The Complete Pipeline
Other eye tracking systems leave you on your own after recording. EYNA provides a complete pipeline from experiment creation through statistical analysis—all in Python.
| Stage | What EYNA Provides |
|---|---|
| Experiment Creation | PsychoPy integration with structured templates |
| Calibration | Streamlined GUI with verification |
| Recording | Simple API (start, stop, add_marker) |
| Data Wrangling | Automatic file organization |
| Data Validation | Built-in quality checks |
| Data Cleaning | Standardized preprocessing |
| Data Analysis | Bayesian mixed-effects models |
Unified Analysis Framework
Bayesian general mixed-effects models as the statistical backbone for all analysis types:
- Area of interest (AOI) analysis
- Fixation metrics
- Pupillometry
- Scanpath analysis
Learn the framework once, apply it everywhere.
Handles Real Eye Tracking Data
- Nested observations (multiple fixations per participant)
- Non-normal distributions (skewed fixation durations)
- Missing data (blinks, track loss)
- Small sample sizes
Direct Probability Statements
Instead of “p < 0.05”, get interpretable results:
“97% probability that high-interest images receive longer fixations, with the difference likely between 45-89ms.”
Appropriate Distributions
- Log-normal for fixation durations
- Beta for proportions
- Poisson for counts
- Automatic handling—no manual transforms needed
Ready to Get Started?
Contact us to learn more about EYNA Helix or see our pricing.