Assessing muscle activation and morphology during gait

According to the Centers for Disease Control and Prevention, CP is the most common physical disability in childhood, significantly influencing muscle control. Physical rehabilitation and strength training interventions play a crucial role in the treatment approach of CP specifically targeting motor deficits. However, not all the training approaches are effective in transferring the improvements related to muscle strength to the activities of daily living (i.e. walking). One strategy that has shown promising results is the functional power training, that includes different exercises involving high velocity movements. To gain insight into this training approach, both architectural and electrophysiological muscle characteristics need to be evaluated during the exercises. This thesis has been carried out in collaboration with a clinical partner, Rehabilitation medicine VUmc (Amsterdam), currently investigating the underlying mechanisms of the functional power training in CP children. The main objective of this thesis was to provide the clinical partner with the technical and methodological support to simultaneously assess muscle activation (with surface electromyography, sEMG) and fascicle displacement (with ultrasound imaging, US) from the same muscle region. In the first part of the project, previously developed bipolar US-transparent EMG electrodes, were improved and tested for the first time in dynamic conditions (i.e. gait). The presence of movement artifacts in EMG signals and the overall quality of US images during dynamic tasks were considered to assess the feasibility of joint EMG-US measures. The second part of the thesis focused on the analysis of US images for the investigation of muscle morphology. The two main variables of interest for pennate muscles are the fascicle length and the pennation angle. Several algorithms have been proposed to automatically quantify and track these parameters throughout the contraction. However, due to the complexity of the task considered, a unique working solution has not been found yet. Hence, an existing fascicle tracking algorithm was improved and adapted for muscle tracking during dynamic tasks. Moreover, considering that both temporal and spatial factors impact the tracking performance, the algorithm was tested on high frame rate US videos acquired during dynamic tasks (heel rise and walk), assessing the effect of different frame rates and beamforming techniques (DAS and FDMAS). The quality of the tracking was evaluated through the root mean square error (RMSE) between the results of the automatic and the manual tracking on two subjects at the lowest frame rate (25 fps). The comparison between the two beamforming strategies showed that, for the walk task the values of the RMSE obtained using FDMAS (FL = (6.52 ± 2.07)mm, PA = (1.85 ± 0.46)°) were significantly lower than using DAS (FL = (8.58 ± 2.58)mm, PA = (2.41 ± 0.61)°). Also for the heel rise task similar results were found using FDMAS (FL = (7.35 ± 2.90)mm, PA = (2.98 ± 1.41)° and DAS (FL = (9.35 ± 3.48)mm, PA = (3.54 ± 1.50)°). These findings suggest that the superior resolution and contrast obtained by means of the FDMAS beamforming method improved the result of the automatic tracking. As for the effect of the frame rate, no significant changes of the performance were found. In conclusion, experimental results demonstrated the feasibility of the combined acquisition of sEMG signal and US images from the same muscle region of the medial gastrocnemius during dynamic tasks.