Cognitive-Motor Integration in Assessing Bimanual Motor Skills
arxiv(2024)
摘要
Accurate assessment of bimanual motor skills is essential across various
professions, yet, traditional methods often rely on subjective assessments or
focus solely on motor actions, overlooking the integral role of cognitive
processes. This study introduces a novel approach by leveraging deep neural
networks (DNNs) to analyze and integrate both cognitive decision-making and
motor execution. We tested this methodology by assessing laparoscopic surgery
skills within the Fundamentals of Laparoscopic Surgery program, which is a
prerequisite for general surgery certification. Utilizing video capture of
motor actions and non-invasive functional near-infrared spectroscopy (fNIRS)
for measuring neural activations, our approach precisely classifies subjects by
expertise level and predicts FLS behavioral performance scores, significantly
surpassing traditional single-modality assessments.
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