Programa del congreso

Walking is a dynamic motor function characterized by synchronized muscle activations that facilitate joint movement and the gait cycle. Gait follows certain patterns that can vary depending on the disease, as in the case of stroke survivors. During stroke rehabilitation, therapy efficacy is generally assessed with clinical scales, which tend to be subjective and provide only a global overview of the functional abilities. Recently, efforts have increased to assess walking performance objectively and reliably, some using surface electromyography (EMG) signals. Clinical literature indicates that changes in EMG during gait are often analyzed with a limited number of metrics. In this work, we propose a case study in which we characterized and analyzed the electromyographic evolution of a stroke survivor throughout a 2-month lower-limb robotic gait therapy, integrating metrics from diverse studies to provide a broader characterization. The metrics are representative of the level of muscle activation, the activation changes, the variability of the signal, the median frequency, and the mean power. The EMG assessment was conducted during overground walking before, during, and after two months of robotic therapy, and with a follow-up after 2 months of only conventional therapy.

After data analysis, these metrics showed a great potential to capture important changes throughout the robotic rehabilitation process, including increased activation levels, energy, and variability in the tibialis anterior and soleus, indicating improved ankle stability and dorsiflexion. Additionally, these changes suggested a reduction in the hyperactivity of the vastus lateralis and rectus femoris, common in post-stroke gait.