Older adults and individuals with knee osteoarthritis (KOA) often exhibit reduced locomotor function and altered muscle activity. Moreover, individuals who undergo total knee arthroplasty (TKA), the end-stage treatment for knee osteoarthritis, often experience suboptimal functional outcomes. Identifying age-, KOA, and TKA-related changes to the neuromuscular control strategies of walking may provide insight into the neurological mechanisms underlying reduced walking performance in these populations. Current motor control theory suggests the underlying mechanisms controlling muscle activity during gait can be decomposed into a few “primitive signals” that represent basic central features of the motor programs. Muscles are grouped into modules (sometimes referred to as synergies) based on the similarity of their activation patterns to the temporal pattern of the primitive signals. A greater number of modules required to represent the original muscle activation patterns suggests a more complex neuromuscular control strategy. Weighting factors are assigned to the modules to quantify the strength of each muscle’s representation within a given module and determine which muscles are associated with each module. This research analyzed the modular control of walking in younger and older adults without KOA as well as individuals with end-stage KOA who went on to receive a TKA and whose function was analyzed 6-months and 24-months after surgery. Electromyography data from lower limb muscles were collected from each participant during at least 5 over-ground walking trials while 3D kinematic and kinetic data were simultaneously collected. The individuals with KOA also completed assessments of performance-based and self-reported function before and 6-months and 24-months after TKA. Non-negative matrix factorization of 500 bootstrapped samples determined the number of modules required to reconstruct each participant’s electromyography. The number of required modules (control complexity) and the muscles associated with each module were compared between groups (younger, older, KOA) and time points (pre-, 6-months, and 24-months post-TKA). In addition, associations between modular control complexity and walking speed, joint mechanics, and functional measures (in individuals with KOA/TKA) were assessed. While unimpaired older adults did not exhibit differences in the modular control of walking compared to younger adults, individuals with KOA demonstrate changes in the complexity and organization of modular control that persist following TKA. These findings suggest that changes in neuromuscular control strategy occur as part of the disease progression of KOA and that TKA alone does not correct this altered motor control, which may contribute to suboptimal functional outcomes in individuals with TKA.
Dr. Roelker graduated from Ohio State University with her Bachelor's in Biomedical Engineering and her Master's and PhD in Mechanical Engineering where her research focused on using musculoskeletal models and simulations to identify differences in the muscle function and motor control of walking in healthy young and older adults. She completed her post-doc at The University of Texas at Austin where her research focused on understanding muscle contributions to foot placement and balance in healthy populations and individuals with post-stroke hemiparesis. Dr. Roelker joined the Department of Kinesiology at UMass Amherst in the fall of 2020 and directs the UMass NeuroMuscular Biomechanics Laboratory. Her research leverages musculoskeletal modeling and simulation techniques to gain insights into the neuro-musculo-skeletal mechanisms underlying typical and impaired locomotion to identify rehabilitation targets to improve locomotor function and quality of life in individuals with impaired mobility. A primary aim of her research is to identify the biomechanical and neuromuscular mechanisms contributing to impaired dynamic balance in populations with increased fall-risk using a combination of experimental and simulation techniques.