CAREER: Personalizing sensory-driven computerized interfaces to optimize motor rehabilitation

Project: Research project

Project Details

Description

Persons with an injury to the brain or spinal cord often undergo physical training to recover movement abilities needed for daily activities. To motivate participation in this “motor therapy,” virtual reality (VR) technologies are increasingly used. VR can be programmed to be highly realistic or look like a game to encourage participants. Still, persons who use VR motor therapy do not always achieve better outcomes than traditional methods, partially because they are not personalized to each user. Improving VR therapy requires a greater understanding of how persons respond to programmable features. Two features that can improve VR motor therapy are the difficulty of the training task and the guidance (feedback) provided during training. VR interfaces that stimulate senses for greater immersion can readily provide training guidance using augmented sensory feedback (ASF). The method of ASF involves providing sensory (e.g., visual, haptic) cues about the direction and magnitude in which a person should move during training. This project will examine how impairment in function affects personal performance, physiologic responses, and perceptions during VR training that adapts the task difficulty and ASF. This project will advance education through supervised training of high-school students to custom-develop VR rehabilitation applications. These students will further engage the community by presenting their work at laboratory demonstrations to K-12 students from under-resourced districts. In addition, they will receive constructive feedback about their applications from caregivers, clinicians, and, most importantly, persons with a spinal cord injury (SCI) serving as end-user mentors. The project will test the hypothesis that motor performance improves when adapting VR training features (i.e., task complexity, ASF for guidance) based on measures indicating well-being and physical readiness for training. This project’s technical objectives are: (1) creating regression-type models relating performance to perceptional and physiologic measures during VR motor training and as a function of varying disability, and (2) leveraging these models in an adaptive control system using positive reinforcement to personalize VR training features. Experiments will include persons with SCI performing VR motor rehabilitation tasks with a robot-arm avatar. This project focuses on the SCI population, under-served by VR motor rehabilitation yet ideal for fundamental scientific study since SCI can present as a physical disability with or without cognitive impairment. Participants will generate muscle-activation signals, measured at the skin surface, serving as inputs to a machine-learning algorithm that detects command intention in controlling the avatar. Data from the VR environment, body-mounted sensors, and surveys will be used to assess changes in performance, physiologic responses, and perceptions during training. As such, this project promotes human-centered training that considers both body and mind in providing clinicians with new and diverse dimensions of patient-specific data to personalize healthcare for better function. This project has the potential to generate critical insights into how user-device interfaces are best adapted for function, including how to deliver sensory-driven training for more intuitive control of devices (e.g., smartphones, vehicles, remote-controlled robots).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.
StatusActive
Effective start/end date1/02/2331/01/28

Funding

  • National Science Foundation

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