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An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones
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Generalized priority-based model for smartphone screen touches.

Jean-Pascal Pfister1, Arko Ghosh2

  • 1Institute of Neuroinformatics and Neuroscience Center Zurich, University of Zurich/ETH Zurich, 8057 Zürich, Switzerland and Department of Physiology, University of Bern, 3012 Bern, Switzerland.

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Summary
This summary is machine-generated.

Human action intervals, like smartphone touches, show different patterns at short and long timescales. A new model links fast motor processes to cognitive planning, explaining these distinct patterns.

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Area of Science:

  • Human-computer interaction
  • Cognitive science
  • Behavioral neuroscience

Background:

  • Human action intervals exhibit distinct statistical properties at short and long timescales.
  • Longer timescales often show scale-invariant (power-law) distributions, linked to complex cognitive processes like planning.
  • Shorter timescales are less understood and governed by different mechanisms, such as sensorimotor control.

Purpose of the Study:

  • To analyze the distribution of smartphone screen touch intervals across multiple timescales.
  • To develop and extend a generative model capable of capturing these intervals and their variations.
  • To investigate the relationship between short-timescale motor processes and long-timescale cognitive control.

Main Methods:

  • Analysis of 9 million smartphone screen touch intervals from 84 individuals.
  • Extension of a priority-based generative model to accommodate smartphone interaction events.
  • Model fitting to capture interindividual variations and identify key parameters.

Main Results:

  • Smartphone intertouch intervals follow different distributions at short and long timescales.
  • A unified model explains short-timescale refractory effects and long-timescale task-priority dynamics.
  • Each individual possesses a unique power-law exponent related to their refractory time constant.

Conclusions:

  • Motor processes influencing rapid actions are intrinsically linked to higher cognitive processes governing longer intervals.
  • The developed model provides a tractable framework for understanding human action timing across timescales.
  • Individual differences in action timing can be characterized by specific model parameters.