Developing Real-time Interaction and Motion Tracking in Immersive VR for Telerehabilitation
Trial Snapshot
- Phase
- Not Applicable
- Sponsor
- University of Wyoming
- Enrollment
- 2
- Primary Endpoint
- Tracking Accuracy
Study Overview
Brief Summary
Current technology for telerehabilitation is limited to be audio- or video- based interaction without an objective and accurate measure of motor functions. A technology integrating motion tracking with 3D immersive virtual reality has been developed by an interdisciplinary team to shift the paradigm of telerehabilitation. We aim to take the significant step to develop the patient-centered telerehabilitation that will feature real-time patient-therapist interaction with functions of tele-monitoring, tele-diagnosis, and tele-therapy. Such an interactive telerehabilitation is expected to increase patient adherence to therapy and minimize the existing health disparities.
Detailed Description
By innovatively integrating the 3D motion tracking with 3D immersive virtual reality (VR), the real-time user interaction and simultaneous motion tracking and analysis in the immersive VR environment were made possible. We now propose to customize this technology for telerehabilitation. The ultimate goal is to build a VR-based interactive tele-rehab system that is patient-centered, with augmented feedback and tele-presence of therapist to assist rehabilitative exercises and recovery of motor functions in both real and virtual environment. To achieve this goal, we are specifically tackling three problems.
- 1: Cross validating the precision of motion data captured in VR. We will modify our current software (Unity-based) so that it can work simultaneous with two motion tracking systems (Optical tracking and Magnetic tracking) to capture motion data in a 3D VR environment. The recorded data in our software will be compared and correlated with those data recorded by the two motion tracking systems in 3D for examination of accuracy.
- 2: Building and testing the network code for remote data transmission and interaction. We will write network code to enable the remote transmission of motion tracking data between two sites. The latency of data transmission will be tested to determine the minimum speed of internet for implementing such a tele-rehab system.
- 3: Designing and implementing a VR interaction task for remote monitoring and diagnosis. A 3D interactive VR task will be built for real-time local interaction and the remote monitoring, assessment and intervention.
Study Design
- Study Type
- Interventional
- Allocation
- Na
- Intervention Model
- Single Group
- Primary Purpose
- Device Feasibility
- Masking
- None
Eligibility Criteria
- Ages
- 18 Years to 45 Years (Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •Only the key researchers of this project can participate in the study
Exclusion Criteria
- •Any individual who is not the responsible researcher in this project shall not participate in the study.
Arms & Interventions
User Interaction with Device
A user will wear motion sensors and VR device to interact with object or another user in VR environment
Intervention: Motion Tracking in VR (Device)
User Interaction with Device
A user will wear motion sensors and VR device to interact with object or another user in VR environment
Intervention: VR Interaction (Behavioral)
Outcomes
Primary Outcomes
Tracking Accuracy
Time Frame: through study completion, approximately 1 year
matching the motion trajectories in VR and REAL with a small error indicating a good match
Latency of Data Transmission
Time Frame: through study completion, approximately 1 year
The duration for the tracked motion data to be transmitted to a remote computer
Total number of the basketed apples
Time Frame: through study completion, approximately 1 year
Computer display of the total count of successfully picked and basketed apples from the tree
Secondary Outcomes
- Total excursion of the hand(through study completion, approximately 1 year)
- Mean speed of hand movement(through study completion, approximately 1 year)
Investigators
Qin Zhu
Associate Professor
University of Wyoming