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Design of Technology for Mobility Assessment and Rehabilitation

Older adults and 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 include weakness, sensorimotor processing delays, and changes in musculoskeletal properties that, together, may result in a compromised ability to turn, difficulty negotiating both predictable and unpredictable environments, and a need to use assistive devices for mobility. As a result, these individuals are often at a high risk of falls, with tripping over obstacles being commonly identified as a major cause of falls. Thus, it is critical to develop assessments capable of identifying the source of mobility impairments and also design interventions to train skills such as turning and obstacle avoidance to maximize functional mobility.

Ongoing Projects

Dynamic Balance Control While Walking with Handheld Assistive Devices
At least 4 million Americans use wheeled and unwheeled walkers to improve balance while walking. These devices can assist balance by expanding the area in contact with the ground to make a larger base of support, reducing the load on the legs, and providing tactile input to the hands to help prevent instability and recover from balance disturbances. Counterintuitively, some studies have reported that walker use is associated with falls, but the reasons why walkers are associated with falls in not well understood. Tripping hazards in the environment may provoke falls through small disturbances transmitted to the body through the upper limbs. Our objective is to characterize the relative roles of mechanical stabilization and tactile input from the upper body on balance control while walking with hand-operated assistive devices. To pursue our objective, we created a robotic rollator that applies perturbations capable of challenging balance by abruptly decelerating during use.

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 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. 

Publications

  1. Zamani N, Abass A, Shetkar M, Dureja S, Li M, Culbertson H, Finley JM. Integrating haptic feedback into a virtual reality mobility training game for people with Parkinson’s diseaseProceedings of the 2021 IEEE World Haptics Conference (WHC). 875-875.
  2. Adlakha G, Singh S, Patil A, Nuthalapati K, Khandve P, Bhattacharyya P, Manoharan S, Santhanam SM, Lachica IF, Finley JM, Lympouridis V. Development of a Virtual Reality Assessment of Visuospatial Function and Oculomotor Control. Proceedings of the IEEE Conference on Virtual Reality and 3D User Interfaces. 753-754. 
  3. Finley JM, Gotsis M, Lympouridis V, Jain S, Kim A, Fisher BE. (2021). Design and Development of a Virtual Reality-Based Mobility Training Game for People With Parkinson’s DiseaseFront Neurol. 11:577713
  4. A. Kim, N. Schweighofer, J.M. Finley. (2019). Locomotor skill acquisition in virtual reality shows sustained transfer to the real world. Journal of Neuroengineering and Rehabilitation. 14;16(1):113.
  5. A. Kim, K. S. Kretch, Z. Zhou, and J.M. Finley. (2018). The quality of visual information about the lower extremities influences visuomotor coordination during virtual obstacle negotiation. Journal of neurophysiology. ​2018 120:2, 839-847 ​
  6. A. Kim, N. Darakjian, and J.M. Finley (2017). Walking in Fully Immersive Virtual Environments: A Feasibility Test for Older Adults and Individuals with Parkinson’s diseaseJournal of Neuroengineering and Rehabilitation. 14, 16.
  7. A. Kim, Z. Zhou, K. Kretch, J.M. Finley. (2017). Manipulating the fidelity of lower extremity visual feedback to identify obstacle negotiation strategies in immersive virtual realityConf Proc IEEE Eng Med Biol Soc 1: 4491-4494.
  8. J.M. Finley, M.S. Statton, A.J. Bastian.(2014) A Novel Optic Flow Pattern Speeds Split-belt Locomotor Adaptation. Journal of Neurophysiology. 111, 969-976. 

Funding

USC Clinical and Translational Sciences Institute The Neuroscience and Engineering of Ocean Wave Surfing as Therapy for Chronic Pain
PIs: Jason Kutch, Ph.D., Heather Culbertson, Ph.D., and James M. Finley, Ph.D
​Dates: 2023-2024

USC Division of Biokinesiology and Physical Therapy Seed Grant
PIs: James M. Finley, Ph.D; Sook-Lei Liew, Ph.D., OTR/L; Nicolas Schweighofer, Ph.D;
Beth Fisher, Ph.D., PT, FAPTA; Judy Pa, Ph.D. 
​Dates: 2017-2018

Design and Development of a Mixed Reality System for Skilled Locomotor Training in Individuals with Parkinson’s disease NIH R21HD088342
PI: James M. Finley, Ph.D
Dates: 2016-2018

USC Undergraduate Research Associates Grant
PI: James M. Finley, Ph.D
​Dates: 2015-2016