Elsevier

Human Movement Science

Volume 29, Issue 6, December 2010, Pages 882-892
Human Movement Science

Fitts’ law holds for pointing movements under conditions of restricted visual feedback

https://doi.org/10.1016/j.humov.2010.03.009Get rights and content

Abstract

Fitts’ law robustly predicts the time required to move rapidly to a target. However, it is unclear whether Fitts’ law holds for visually guided actions under visually restricted conditions. We tested whether Fitts’ law applies under various conditions of visual restriction and compared pointing movements in each condition. Ten healthy participants performed four pointing movement tasks under different visual feedback conditions, including full-vision (FV), no-hand-movement (NM), no-target-location (NT), and no-vision (NV) feedback conditions. The movement times (MTs) for each task exhibited highly linear relationships with the index of difficulty (r2 > .96). These findings suggest that pointing movements follow Fitts’ law even when visual feedback is restricted or absent. However, the MTs and accuracy of pointing movements decreased for difficult tasks involving visual restriction.

Introduction

Pointing is one of the most common human motor behaviors. In human pointing, spatial accuracy decreases as the speed of movement increases and movement becomes slower as the need for accuracy increases. The early work of Woodworth (1899) examined the conditions that affect movement accuracy and began a long tradition of research on motor control. The next great contribution to research on speed-accuracy trade-offs came from Fitts (1954), who was the first to propose a formal relationship between movement time (MT) and the index of difficulty (ID). In the studies by Fitts and colleagues (Fitts, 1954, Fitts and Peterson, 1964), participants were asked to move their hands between two targets that varied in width (W: the width of the target) and amplitude (A: the distance from the starting point to the target). The critical variable was the ID, which is given by the relation of the A of the movement to the W of the target (ID = log2 (2A/W)). The ID term quantifies the difficulty of the movement task: as the ID increases, the difficulty of the movement increases. The results indicated that the relationship between MT and the ID could be captured by a linear function (i.e., MT = a + b*ID; a and b are empirical constants). This equation was found to be so widely applicable that it became known as Fitts’ law (for review, see Plamondon & Alimi, 1997). Since Fitts’ early experiments, the relationship between the ID and MT has been replicated hundreds of times across a wide range of conditions, including pointing at two-dimensional and three-dimensional targets (Adam et al., 2006, Adamovich et al., 1998, Augustyn and Rosenbaum, 2005, Kovacs et al., 2008, Murata and Iwase, 2001), visual illusion targets (Glover, 2002), and obstacle avoidance tasks (Jax, Rosenbaum, & Vaughan, 2007). Recent studies have also confirmed the applicability of Fitts’ law to prehension movements, mouse cursor movements, rotational movements, and foot movements (Abrams et al., 1990, Bootsma et al., 1994, Grosjean et al., 2007, Hoffmann, 1991, Lin et al., 1992).

When humans execute simple reaching movements, they automatically carry out a number of continuous multi-step processes, including processes involving object cognition, movement planning, perceptual feedback, and on-line movement control. The origins of this planning-control model date back more than a century to Woodworth (1899), who separated rapid movement into two phases known as the initial adjustment phase (i.e., movement planning) and the current control phase (i.e., on-line control). Over the years, this model has been examined and extended considerably (for review, see Glover, 2002). Visual feedback about the status of a target and one’s hand movements are typically available for both movement planning and on-line control (Goodale et al., 1986, Mirabella et al., 2008). Results from several previous studies have indicated that movement accuracy increases when visual feedback of the moving limb is available (Bard et al., 1985, Proteau et al., 2000, Spijkers and Spellerberg, 1995). However, a recent study (Sarlegna et al., 2003) found that visual information on the target’s position contributed more to the on-line control of goal-directed arm movements than did visual information on hand position.

More recently, Brouwer and Knill, 2007, Brouwer and Knill, 2009 suggested that when no visual information is available, people use the information about location that they memorized during planning to move their hands to a target location; however, this strategy yields poor accuracy. For instance, Brouwer and Knill (2007) used visually guided reaching procedures to test the relative reliability of visually presented and remembered information during reaching. They reported that vision appeared to dominate when vision was significantly more reliable than the information stored in memory, but under conditions in which visual information was degraded, the brain gave more weight to information stored in memory to plan and control movements. However, the accuracy of movements guided by memory was poorer than the accuracy of movements guided by visual information because the memorized information was sometimes imprecise and inaccurate. In summary, these studies demonstrated that humans can execute goal-directed movements even when visual feedback is not available during execution of the movement.

