• Mauro Zago, Chiarella Sforza, Diego Mariani, Matteo Marconi, Alan Biloslavo, Greca Antonio La A Department of Surgery, Emergency Surgery Unit, Policlinico Gemelli, Catholic University of the Sacred Heart, Rome, Italy., Hayato Kurihara, Andrea Casamassima, Samantha Bozzo, Francesco Caputo, Manuela Galli, and Matteo Zago.
• Department of Surgery, Minimally Invasive Surgery Unit, Policlinico San Pietro, Via Forlanini 15, Ponte San Pietro, 24036, Bergamo, Italy.
• Eur J Trauma Emerg Surg. 2020 Dec 1; 46 (6): 1421-1428.

PurposeIncreasing 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.MethodsTen 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.ResultsBG 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).ConclusionsHMA 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.

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