# I-Corps: Translation Potential of Real-Time Injury Prediction in Sports Using Machine Learning and Biomechanical Data

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · Cal Poly Pomona Foundation, Inc. (CA) · $50,000

## Abstract

This I-Corps project is based on the development of an injury risk prediction tool to prevent non-contact injuries in high-intensity sports such as soccer. Non-contact injuries, such as anterior cruciate ligament (ACL) tears, are a leading cause of time-loss injuries in collegiate and professional athletes and often have long-term physical and financial impacts. Traditional approaches to injury prevention rely on historical or post-injury data and are often inadequate due to limited customization and delayed response. This technology addresses these limitations by providing real-time, personalized risk assessments using wearable technology and advanced analytics. The solution may reduce injury rates, improve player well-being, enable longer athletic careers, and provide cost savings for teams, universities, and insurers. This technology may streamline data analysis, enhance communication among coaching staff, and offer an actionable dashboard for decision-making, leading to better training plans and fewer injuries.

This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a machine learning-based platform that integrates biomechanical, physiological, and performance data to detect and prevent injuries in athletes. The core technology includes statistical and machine learning models trained on real-world movement and workload data from athletes, enabling the system to generate

## Key facts

- **NSF award ID:** 2534759
- **Awardee organization:** Cal Poly Pomona Foundation, Inc. (CA)
- **SAM.gov UEI:** JMGMMM7BMBT6
- **PI:** Payam Parsa
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** ARTIFICIAL INTELL & COGNIT SCI
- **Estimated total:** $50,000
- **Funds obligated:** $50,000
- **Transaction type:** Standard Grant
- **Period:** 09/15/2025 → 08/31/2026

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2534759

## Citation

> US National Science Foundation, Award 2534759, I-Corps: Translation Potential of Real-Time Injury Prediction in Sports Using Machine Learning and Biomechanical Data. Retrieved via AI Analytics 2026-06-07 from https://api.ai-analytics.org/grant/nsf/2534759. Licensed CC0.

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