mlsanityData to 7 Oct 2026

Cognitive-Motor Integration in Assessing Bimanual Motor Skills

arXiv 2404.10889 ↗First posted 16 Apr 2024cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 18 of its 62 references that are in the map. First posted on arXiv 16 Apr 2024.

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18 of 62 references.

References · 18

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6 more
  1. 2022Video-based Formative and Summative Assessment of Surgical Tasks using Deep Learningcited by 8
  2. 2020Where Does Trust Break Down? A Quantitative Trust Analysis of Deep Neural Networks via Trust Matrix and Conditional Trust Densitiescited by 7
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