SBIR/STTR Research Award
SBIR Phase I:Brave Virtual Worlds Human Movement Artificial Intelligence (AI) Engine and Biofeedback Loop
Award amount
$273,915Program and phase
SBIR · Phase IAward year
2023Award details
- Awarding agency
- National Science Foundation
- Branch
- Not reported
- Recipient company
- BRAVE VIRTUAL WORLDS, INC.
- Proposal award date
- 2023-09-01
- Contract end date
- 2024-08-31
- UEI
- Z9AEGCRJ2G28
- Solicitation number
- NSF 23-515
- Topic code
- DH
Research abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project aims to develop a biofeedback system that combines wearable sensors, real-time data capture, and immersive virtual reality visualization. This system has the potential to enhance the understanding of joint angles and movement patterns enabling in-depth analysis of human movement. The proposed technology targets a significant market opportunity in the athletic training and physical therapy industry, which is valued at $200 million. _x000D_
_x000D_
This SBIR Phase I project addresses intellectual merit through a systematic research approach. The project involves designing and refining the biofeedback system, conducting extensive data collection, and implementing advanced algorithms for real-time analysis. The project's goals include developing a user-friendly interface, optimizing sensor accuracy, and creating a seamless biofeedback system for improved training and rehabilitation. Anticipated technical results include the design and development of a machine learning layer to classify and identify key components of movements in order to create a contextual database for further analysis to determine movement efficiency and highlight movement patterns as well as the development of a corrective exercise/feedback layer using the context from the machine learning layer to generate further insights into what is causing highlighted movement patternsThis second later will incorporate corrective exercises that are suggested for improvement. Additionally, a real-time layer incorporating the first two layers into the real-time portion will be used for immediate feedback to the end-user, thus providing a closed bio-feedback loop._x000D_
_x000D_
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.
Technology keywords
Not reported