Model Evaluation
After running a model, RIME can evaluate its output against your gold-standard annotations.
Opening the Model Evaluation panel
View → Model Evaluation
What the panel computes
Evaluation compares model-detected events to annotated events in the corresponding lane.
| Metric | Description |
|---|---|
| Sensitivity | True positive rate (detected FOG / annotated FOG) |
| Specificity | True negative rate |
| F1 score | Harmonic mean of precision and recall |
| Event overlap | Per-episode overlap between detected and annotated events |
Evaluation window
You can restrict evaluation to a specific task condition to compare model performance across walking contexts.
Exporting evaluation results
Evaluation metrics are included in the session export. See Export & Reports.