Saccade derivative filters and their clinical implications
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Updated: Oct 29, 2026

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
Published on: March 18, 2019
1Electrical & Systems Engineering Department, University of Connecticut, Storrs 06269-2157, USA.
Abstract:
A saccade model is used to evaluate the accuracy of three derivative algorithms, the two-point central difference derivative filter, band-limited derivative filter and median derivative filter. Noise contaminated saccade simulations are used to compare the known velocity and acceleration waveforms with estimates from each of the three algorithms. The median derivative filter, a nonlinear differentiating digital filter, provides the best velocity estimates from an eye position signal. This filter has no impulse response function, eliminates Gibb's phenomena evident in all linear filters, and is easy to implement.

