This Small Business Innovation Research (SBIR) Phase I project targeted the research and development of an immersive virtual reality telehealth platform for remote physical therapy and patient monitoring, an embodied telehealth service that connects therapists and patients, transporting the users into a 3D virtual avatar that replicates body movements from the physical world with real-time biomechanical analytics. Through this award, we have developed our customer discovery and interviews with physical therapists, built customer relationships in both independent therapy providers and large hospitals, examined channel distributions, and advanced our interactions with different market segments between outpatient physical therapy, preventative care, rehabilitation policy organizations, therapist education programs, and telehealth companies. By the end of Phase I, we amassed 200+ customer discovery interviews, 140+ survey respondents, and 50+ prototype demos of the platform with physical therapists which well positioned our prototype development. The data from Phase I interviews pointed to two major unmet market needs for outpatient physical therapy: effective full-body remote movement evaluation and a gold standard for biomechanical assessment, and in Phase II, we propose to extend our system to meet that demand.

Through the commercial development of this Phase I SBIR, we refined our value proposition and increased our validation towards a platform-as-a-service business model towards capturing our revenue stream. We built and iterated our prototype virtual reality telehealth platform with a co-design panel of over 6 physical therapists from diverse backgrounds and tested the prototype by demoing to the American Physical Therapy Association, partnering with 3 physical therapy clinics, and obtained letters of intent from the Houston Veterans Medical Affairs and Stanford Healthcare. Our prototype is well implemented into TRL4, with continued development into a proposed Phase II. Early angel investors have supported our prototyping and interactions with investors have been initiated with over $200,000 raised in under 2 months through SAFEs and Regulation Crowdfunding. A Phase II award will allow us to finalize our feature set to meet the needs of our physical therapists and move beyond a Beta Platform towards raising a Series-a, followed by carefully planned product lines in synchronous care, asynchronous continued care, and predictive health monitoring for preventative care.

In terms of technical milestones, the frontend VR environment, backend HIPAA compliant data storage, joint data estimation including analytic metrics, and patient-therapist feedback loop are now ready for large scale user testing. The biomechanical analysis has been validated through accurate measures from 3D motion tracking systems. With the conclusion of Phase 1, we are now ready to begin user testing with the therapists who asked to test our product when it was ready for preliminary trials via our partner healthcare organizations. Our Phase 2 plans build directly off of this feedback between the physician and the patient while also opening up new measures for lower-extremity movement and ensuring high-usability for patient usage experiences. Our system will be sustained to support both synchronous and asynchronous evaluation, allowing physicians and users to meet in real time, or both may look back at the session to gather feedback about movements. Validation will include comparatively analyzing physical in-person, 2D web camera, and 3D VR environment assessments. Interrater-reliability of PTs is important and can be assessed through each platform. These beta tests will help us distinguish the benefits of a 3D VR environment while keeping relations with potential customers. We will build off the foundation to provide physicians means to create their own movement tasks, with the potential to share with others. All data will be available, providing a consistent platform for multiple physicians to collaborate on both tasks for patients and subjective analysis/diagnosis on the objective data.

Last Modified: 10/30/2022
Modified by: Aviv Elor