EMG-Assisted Neuromusculoskeletal Models Can Estimate Physiological Muscle Activations and Joint Moments Across the Neck Before Impacts

Pavlos Silvestros, Claudio Pizzolato, David G Lloyd, Ezio Preatoni, Harinderjit S Gill, Dario Cazzola

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Abstract

Knowledge of neck muscle activation strategies prior to sporting impacts is crucial for investigating mechanisms of severe spinal injuries. However, measurement of muscle activations during impacts is experimentally challenging and computational estimations are not often guided by experimental measurements. We investigated neck muscle activations prior to impacts with the use of electromyography (EMG)-assisted neuromusculoskeletal models. Kinematics and EMG recordings from four major neck muscles of a rugby player were experimentally measured during rugby activities. A subject-specific musculoskeletal model was created with muscle parameters informed from MRI measurements. The model was used in the Calibrated EMG-Informed Neuromusculoskeletal Modelling toolbox and three neural solutions were compared: i) static optimisation (SO), ii) EMG-assisted (EMGa) and iii) MRI-informed EMG-assisted (EMGaMRI). EMGaMRI and EMGa significantly (p¡0.01) outperformed SO when tracking cervical spine net joint moments from inverse dynamics in flexion/extension (RMSE = 0.95, 1.14 and 2.32 Nm) but not in lateral bending (RMSE = 1.07, 2.07 and 0.84 Nm). EMG-assisted solutions generated physiological muscle activation patterns and maintained experimental co-contractions significantly (p¡0.01) outperforming SO, which was characterised by saturation and non-physiological "on-off" patterns. This study showed for the first time that physiological neck muscle activations and cervical spine net joint moments can be estimated without assumed a priori objective criteria prior to impacts. Future studies could use this technique to provide detailed initial loading conditions for theoretical simulations of neck injury during impacts.

Original languageEnglish
Article numberBIO-21-1051
JournalJournal Of Biomechanical Engineering
Early online date24 Sep 2021
DOIs
Publication statusE-pub ahead of print - 24 Sep 2021

Keywords

  • EMG
  • musculoskeletal system
  • modelling and simulation
  • Rugby
  • Injury prevention

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