2024/04/16 by Erim Yanık, Xavier Intes, Yanik, Erim +3
Neuroscience · Psychology · #Artificial Intelligence (cs.AI) #Children's Physical and Motor Development #FOS: Computer and information sciences #Hemispheric Asymmetry in Neuroscience #Motor Control and Adaptation
paper · pdf · doi:10.48550/arxiv.2404.10889
openalex publication_date 2024/04/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.