Interpretation of motion analysis of laparoscopic instruments based on principal component analysis in box trainer settings
- 185 Downloads
Motion analysis parameters (MAPs) have been extensively validated for assessment of minimally invasive surgical skills. However, there are discrepancies on how specific MAPs, tasks, and skills match with each other, reflecting that motion analysis cannot be generalized independently of the learning outcomes of a task. Additionally, there is a lack of knowledge on the meaning of motion analysis in terms of surgical skills, making difficult the provision of meaningful, didactic feedback. In this study, new higher significance MAPs (HSMAPs) are proposed, validated, and discussed for the assessment of technical skills in box trainers, based on principal component analysis (PCA).
Motion analysis data were collected from 25 volunteers performing three box trainer tasks (peg grasping/PG, pattern cutting/PC, knot suturing/KS) using the EVA tracking system. PCA was applied on 10 MAPs for each task and hand. Principal components were trimmed to those accounting for an explained variance > 80% to define the HSMAPs. Individual contributions of MAPs to HSMAPs were obtained by loading analysis and varimax rotation. Construct validity of the new HSMAPs was carried out at two levels of experience based on number of surgeries.
Three new HSMAPs per hand were defined for PG and PC tasks, and two per hand for KS task. PG presented validity for HSMAPs related to insecurity and economy of space. PC showed validity for HSMAPs related to cutting efficacy, peripheral unawareness, and confidence. Finally, KS presented validity for HSMAPs related with economy of space and knotting security.
PCA-defined HSMAPs can be used for technical skills’ assessment. Construct validation and expert knowledge can be combined to infer how competences are acquired in box trainer tasks. These findings can be exploited to provide residents with meaningful feedback on performance. Future works will compare the new HSMAPs with valid scoring systems such as GOALS.
KeywordsBox trainer Motion analysis EVA tracking system Principal component analysis HSMAP
The authors would like to acknowledge all staff of the Jesús Usón Minimally Invasive Surgery Centre involved in setting up and performing the experiments described in this work.
Compliance with ethical standards
Drs. I. Oropesa, F. Pérez Escamirosa, J.A. Sánchez Margallo, S. Enciso, B. Rodríguez-Vila, A. Minor Martínez, F.M Sánchez-Margallo, P. Sánchez-González, and E.J. Gómez have no conflict of interests or financial ties to disclose.
- 4.Oropesa I, Sánchez-González P, Chmarra MK, Lamata P, Fernández Á, Sánchez-Margallo JA, Jansen FW, Dankelman J, Sánchez-Margallo FM, Gómez EJ (2013) EVA: laparoscopic instrument tracking based on endoscopic video analysis for psychomotor skills assessment. Surg Endosc 27:1029–1039. https://doi.org/10.1007/s00464-012-2513-z CrossRefPubMedGoogle Scholar
- 5.Escamirosa FP, Flores RMO, Oropesa I, Vidal CRZ, Martínez AM (2015) Face, content, and construct validity of the EndoViS training system for objective assessment of psychomotor skills of laparoscopic surgeons. Surg Endosc 29:3392–3403. https://doi.org/10.1007/s00464-014-4032-6 CrossRefPubMedGoogle Scholar
- 7.Oropesa I, Sánchez-González P, Lamata P, Chmarra MK, Pagador JB, Sánchez-Margallo JA, Sánchez-Margallo FM, Gómez EJ (2011) Methods and tools for objective assessment of psychomotor skills in laparoscopic surgery. J Surg Res 171:e81–e95. https://doi.org/10.1016/j.jss.2011.06.034 CrossRefPubMedGoogle Scholar
- 14.Oropesa I, Sánchez-González P, Chmarra MK, Lamata P, Pérez-Rodríguez R, Jansen FW, Dankelman J, Gómez EJ (2013) Supervised classification of psychomotor competence in minimally invasive surgery based on instruments motion analysis. Surg Endosc 28:657–670. https://doi.org/10.1007/s00464-013-3226-7 CrossRefGoogle Scholar