Alterations in muscular control when performing unfamiliar elbow flexion and extension movements

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Abstract
Purpose: This work analyzes how the Central Nervous System (CNS) adapts its control strategies—muscle synergies and muscular coactivation—during unfamiliar elbow flexion/extension tasks at different velocities. Methods: Twenty healthy participants (10 male; 10 female; age 31 ± 10,2 years) were recruited. Muscular activation of the biceps brachii, brachioradialis, and triceps brachii was recorded using surface electromyography. Elbow movements were tracked using a motion-capture system and an upper body biomechanical model. To represent an unfamiliar task, participants performed the movement in the transverse plane, while the familiar task was performed in the sagittal plane to allow for comparison. Movements were executed at different angular velocities to assess their effect. Muscle synergies were identified using the Non-Negative Matrix Factorization method. Results: The results indicate that the CNS adapts to unfamiliar movements primarily by increasing muscular coactivation to control position and movement velocity (p < 0.001, comparing familiar versus unfamiliar tasks). In contrast, during familiar tasks, the CNS achieves the stability required for faster movements through a higher contribution of muscle synergies (p < 0.05, comparing slowest versus fastest velocity). The statistical results revealed no significant interaction between task familiarity and movement velocity, suggesting that the effect of task familiarity on muscular activation remains consistent across all angular velocities. Conclusion: This work provides valuable insights into how muscle synergies and muscular coactivation complement each other. For an unfamiliar elbow flexion/extension task, the CNS primarily adapts by increasing the activation of all muscles acting on the joint to control position and movement velocity.
Funding Information
  • German Academic Exchange Service (57649580)
  • Medizinische Fakultät, RWTH Aachen University
  • RWTH Aachen University

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