This project explores the use of heart rate variability (HRV) to classify exercise intensity zones. The primary goal is to determine whether a short RR-interval sequence (~1 min) can reliably indicate which intensity zone the subject is in.
- Classify intensity zones using HRV (time or frequency domain features).
- Determine the minimum time window required for reliable classification.
- Use Random Forest for classification based on selected features.
- Try other models, like NNs, if necessary.
- Use data from incremental exercise tests where VT1 and VT2 are known to occur between two workload steps.
- Ideally follow-up tests with finer workload increments between those steps could improve resolution. (-> Repeat the process to refine the precision of VT detection.)
Includes:
- Power output
- RR-intervals
- VO₂ measurements
- Ventilatory thresholds
These were collected from graded exercise tests on a cycle ergometer involving 18 subjects, sourced from this dataset.
Model development for classification is currently in progress.
- Extend classification to lactate thresholds.
- Validate model across different populations and test protocols.