FEATHERS 2.0: Functional Engagement in Assistive Therapy Through Exercise Robotics v2.0

(Main Phase Only - Data Collected with Clinical Population)

The FEATHERS project at the RREACH Lab at The University of British Columbia focuses on developing and evaluating novel physical exercise technologies for kids with motor disabilities. The study team would like to study how immersive virtual reality (VR) technology can be used to benefit upper limb rehabilitation for persons with hemiplegia. The purpose of the experiment is to see how the use of error augmentation (i.e. adding visual or game element feedback to accentuate deviation from the desired exercise motion) might encourage persons with hemiplegia to engage their affected side more effectively by comparing the symmetry between the stronger and weaker limbs. It is also hypothesized that the immersive environment of VR and the ability to provide 1:1 direct visual feedback will increase active engagement to rehabilitative exercises in these populations. The study will address the question of whether error augmentation aids in the rehabilitation of the affected upper limb movement quality in hemiparesis when practicing bilateral reaching tasks. Specifically, can visual amplification of paretic asymmetry in an immersive VR environment improve movement quality in the affected side?

Adolescents and young adults with hemiplegia (i.e. due to ABI, CP, etc.) and their adjoining therapists will be recruited for from the community. We will conduct testing in a single-session setup at the participant chosen location with an easily transportable system including a standard 2-3 sensor Oculus system hardware setup and software developed by the research team. Sessions conducted outside the research lab rooms will require a minimum of a 2m x 1.5m space for calibration. The participants will test all augmentation factors in a randomized order and the sessions are expected to take between 90-120 minutes. A short post-session usability survey will be administered and sample population demographic data will be recorded including age, gender, and handedness. Manual Ability Classification System (MACS) and Bimanual Fine Motor Function (BFMF) scores will be recorded or assessed to classify the upper limb motor ability of the sample set.