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Attention, Perception, & Psychophysics

, Volume 81, Issue 1, pp 12–19 | Cite as

The relationship between task difficulty and motor performance complexity

  • Stacey L. Gorniak
Short Report

Abstract

Difficult tasks are commonly equated with complex tasks across many behaviors. Motor task difficulty is traditionally defined via Fitts’ law, using evaluation criteria based on spatial movement constraints. Complexity of data is typically evaluated using non-linear computational approaches. In this project, we investigate the potential to evaluate task difficulty via behavioral (motor performance) complexity in a Fitts-type task. Use of non-linear approaches allows for inclusion of many features of motor actions that are not currently included in the Fitts-type paradigm. Our results indicate that tasks defined as more difficult (using Fitts movement IDs) are not associated with complex motor behaviors; rather, an inverse relationship exists between these two concepts. Use of non-linear techniques allowed for the detection of behavioral differences in motor performance over the entire action trajectory in the presence of action errors and among neutrally co-constrained effectors not detected using traditional Fitts’-type analyses utilizing movement time measures. Our findings indicate that task difficulty may potentially be inferred using non-linear measures, particularly in ecological situations that do not obey the Fitts-type testing paradigm. While we are optimistic regarding these initial findings, further work is needed to assess the full potential of the approach.

Keywords

Fitts’ law Motor behavior Non-linear analysis Complexity Task difficulty 

Notes

Acknowledgements

The author would like to thank Mark Latash and the Motor Control Laboratory (MCL) at the Pennsylvania State University. The data presented in this manuscript were collected in the MCL. The author would also like to thank Amanda Butcher for her assistance in generating artwork for this manuscript, and Nicholas Stergiou and the Nebraska Biomechanics Core Facility (NBCF) for their insights, comments, and discussion on using non-linear dynamics in behavioral research.

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Copyright information

© The Psychonomic Society, Inc. 2018

Authors and Affiliations

  1. 1.Department of Health and Human PerformanceUniversity of HoustonHoustonUSA
  2. 2.Center for Neuromotor and Biomechanics ResearchUniversity of HoustonHoustonUSA

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