Neuromuscular simulations for predicting functional walking ability

点击翻译按钮获取中文摘要

Restoration of functional walking ability is a high priority for rehabilitation in pathological populations, e.g., older adults, stroke survivors, individuals with spinal cord injury and Parkinson’s disease. This project will address two critical gaps currently limiting rehabilitation efforts to improve functional walking ability. First, the underlying impairments in neuromuscular control (i.e., how the nervous system recruits muscles to move) that cause pathological walking ability are not well-understood. Second, these impairments can vary from individual to individual such that “one-size-fits-all” rehabilitation approaches produce only modest gains in walking ability. To overcome these gaps, this research will use a combination of experimental motion capture and predictive musculoskeletal computer simulation techniques to identify neuromuscular impairments of walking ability. This project will provide fundamental knowledge about neuromuscular control that is important for functional walking ability. The knowledge gained will help guide rehabilitation interventions to improve pathological walking. This project will also provide educational and research opportunities for socioeconomic and educationally disadvantaged K-12 and undergraduate students in the Appalachian region to learn how biomechanics can improve human health, stimulating their interest and participation in STEM.The objective of this project is to determine the causal relationship between neuromuscular generalization and functional walking ability through predictive simulation techniques. If neuromuscular generalization is identified as important for functional walking ability, which is expected based on preliminary results, the predictive simulation framework can be used to identify impairments in neuromuscular generalization and provide a target for gait rehabilitation. To achieve the project’s objective, the Research Plan is organized under two aims. The FIRST Aim is to characterize the observed relationship between fastest achievable walking speed and neuromuscular generalization across standing reactive balance and walking. The working hypothesis that recruiting standing reactive balance motor modules during walking enables an individual to walk at faster speeds will be tested in healthy young adults, older adults with a history of falls, and stroke survivors. Surface EMGs (electromyographs) will be measured from 12 muscles in the dominant leg (both legs in stroke survivors) while tasks are performed on a split – belt instrumented treadmill. Tasks include (a) standing quietly on a stationary treadmill while being exposed to support-surface translation perturbations through discrete movements of the treadmill belts (standing reactive balance), (b) walking at a self-selected speed on the treadmill for 30 seconds and (c) walking on the treadmill at the fastest speed that can be safely maintained for 30 seconds. Motor modules will be separately identified from the assembled EMG data matrices from each task using non-negative matrix factorization. The SECOND Aim is to demonstrate that increased neuromuscular generalization across standing reactive balance and walking leads to higher maximum walking speed. The working hypothesis that recruiting standing reactive balance motor modules during walking enables an individual to walk at faster speeds will be tested using predictive simulations driven by motor modules that maximize walking speed using the data collected under Aim 1. A generic musculoskeletal model with 23 degrees of freedom and 46 muscles per side (OpenSim Gait 2392 model) will be scaled to subject mass and dimensions. Experimentally observed motor modules will be converted to simulated motor modules through solving the inverse-dynamics based muscle redundancy problem. Walking simulations of single gait cycles that are constrained by motor modules will be generated that track observed motion from the self-selected and maximum walking trials using direct collection in OpenSim. Identifying whether recruiting reactive balance motor modules during walking enables walking at faster speeds will provide strong evidence for neuromuscular generalization as a novel rehabilitation target.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.