Health science reports · 2026
Investigating the Similarity and the Combination of Muscle Synergies During Multi and Uniplanar Upper Limb Motions by Musculoskeletal Model: An Experimental and Computational Study.
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Farrokhnia Morteza, Haghpanah Seyyed Arash, Ghavanloo Esmaeal, Karami Abbas
Аннотация
BACKGROUND AND AIMS: Understanding how the central nervous system generates muscle activation patterns for performing diverse movements remains a significant challenge in motor control. This study aims to evaluate the similarities and combinations of complex multiplanar upper limb movements in relation to the synergies of basic motions, using both experimental and computational approaches.
METHODS: Three healthy participants performed both proprioceptive neuromuscular facilitation (PNF) patterns and basic upper limb motions. Electromyography (EMG) and kinematic data were recorded simultaneously. A verified musculoskeletal (MS) model, calibrated with computed muscle control (CMC) results and processed EMG data, was used to estimate muscle activations. Muscle synergies and corresponding activation coefficients were extracted using non-negative matrix factorization (NNMF), and variance accounted for (VAF) metrics were applied to determine the optimal number of synergies. Spearman's rank correlation and least squares optimization were employed to assess the similarity and combination of synergy patterns between motion types.
RESULTS: Four muscle synergies were identified for both basic and complex movements. A shared synergy with correlation values exceeding 0.5 was observed across both types of movement. The composition of each complex motion synergy usually requires the merging of three basic motion synergies.
CONCLUSIONS: The findings suggest that complex upper limb movements are constructed through combinations of fundamental motor modules. This supports the concept of modular control in human motor coordination.
METHODS: Three healthy participants performed both proprioceptive neuromuscular facilitation (PNF) patterns and basic upper limb motions. Electromyography (EMG) and kinematic data were recorded simultaneously. A verified musculoskeletal (MS) model, calibrated with computed muscle control (CMC) results and processed EMG data, was used to estimate muscle activations. Muscle synergies and corresponding activation coefficients were extracted using non-negative matrix factorization (NNMF), and variance accounted for (VAF) metrics were applied to determine the optimal number of synergies. Spearman's rank correlation and least squares optimization were employed to assess the similarity and combination of synergy patterns between motion types.
RESULTS: Four muscle synergies were identified for both basic and complex movements. A shared synergy with correlation values exceeding 0.5 was observed across both types of movement. The composition of each complex motion synergy usually requires the merging of three basic motion synergies.
CONCLUSIONS: The findings suggest that complex upper limb movements are constructed through combinations of fundamental motor modules. This supports the concept of modular control in human motor coordination.