Gait & posture · 2026
Speeds alter lower-limb muscle synergy patterns in adult males with functional ankle instability during treadmill running.
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Zhao Kanglong, Zhu Changqing, Zhong Jintao, Qian Chengle, Sun Mengzi, Xu Yilin, Li Li, Mao Wenhui
Аннотация
OBJECTIVE: This study aimed to investigate the effects of running speed on lower-limb muscle synergies in adult males with functional ankle instability (FAI).
METHODS: Fifteen Males with FAI and fifteen matched healthy male controls ran on a treadmill at speeds 20% faster and 20% slower than their preferred running speed. Surface electromyographic signals were recorded from eight lower-limb muscles. Muscle synergy patterns were extracted using non-negative matrix factorization and classified via K-means clustering. Two-way ANOVA was applied to muscle weightings and peak activation coefficients (α = 0.05).
RESULTS: Six synergy patterns were identified across the two conditions in both groups. Significant between-group differences in muscle weightings were observed: the FAI group showed lower soleus weighting in Synergy 1 (p = .026), lower gluteus maximus in Synergy 3 (p = .007), and lower rectus femoris in Synergy 4 (p = .018). For coefficient peaks, the FAI group demonstrated higher values in Synergy 2 (p = .023). A significant group-by-speed interaction in Synergy 3 (p = .006) revealed that the control group had decreased values from slow to fast speeds (p < .001), while the FAI group showed no change (p = .305). Synergy 6 showed a significant speed main effect (fast > slow, p = .045).
CONCLUSION: Male individuals with FAI exhibited muscle synergies that were less adaptable to speed changes during treadmill running, reflecting a rigid neuromuscular control pattern. Increased weighting of proximal muscles in the FAI group suggests a proximal compensatory strategy.
METHODS: Fifteen Males with FAI and fifteen matched healthy male controls ran on a treadmill at speeds 20% faster and 20% slower than their preferred running speed. Surface electromyographic signals were recorded from eight lower-limb muscles. Muscle synergy patterns were extracted using non-negative matrix factorization and classified via K-means clustering. Two-way ANOVA was applied to muscle weightings and peak activation coefficients (α = 0.05).
RESULTS: Six synergy patterns were identified across the two conditions in both groups. Significant between-group differences in muscle weightings were observed: the FAI group showed lower soleus weighting in Synergy 1 (p = .026), lower gluteus maximus in Synergy 3 (p = .007), and lower rectus femoris in Synergy 4 (p = .018). For coefficient peaks, the FAI group demonstrated higher values in Synergy 2 (p = .023). A significant group-by-speed interaction in Synergy 3 (p = .006) revealed that the control group had decreased values from slow to fast speeds (p < .001), while the FAI group showed no change (p = .305). Synergy 6 showed a significant speed main effect (fast > slow, p = .045).
CONCLUSION: Male individuals with FAI exhibited muscle synergies that were less adaptable to speed changes during treadmill running, reflecting a rigid neuromuscular control pattern. Increased weighting of proximal muscles in the FAI group suggests a proximal compensatory strategy.