NeuroMuscular Biomechanics Laboratory: Research
Accordions
The definitive treatment to relieve the pain, disability, and loss of motion associated with late-stage osteoarthritis is total knee arthroplasty (TKA) (also known as a total knee replacement). While long-term implant survival of TKA is approximately 90-95% for elderly patients after 10 to 15 years, the clinical outcomes are worse for younger, active patients. For most patients, TKA successfully relieves the pain associated with osteoarthritis of the knee, but improvements are needed to allow patients to perform more physically demanding activities such as stair negotiation, squatting, kneeling, gardening, and recreational sports. There exists a wide range of clinical outcomes that makes it difficult for the surgeon to give an individual patient an accurate estimation of post-operative outcome.
We are developing a transformational and computer-assisted approach to total knee arthroplasty. Through our comprehensive and rigorous approach, we seek to answer the question of whether it is possible to predict post-operative functional outcomes based on objective intra-operative measurements of surgical technique, specifically component alignment and initial soft tissue balance. This approach is innovative because it represents the first effort to parameterize key aspects of surgical technique and objectively relate intra-operative measurements to post-operative outcomes. Such an integrated approach will allow us to determine to what degree actions taken by the surgeon during surgery affect the post-operative functional course for a given patient. With that knowledge, surgeons will be able to make patient-specific intra-operative decisions and better predict post-operative function. Physical therapists can customize a patient’s rehabilitation program. Implant manufacturers can customize the design of an implant to match a certain type of patient and can ensure high post-operative function despite a given amount of variability in surgical technique.
The Value of Modeling and Simulations
Determining the causal relationship between muscle function and an observed motion is a key step in fully understanding normal movement as well as for establishing a scientific basis for prescribing treatment strategies for pathological movement patterns. However, experimental techniques alone, such as gait analysis and EMG, are not able to fully understand the complex neuromuscular dynamics associated with human motion.
Computer simulations of human movement have proven to be powerful tools to establish such cause-effect relationships. Simulations are well suited for estimating key data, such as muscle forces, that are difficult to obtain from experimental approaches alone. These simulations can be used to help understand muscle activations, joint kinematics, and internal joint loading and thereby can shed light onto mechanisms of pathological or altered kinematics. Dynamic simulations are well-suited for performing “what if?” studies in which, for example, the activation or force production of one muscle or muscle group can be changed to observe the resulting motion and muscle forces. Forward-dynamic simulations are especially useful for studying functional tasks because they involve the application of forces to produce motions, offering potential insights into the roles played by individual muscles during a task. These simulations also permit monitoring of other variables of interest such as joint contact forces which may affect functional performance and offer insight as to the biomechanical reasons for suboptimal outcomes.
Our Approach
We create dynamic simulations of human movement with the software package known as OpenSim. Our simulation studies span the movements of gait, the sit-to-stand task, and stair climbing and include healthy young and old populations as well as patients with varying knee OA severity.
We currently have the following active projects:
• Differentiating muscle contributions to support and progression during gait in older and young adults
• Analysis of stair ascent and descent in a young, healthy population
• Investigation of the sit-to-stand task in a knee OA population
