Harness the power of deep learning to identify respiratory-based exercise intensity thresholds with expert-level accuracy. Trained on over 1,600 CPETs, Oxynet delivers instant, objective threshold detection validated in peer-reviewed research.
What is Oxynet?
Oxynet is a cutting-edge deep learning system that automatically detects exercise thresholds with expert-level precision. Using advanced neural networks trained on hundreds of cardiopulmonary exercise tests from diverse populations (from chronic heart failure patients to trained distance runners), Oxynet provides objective, reproducible threshold identification in real-time.
Key features of Oxynet include:
Coming in our next publication: Our research demonstrates that Oxynet performs comparably to expert consensus in identifying respiratory-based exercise intensity thresholds, with the added benefits of objectivity, speed, and standardization. This technology represents a breakthrough in exercise physiology, combining deep learning with pedagogical best practices for both clinical and educational applications.
