Skip to main content
SpringerLink
Log in

Educational impact of hand motion analysis in the evaluation of FAST examination skills

  • Original Article
  • Published:
European Journal of Trauma and Emergency Surgery Aims and scope Submit manuscript

Abstract

Purpose

Increasing pressure pushes towards the objective competence assessment of clinical operators. Hand motion analysis (HMA) was introduced to measure surgical and clinical procedures; its recent application to FAST examinations leaves unsolved issues. This study aimed at determining optimal HMA parameters to discriminate between operators’ skill levels, and which FAST tasks are experience-dependent.

Methods

Ten experienced (EG) and 13 beginner (BG) sonographers performed a FAST examination on one female and one male model. A motion capture system returned the duration, working volume, number of movements (absolute and time normalized), and hand path length (absolute and time normalized) of each view.

Results

BG took more time in completing specific views, with a higher working volume (p = 0.003) and longer hands path (p < 0.001). The number of movements was lower in the EG (p < 0.001) and differed between views (p = 0.014). No significant Group/Model differences were found for the normalized number of movements. The LUQ view required a higher number of movements (p < 0.001).

Conclusions

HMA identified kinematic parameters discriminating between proficiency level and critical subtasks in the FAST examination. These findings could be the base for a focused HMA-based evaluation of performances following a proctored training period. There is room to incorporate HMA into simulation metrics and evidence-based credentialing standards for clinical ultrasound applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Dosis A, Aggarwal R, Bello F, Moorthy K, Munz Y, Gillies D, et al. Synchronized video and motion analysis for the assessment of procedures in the operating theater. Arch Surg. 2005;140:293–9.

    Article  Google Scholar 

  2. Glarner CE, Hu YY, Chen CH, Radwin RG, Zhao Q, Craven MW, et al. Quantifying technical skills during open operations using video-based motion analysis. Surgery. 2014;156:729–34.

    Article  Google Scholar 

  3. McGoldrick RB, Davis CR, Paro J, Hui K, Nguyen D, Lee GK. Motion analysis for microsurgical training: objective measures of dexterity, economy of movement, and ability. Plast Reconstr Surg. 2015;136:231e–240e.

    Article  CAS  Google Scholar 

  4. Grober ED, Roberts M, Shin EJ, Mahdi M, Bacal V. Intraoperative assessment of technical skills on live patients using economy of hand motion: establishing learning curves of surgical competence. Am J Surg. 2010;199:81–5.

    Article  Google Scholar 

  5. Sgouros NP, Loukas C, Koufi V, Troupis TG, Georgiou E. An automated skills assessment framework for laparoscopic training tasks. Int J Med Robot Comput Assist Surg. 2018;14:1–10.

    Article  Google Scholar 

  6. D’Angelo A-LD, Rutherford DN, Ray RD, Laufer S, Mason A, Pugh CM. Working volume: evaluating validity evidence of a new measure of surgical efficiency. Am J Surg. 2016;211(2):445–50. 

    Article  Google Scholar 

  7. Ziesmann MT, Park J, Unger B, Kirkpatrick AW, Vergis A, Pham C, et al. Validation of hand motion analysis as an objective assessment tool for the focused assessment with sonography for trauma examination. J Trauma Acute Care Surg. 2015;79:631–7.

    Article  Google Scholar 

  8. Zago M. Time for a comprehensive ultrasound-enhanced trauma management. Eur J Trauma Emerg Surg. 2009;35:339–40.

    Article  Google Scholar 

  9. Padalino P, Bomben F, Chiara O, Montagnolo G, Marini A, Zago M, et al. Healing of blunt liver Injury after non-operative management: role of ultrasonography follow-up. Eur J Trauma Emerg Surg. 2009;35:364–70.

    Article  Google Scholar 

  10. Jeanmonod R, Stawicki SP, Bahner DP, Zago M. Advancing clinician-performed sonography in the twenty-first century: building on the rich legacy of the twentieth century pioneers. Eur J Trauma Emerg Surg. 2016;42:115–8.

    Article  CAS  Google Scholar 

  11. Sahlani L, Thompson L, Vira A, Panchal AR. Bedside ultrasound procedures: musculoskeletal and non-musculoskeletal. Eur J Trauma Emerg Surg. 2016;42:127–8.

    Article  Google Scholar 

  12. Lewis GC, Crapo SA, Williams JG. Critical skills and procedures in emergency medicine. Vascular access skills and procedures. Emerg Med Clin N Am. 2013;31:59–86.

    Article  Google Scholar 

  13. Ratnasekera A, Ferrada P. Ultrasonographic-guided resuscitation of the surgical patient. JAMA Surg. 2018;153:77–8.

    Article  Google Scholar 

  14. Pereira J, Afonso AC, Constantino J, Matos A, Henriques C, Zago M, et al. Accuracy of ultrasound in the diagnosis of acute cholecystitis with coexistent acute pancreatitis. Eur J Trauma Emerg Surg. 2017;43:79–83.

