Muscle Activation Timing and Synergies During End-Effector Robot-Assisted Gait: A Surface EMG Study

Surface electromyographic (SEMG) patterns during robot-assisted walking are still poorly documented. This study aimed to characterize the timing and synergies of muscle activations of the lower extremities during locomotion assisted with an end-effector robot. Healthy subjects walked at 1.8 km/h under two modes: passive and active with a full body weight load. The robotic gait cycle (RGC) was identified by detecting the flexion-extension phases of the right lower limb. SEMG signals were recorded from eight lower limb muscles, time-normalized with respect to the RGCs and averaged across 10 RGCs. Non-negative Matrix Factorization (NMF) identified three basic waveforms (factors) explaining 90.6% of the variance in the dataset of SEMG waveforms corresponding to three distinct muscle synergies: rectus femoris–vastus lateralis–vastus medialis (extension phase), gastrocnemius medialis–soleus–peroneus longus (mid-flexion phase), and tibialis anterior–biceps femoris longus (transition between extension and early flexion phases). Cluster analysis on the cosine distance matrix of the NMF factor coefficients further validated the three distinct muscle groupings. Temporal activation patterns were seemingly preserved between passive and active conditions, suggesting similar underlying neuromuscular organization. This study supports the use of clinical gait analysis, particularly with SEMG, to assess neuromuscular patterns of neurological patients before, during, and after robotic rehabilitation.