Lunge Flow: An Intelligent System for Improving Fencing Technique using Pose Estimation and AI
The Lunge Flow app addresses the challenge of improving fencing techniques and preventing injuries by providing AI-driven, personalized feedback on user-uploaded videos [1]. Combining pose estimation, K-Means clustering, and ChatGPT, the app analyzes user movements and compares them to reference techniques. Experiments revealed an 80% accuracy rate for feedback matching professional evaluations and a high user satisfaction score of 4.6. The app’s key strengths are its accessibility, real-time feedback, and potential to enhance training outcomes. Future improvements include expanding technique coverage, refining visual design, and improving analysis for low-quality videos. Lunge Flow is a reliable, innovative tool for fencers and athletes aiming to perfect their craft.
Authors
- S Li
- Toan Huynh (ORCID: https://orcid.org/0000-0002-6455-3056)
Publication Details
- Published
- 2025-02-22
- DOI
- https://doi.org/10.5121/csit.2025.150404
- Primary Topic
- Mechanics and Biomechanics Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00