Association between temporal asymmetry and muscle synergy during walking with rhythmic auditory cueing in stroke survivors living with impairments

Modeling the Heterogeneity of Post-Stroke Gait Control in Free-Living Environments Using a Personalized Causal Network

Post-stroke gait control is a complex, often fail to account for the heterogeneity and continuity of gait in existing gait models. Precisely evaluating gait speed adjustability and gait instability in free-living environments is important to understand how individuals with post-stroke gait dysfunction approach diverse environments and contexts. This study aimed to explore individual causal interactions in the free-living gait control of persons with stroke. To this end, fifty persons with stroke wore an accelerometer on the fifth lumbar vertebra (L5) for 24 h in a free-living environment. Individually directed acyclic graphs (DAGs) were generated based on the spatiotemporal gait parameters at contemporaneous and temporal points calculated from the acceleration data. Spectral clustering and Bayesian model comparison were used to characterize the DAGs. Finally, the DAG patterns were interpreted via Bayesian logistic analysis. Spectral clustering identified three optimal clusters from the DAGs. Cluster 1 included persons with moderate stroke who showed high gait asymmetry and gait instability and primarily adjusted gait speed based on cadence. Cluster 2 included individuals with mild stroke who primarily adjusted their gait speed based on step length. Cluster 3 comprised individuals with mild stroke who primarily adjusted their gait speed based on both step length and cadence. These three clusters could be accurately classified based on four variables: Ashman's D for step velocity, Fugl-Meyer Assessment, step time asymmetry, and step length. The diverse DAG patterns of gait control identified suggest the heterogeneity of gait patterns and the functional diversity of persons with stroke. Understanding the theoretical interactions between gait functions will provide a foundation for highly tailored rehabilitation.

Characteristics of limb kinematics in the gait disorders of post-stroke patients

Post-stroke gait disorders involve altered lower limb kinematics. Recently, the endpoint of the lower limb has been used as a control variable to understand gait kinematics better. In a cross-sectional study of sixty-seven post-stroke patients, the limb extension angle and effective limb length during gait were used as input variables with a mixed Gaussian model-based probabilistic clustering approach to identify five distinct clusters. Each cluster had unique characteristics related to motor paralysis, spasticity, balance ability, and gait strategy. Cluster 1 exhibited high limb extension angle and length values, indicating increased spasticity. Cluster 2 had moderate extension angles and high limb lengths, indicating increased spasticity and reduced balance ability. Cluster 3 had low limb extension angles and high limb length, indicating reduced balance ability, more severe motor paralysis, and increased spasticity. Cluster 4 demonstrated high extension angles and short limb lengths, with a gait strategy that prioritized stride length in the component of gait speed. Cluster 5 had moderate extension angles and short limb lengths, with a gait strategy that prioritized cadence in the component of gait speed. These findings provide valuable insights into post-stroke gait impairment and can guide the development of personalized and effective rehabilitation strategies.

Analysis of muscle synergy and gait kinematics during regain of gait function through rehabilitation in a monoplegic patient

Purpose

We conducted muscle synergy and gait analyses in a monoplegic patient whose gait function improved through training, to explore the possibility of using these parameters as indicators of training.

Case presentation

A 49-year-old male had monoplegia of the right lower limb caused by infarction of the left paracentral lobule. After 2 months of training, he was able to walk and returned to work.

Methods

Consecutive analyses were done after admission. Muscle synergy analysis: during walking, surface electromyograms of gluteus maximus, quadriceps femoris, adductor femoris, hamstrings, tibialis anterior, medial/lateral gastrocnemius, and soleus on both sides were recorded and processed for non-negative matrix factorization (NNMF) analysis. Gait analysis: markers were placed at foot, and walking movements were video recorded as changes in position of the markers.

Results

Compared with three muscle synergies detected on the non-paretic side, two muscle synergies were extracted on the paretic side at admission, and the number increased to three and then four with progress in rehabilitation training. Changes in weighting and activity of the muscle synergies were greater on the non-paretic side than on the paretic side. With training, the knee joint flexor and the ankle dorsiflexor activities on the paretic side and the gluteus maximus activity on the non-paretic side increased during swing phase as shown by weight changes of muscle synergies, and gait analysis showed increased knee joint flexion and ankle joint dorsiflexion during swing phase in the paretic limb. On the non-paretic side, however, variability of muscle activity was observed, and three or four muscle synergies were extracted depending on the number of strides analyzed.

Conclusion

The number of muscle synergies is considered to contribute to motor control. Rehabilitation training improves gait by increasing the number of muscle synergies on the paretic side and changing the weights of the muscles constituting the muscle synergies. From the changes on the non-paretic side, we propose the existence of compensatory mechanisms also on the non-paretic side. In muscle synergy analysis, in addition to the filters, the number of strides used in each analysis set has to be examined. This report highlights the issues of NNMF as analytical methods in gait training for stroke patients.