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Updated: Jan 27, 2026

Using Virtual Reality to Transfer Motor Skill Knowledge from One Hand to Another
Published on: September 18, 2017
Educational impact of hand motion analysis in the evaluation of FAST examination skills
Mauro Zago1, Chiarella Sforza2,3, Diego Mariani4
1Department of Surgery, Minimally Invasive Surgery Unit, Policlinico San Pietro, Via Forlanini 15, Ponte San Pietro, 24036, Bergamo, Italy.
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.
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