Background
Recent evidence suggests that disinhibition and/or hyperexcitation of the brainstem descending pathways and intraspinal motor network diffuse spastic synergistic activation patterns after stroke. This results in simplified or merged muscle sets (i.e., muscle modules or synergies) compared to non-impaired individuals and this leads to poor walking performance. However, the causal relations of how these neuromuscular deficits influence gait quality (e.g., symmetry or natural walking patterns) are still unclear. The objective of this exploratory study was to investigate the relations of modular neuromuscular framework and gait quality measures in chronic stroke individuals.
Methods
Sixteen chronic post-stroke individuals participated in this study. Full lower body three-dimensional kinematics and electromyography (EMG) were concurrently measured during overground walking at a comfortable speed. We classified subjects into two groups based on the number of muscle modules and compared gait quality measures using a two-sampled t-test. Then, a stepwise multiple regression was used to investigate the optimal combination of the neuromuscular parameters to predict gait quality measures.
Results
Subjects who had a reduced number of muscle modules had greater asymmetry in the kinematic parameters including limb length (p < 0.01), footpath area (p < 0.01), hip (p < 0.05) and knee (p < 0.01) flexion/extensions, and hip abduction/adduction (p < 0.01). We also found that the gait quality measures were predictable with the input variables from the modular neuromuscular control framework including variability accounted for (\(VAF\)) information from the muscle modules and area under the EMG envelope curves of the quadriceps (i.e., rectus femoris and vastus lateralis) and tibialis anterior muscles with significant association (average R2 = 45.6%).
Conclusions
The results suggest that there exists a strong correlation between the neuromuscular control framework and the gait quality measures. This study helps to understand the underlying causality of disturbances in gait quality and provides insight for a more comprehensive outcome measure to assess gait impairment after stroke.