Locomotor Skill Learning in Virtual Environments

Finley

Dr. James Finley

In the USC Locomotor Control Lab, we seek to understand how walking is controlled and adapted in both the healthy and injured neuromuscular system. We develop models and experiments based on principles of neuroscience, biomechanics, engineering, and exercise physiology to identify the factors that guide locomotor learning and rehabilitation. Ultimately, the goal of our work is to design novel and effective interventions to improve walking ability in individuals with damage to the nervous system.

Individuals with neurological impairments such as stroke or Parkinson’s disease (PD) commonly have gait impairments that reduce their ability to walk safely in the community. These impairments are characterized by a compromised ability to turn and difficulty negotiating both predictable and unpredictable environments. As a result, these individuals are much more likely to fall than healthy age-matched controls, with tripping over obstacles being commonly identified as a major cause of falls. Thus, it is critical to train skills such as turning and obstacle avoidance to maximize functional gait ability. The use of virtual environments allows us to tailor each patient’s training context to match the obstacles and barriers they face on a daily basis in a safe, well-controlled setting.

Ongoing Projects

Design and Development of a Fully Immersive Virtual-Reality System for Improving Skilled Walking Ability
Despite our understanding that training skills such as turning and obstacle avoidance are necessary to maximize functional mobility, gait interventions often focus on walking along an unobstructed path in a straight line. Existing interventions may also fail to integrate principles of skill training, which are known to facilitate long-term improvements in motor skill (e.g., progressive increase in difficulty , focus on skillful movement, promoting independence). To address this limitation, we are developing and testing the usability of a multi-platform training system that allows individuals with Parkinson's disease to practice advanced walking skills such as turning and obstacle avoidance in real-world scenarios. We are relying on a user-centered approach to address the limitations of previous approaches to virtual-reality-based training in order to achieve a training experience that is meaningful to the end-user (patients and therapists). A key innovation of our approach is that our system can be used either with standard treadmills, over-ground in an open space, or in conjunction with newer, omni-directional treadmills.

Principles of Locomotor Skill Learning in Real and Virtual Environments
Recent advances in consumer-grade technology for virtual reality have lowered the barriers to widespread use of VR for clinical applications such as a neuromotor rehabilitation. However, in order to optimize the design and implementation of VR-based interventions, it is important to understand the fundamental processes underlying motor skill learning in virtual environments and the factors that influence whether skills learned in virtual environments will generalize in the real world. In addition to understanding how conditions of practice influence skill acquisition, retention, and transfer, we also seek to understand what neural networks are involved with locomotor skill learning in healthy individuals and how damage to these networks in pathological populations influences the learning process.