At a glance
- What
- A wavelet-inspired decomposition that finds submovements in a mouse speed series and gives each a location, width and amplitude.
- Why
- Submovements overlap: the next starts before the previous ends. Segmentation cuts the time axis into intervals and assigns each instant to one movement, so it cannot measure overlap.
- How
- A CWT with a log-normal speed shape as mother wavelet seeds the fit; a peak-weighted loss refines it, repeating on the residual. Synthetic trials modelled on 13 users' FPS aiming data supply a known count.
- New
- Overlapping movements count separately rather than as one. Peak-weighted refinement recovered the correct submovement count in 67.124% of synthetic trials, above MSE refinement or the raw CWT guess.
