Effect of Parkinson’s disease and two therapeutic interventions on muscle activity during walking: a systematic review

Abstract

Gait deficits are a common feature of Parkinson’s disease (PD) and predictors of future motor and cognitive impairment. Understanding how muscle activity contributes to gait impairment and effects of therapeutic interventions on motor behaviour is crucial for identifying potential biomarkers and developing rehabilitation strategies. This article reviews sixteen studies that investigate the electromyographic (EMG) activity of lower limb muscles in people with PD during walking and reports on their quality. The weight of evidence establishing differences in motor activity between people with PD and healthy older adults (HOAs) is considered. Additionally, the effect of dopaminergic medication and deep brain stimulation (DBS) on modifying motor activity is assessed. Results indicated greater proximal and decreased distal activity of lower limb muscles during walking in individuals with PD compared to HOA. Dopaminergic medication was associated with increased distal lower limb muscle activity whereas subthalamic nucleus DBS increased activity of both proximal and distal lower limb muscles. Tibialis anterior was impacted most by the interventions. Quality of the studies was not strong, with a median score of 61%. Most studies investigated only distal muscles, involved small sample sizes, extracted limited EMG features and lacked rigorous signal processing. Few studies related changes in motor activity with functional gait measures. Understanding mechanisms underpinning gait impairment in PD is essential for development of personalised rehabilitative interventions. Recommendations for future studies include greater participant numbers, recording more functionally diverse muscles, applying multi-muscle analyses, and relating EMG to functional gait measures.

Biomechanical responses of Nordic walking in people with Parkinson's disease

“…We speculate that this is due to the low activity of the medial gastrocnemius in individuals with Parkinson's disease, as it is important for the forward propulsion in the terminal phase of support. 26 Moreover, the internal work in the Parkinson group was lower than that in the healthy control group, resulting in a reduced total mechanical work at both walking conditions. This finding does not support what we previously hypothesized, indicating that, at same walking speeds, the higher energy expenditure in the gait of people with Parkinson's disease compared to healthy controls 27 (Figure 2) is due to other sources than mechanical work generation, possibly co-contraction and muscle activation to generate stability.…”

Force Platform-Based Intervention Program for Individuals Suffering with Neurodegenerative Diseases like Parkinson

“…Gait deficits are the most visible and prevalent symptom of Parkinson's disease, and they are recognised to be predictive of future motor, psychosocial, and cognitive impairment. However, identifying important biomarkers and, as a result, materialising rehabilitation strategies and tactics necessitate a detailed understanding of muscular activity which causes gait impairment as well as the therapeutic interventions impact on motor behaviour [ 11 – 13 ]. As the illness develops, numerous gait abnormalities emerge, displaying distinct patterns of gait disruptions [ 14 ], reduced speed, shorter step length [ 15 ], and shuffling steps, requiring stronger double limb support, more pace, discreetness in turns (i.e., turning blocks), and difficulties along with freezed gait [ 16 ], inferior balance, and postural controls.…”

Wavelet-Based Assessment of the Muscle-Activation Frequency Range by EMG Analysis

“…Most of the literature in the field is mainly focused on the analysis of the muscular activity in time domain to extract the timing of activation onset and offset. This approach is extensively adopted in clinics to quantitatively characterize different neuromotor disorders [7,8], patient follow-up, and improve rehabilitation strategies [9]. Furthermore, myoelectric non-pattern-recognition-based prosthetic control is acknowledged to include an activation-timing algorithm as one of the fundamental steps of the control procedure [10].…”