    Article  CAS  Google Scholar 

  15. Ziesmann MT, Park J, Unger BJ, Kirkpatrick AW, Vergis A, Logsetty S, et al. Validation of the quality of ultrasound imaging and competence (QUICk) score as an objective assessment tool for the FAST examination. J Trauma Acute Care Surg. 2015;78:1008–13.

    Article  Google Scholar 

  16. Zago M, Martinez Casas I, Pereira J, Mariani D, Silva AR, Casamassima A, et al. Tailored ultrasound learning for acute care surgeons: a review of the MUSEC (Modular UltraSound ESTES Course) project. Eur J Trauma Emerg Surg. 2016;42:161–8.

    Article  CAS  Google Scholar 

  17. Annet M. Subgroup handedness and the probability of nonright preference for foot or eye and of a nonright-handed parent. Percept Mot Skills. 2001;93(3):911–4.

    Article  Google Scholar 

  18. Todsen T, Tolsgaard MG, Olsen BH, Henriksen BM, Hillingsø JG, Konge L, et al. Reliable and valid assessment of point-of-care ultrasonography. Ann Surg. 2015;261:309–15.

    Article  Google Scholar 

  19. Matyal R, Mitchell J, Hess P, Chaudary B, Bose R, Jainandunsin J, et al. Simulator-based transesophageal echocardiographic training with motion analysis: a curriculum-based approach. Anesthesiology. 2014;121:389–99.

    Article  Google Scholar 

  20. Clinkard D, Holden M, Ungi T, Messenger D, Davison C, Fichtinger G, et al. The development and validation of hand motion analysis to evaluate competency in central line catheterization. Acad Emerg Med. 2015;22:212–8.

    Article  Google Scholar 

  21. Chmarra MK, Klein S, De Winter JCF, Jansen FW, Dankelman J. Objective classification of residents based on their psychomotor laparoscopic skills. Surg Endosc Other Interv Tech. 2010;24:1031–9.

    Article  Google Scholar 

  22. Datta V, Mackay S, Mandalia M, Darzi A. The use of electromagnetic motion tracking analysis to objectively measure open surgical skill in the laboratory-based model. J Am Coll Surg. 2001;193:479–85.

    Article  CAS  Google Scholar 

  23. Hassan EA, Jenkyn TR, Dunning CE. Direct comparison of kinematic data collected using an electromagnetic tracking system versus a digital optical system. J Biomech. 2007;40:930–5.

    Article  Google Scholar 

Download references

Funding

The author received no specific funding for this work.

Author information

Authors and Affiliations

  1. Department of Surgery, Minimally Invasive Surgery Unit, Policlinico San Pietro, Via Forlanini 15, Ponte San Pietro, 24036, Bergamo, Italy

    Mauro Zago & Samantha Bozzo

  2. Department of Biomedical Sciences for Health, Università degli Studi di Milano, via Mangiagalli 31, 20133, Milan, Italy

    Chiarella Sforza

  3. Institute of Molecular Bioimaging and Physiology, National Research Council, Segrate, Italy

    Chiarella Sforza

  4. General Surgery Department, Legnano Hospital, ASST Ovest Milanese, Legnano, MI, Italy

    Diego Mariani

  5. General Surgery Department, S. Maria delle Stelle Hospital, ASST Melegnano e Martesana, Melzo, Milan, Italy

    Matteo Marconi

  6. General Surgery Department, Cattinara University Hospital, Trieste, Italy

    Alan Biloslavo

  7. Department of Surgery, Emergency Surgery Unit, Policlinico Gemelli, Catholic University of the Sacred Heart, Rome, Italy

    Antonio La Greca

  8. Emergency and Trauma Surgery Unit, Humanitas Research Hospital, Via Manzoni, 35, 20090, Rozzano, MI, Italy

    Hayato Kurihara

  9. General Surgery Department, S. Maria delle Stelle Hospital, ASST Melegnano e Martesana Melzo, Cernusco sul Naviglio, MI, Italy

    Andrea Casamassima

  10. Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy

    Francesco Caputo, Manuela Galli & Matteo Zago

  11. Fondazione Istituto Farmacologico Filippo Serpero, Viale Luigi Majno 40, 20122, Milan, Italy

    Matteo Zago

Authors
  1. Mauro Zago
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chiarella Sforza
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Diego Mariani
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Matteo Marconi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alan Biloslavo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Antonio La Greca
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hayato Kurihara
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Andrea Casamassima
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Samantha Bozzo
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Francesco Caputo
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Manuela Galli
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Matteo Zago
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matteo Zago.

Ethics declarations

Conflict of interest

The authors have declared that no competing interests exist.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zago, M., Sforza, C., Mariani, D. et al. Educational impact of hand motion analysis in the evaluation of FAST examination skills. Eur J Trauma Emerg Surg 46, 1421–1428 (2020). https://doi.org/10.1007/s00068-019-01112-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00068-019-01112-6

Keywords

Search

Navigation