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A novel approach utilizing Genetic Algorithms (GAs) is introduced for the reduction of musculoskeletal (MSK) model complexity. Through this optimization technique, the effectiveness of GAs in streamlining model representations while preserving essential dynamics, is demonstrated. Using this technique, a reduced model using 15 pairs of muscles was shown to yield similar results to those obtained using the full model of 36 muscle-pairs (or 72 muscles) in the HYOID model.

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An Intelligent Optimized Reduced Model of the Musculoskeletal System for the Head-Neck Joints

  • 会议论文

  • 发表日期：

    2025年

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  • Ismail Raslan,
  • Mohammad A. Jaradat,
  • Lotfi Romdhane

摘要

A novel approach utilizing Genetic Algorithms (GAs) is introduced for the reduction of musculoskeletal (MSK) model complexity. Through this optimization technique, the effectiveness of GAs in streamlining model representations while preserving essential dynamics, is demonstrated. Using this technique, a reduced model using 15 pairs of muscles was shown to yield similar results to those obtained using the full model of 36 muscle-pairs (or 72 muscles) in the HYOID model.