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Medical training simulators have the potential to provide remote and automated assessment of skill vital for medical training. Consequently, there is a need to develop "smart" training devices with robust metrics that can quantify clinical skills for effective training and self-assessment. Recently, metrics that quantify motion smoothness such as log dimensionless jerk (LDLJ) and spectral arc length (SPARC) are increasingly being applied in medical simulators. However, two key questions remain about the efficacy of such metrics how do

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