Clinical Validation of an On-Device AI-Driven Real-Time Human Pose Estimation and Exercise Prescription Program; Prospective Single-Arm Quasi-Experimental Study
This study provides the first clinical evidence that on-device AI pose estimation enables facility-independent resistance training with outcomes comparable to traditional programs. Unlike cloud-based systems, our lightweight model (28.6 ms inference) supports real-time mobile deployment, advancing accessible precision exercise medicine. Limitations include a single-arm design and gender imbalance, warranting future RCTs with diverse cohorts.
Authors
- Taeseok Choi (ORCID: https://orcid.org/0000-0003-0858-121X)
- Wansuk Choi
- Seoyoon Heo
Institutions
- Kunsan National University (KR)
- Kyungwoon University (KR)
- Kyungbok University (KR)
Publication Details
- Journal
- Healthcare
- Published
- 2026-02-13
- DOI
- https://doi.org/10.3390/healthcare14040482
- Primary Topic
- Sports Performance and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00