An inverse-linear logistic model of the main sequence

  • Andrew Duchowski Clemson University
  • Krzysztof Krejtz SWPS University of Psychology
  • Cezary Biele National Information Processing Institute
  • Anna Niedzielska National Information Processing Institute
  • Peter Kiefer ETH Zürich
  • Ioannis Giannopoulos ETH Zürich
  • Nina Gehrer University of Tübingen
  • Michael Schönenberg University of Tübingen
Keywords: saccades, microsaccades, main sequence, non-linear modeling


A model of the main sequence is proposed based on the logistic function. The model’s fit to the peak velocity-amplitude relation resembles an S curve, simulta- neously allowing control of the curve’s asymptotes at very small and very large amplitudes, as well as its slope over the mid amplitude range. The proposed inverse-linear logistic model is also able to express the linear relation of duration and amplitude. We demonstrate the utility and robustness of the model when fit to aggregate data at the small- and mid-amplitude ranges, namely when fitting microsaccades, saccades, and superposition of both. We are confident the model will suitably extend to the large-amplitude range of eye movements.

Author Biography

Andrew Duchowski, Clemson University

Professor of Computer Science

Visual Computing

How to Cite
Duchowski, A., Krejtz, K., Biele, C., Niedzielska, A., Kiefer, P., Giannopoulos, I., Gehrer, N., & Schönenberg, M. (2017). An inverse-linear logistic model of the main sequence. Journal of Eye Movement Research, 10(3).