IPHS 300: AI for Humanity
Document Type
Poster
Publication Date
Spring 2025
Abstract
This project explores the use of AI-powered video analysis to simulate elite-level coaching in butterfly stroke technique. Using Google’s Gemini 2.5, the goal of the project is to determinewhether a large multimodel, trained on technique videos of elite swimmers, can generate detailed and personalized feedback that mirrors the insight of a well-informed human swim coach. Training videos featuring Olympic-level butterfly swimmers were used to establish an internal reference model of an ideal butterfly technique. The model was then presented with videos of collegiate swimmers and prompted to deliver coaching-style feedback. Overall, this project demonstrates the potential for AI systems to support accessible athletic development, offering real-time, technical feedback based upon researched coaching science and elite athletic performance.
Recommended Citation
Eisenbeis, Gwen, "Exploring the Potential of AI for Swim Technique Evaluation and Athlete-Centered Coaching" (2025). IPHS 300: AI for Humanity. Paper 55.
https://digital.kenyon.edu/dh_iphs_ai/55
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
