscopic surgery training system,” in Proceedings of the 14thIEEE International Conference and Workshops on the Engineering ofComputer Based Systems (ECBS), Tucson, Arizona, 2007, pp. 339-348.

C. Chiu and Z. Chaczko, An Anticipatory Sanet Environment forTraining and Simulation of Laparoscopic Surgical Procedures, AdvancedMethods and Applications in Computational Intelligence: Topics inIntelligent Engineering and Informatics. Germany: Springer Media, 2012, ISSN 2193-9411.

C. Chiu and Z. Chaczko, et al., “Sensor-Actor Network Solution for Scalable Ad-hoc Sensor Networks,” Electronics & TelecommunicationsQuarterly, International Journal of Electronics & Telecommunications, vol. 58, no. 1, 2012, (KEIT-PAN 2012), ISSN 0867-6747.

Z. Chaczko, R. Klempous, J. Nikodem, and M. Nikodem, “Methods of sensors localization in Wireless Sensor Networks,” in Proceedings of the14th IEEE International Conference and Workshops on the Engineeringof Computer Based Systems (ECBS), 2007, pp. 145-152.

T.-L. Lin and G. Song, “Generalized spring tensor models for protein fluctuation dynamics and conformation changes,” BMC Structural Biology, vol. 10, p. 12, 2010, doi: 10.1186/1472-6807-10-S1-S3. [CrossRef]

Z. Chaczko, J. Nikodem, R. Klempous, and M. Nikodem, “Sensor Localisation Methods in the COSA Framework,” in 2nd Conference onWireless Broadband and Ultra Wideband Communications (AusWireless), 2007, p. 60.

C. Feng, J. W. Rozenblit, and A. Hamilton, “A computerized assessment to compare the impact of standard, stereoscopic and high-definition laparoscopic monitor displays on surgical technique,” Surgical Endoscopy, vol. 24, no. 11, pp. 2743-2748, 2010, doi: 10.1007/s00464-010-1038-6. [CrossRef]

C. Feng and J. W. Rozenblit, et al., “Surgical training and performance assessment using motion tracking,” in Proceedings of the 13th IEEE InternationalConference and Workshops on the Engineering of ComputerBased Systems (ECBS), 2006, URL: http://dev.astec.arizona.edu/home.

M. Georgeff and A. Lansky, “Procedural Knowledge,” Proceedings ofthe IEEE (Special Issue on Knowledge Representation), vol. 74, pp. 1383-1398, 1986.

Z. Chaczko, P. Moses, and C. Chiu, “Cooperative Extended Kohonen Mappings for Wireless Sensor Networks,” Eurocast 2009 Revised SelectedPapers: Lecture Notes in Computer Science, vol. 5717, no. 5717, 2009, Berlin, Germany: Springer Media.

C. Clementi, H. Nymeyer, and J. N. Onuchic, “Topological and energetic factors: What determines the structural details of the transition state ensemble and en-route intermediates for protein folding?” Journal ofMolecular Biology, vol. 298, pp. 937-953, 2000.

M. Clerc, Particle Swarm Optimization. London, UK: ISTE, 2006.

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Published

2015-07-02

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ARTICLES / PAPERS / General