As mentioned above, numerous previous studies have investigated characteristic visually guided human actions using different dimensional and body part conditions. In addition, some of these reports have also discussed the contributions of target- and body part-relevant information to goal-directed movement. However, it remains unclear whether Fitts’ law holds for visually guided actions under conditions of restricted vision. In the classical Fitts’ task (Fitts, 1954), the participants were asked to perform reciprocal tapping tasks with two rectangular metal plates. The participants were given 2 s to see the locations of the targets and their hands before each trial, and the participants started tapping when they heard an audio cue. Because of this experimental design, both planning and on-line control mechanisms were used to ensure accurate reciprocal tapping movements in Fitts’ task. However, the existing evidence for Fitts’ crucial finding that MTs are directly related to amplitude, and target size is limited to full-vision conditions. Although some recent studies (e.g., Grosjean et al., 2007, Murata and Iwase, 2001) have indicated that Fitts’ law also holds for different movements, effectors, and movement contexts, these tasks included both movement planning and on-line control processes. Therefore, in this study we tested whether Fitts’ law applies when visual feedback during pointing is absent or restricted.

In this study, we used four visually restricted conditions to determine whether Fitts’ law was applicable (i.e., full-vision, no feedback about hand movement, no feedback about target location, and no visual feedback of any type). Ten participants performed pointing movements while holding a stylus under all four conditions. The condition of full-vision feedback (i.e., both the target location and the participant’s hand movement were visible, as in common goal-directed movement) was used as the control condition. The conditions of no-hand-movement feedback and no-target-location feedback were designed to test how hand movement and target location feedback, respectively, influence Fitts’ relationship. Finally, the condition of no visual feedback was designed to test whether Fitts’ law applies to pointing movements when there is no visual feedback. We also address differences in MT and accuracy under these four conditions. The results indicate that although the accuracy of pointing movements was degraded under conditions of visual restriction, the first motor principle of Fitts’ law was applicable under all conditions. However, there were several important differences between the four conditions in terms of the parameters of the linear relationship, movement times, accuracy rates, and accuracy distributions.

Section snippets

Method

In this experiment, participants performed four pointing tasks; under full-vision (FV), no-hand-movement (NM), no-target-location (NT), and no-vision (NV) feedback conditions. Because Fitts’ law holds for both discrete and continuous movements (Fitts, 1954, Fitts and Peterson, 1964), we asked participants to use a stylus to point once per trial (i.e., a discrete pointing movement, such as pointing from left-to-right or from right-to-left) during all tasks. Participants were allowed to see the

Control of accuracy

To investigate the differences in pointing performance across the four pointing tasks, we calculated the accuracy rates for each task (Fig. 3). The accuracy rate was defined as the number of trials in which the tip of the stylus touched the target divided by the total number of trials for each task. The mean accuracy rates for each ID in Fig. 3 included both directions of movement. We performed a task (four tasks) × ID (six levels) repeated measures ANOVA on mean accuracy rates. We found

Discussion

The current experiment contrasted performance on four pointing tasks with varying degrees of restriction of visual feedback. The results indicated that Fitts’ law holds for pointing movements under different conditions of restricted visual feedback. However, the results also revealed shorter MTs, lower accuracy rates, and asymmetrical distributions of accurate responses in the NM, NT, and NV tasks. These differences are understandable in the context of the characteristics of human feedback

Acknowledgments

This study was supported in part by a Grant-in-Aid for Scientific Research (B) 21404002, Japan and AA Science Platform Program of the Japan Society for the Promotion Science. We also thank the individuals who participated in this study and the staff of the Wu Laboratory for their assistance with data collection.

References (42)

  • S.V. Adamovich et al.

    Pointing in 3D space to remembered targets I. Kinesthetic versus visual target presentation

    Journal of Neurophysiology

    (1998)
  • J. Annett et al.

    The measurement of elements in an assembly task: the information output of the human motor system

    Quarterly Journal of Experimental Psychology

    (1958)
  • J.S. Augustyn et al.

    Metacognitive control of action: Preparation for aiming reflects knowledge of Fitts’ law

    Psychonomic Bulletin and Review

    (2005)
  • C. Bard et al.

    Role of peripheral vision in the directional control of rapid aiming movements

    Canadian Journal of Psychology

    (1985)
  • J.A. Bauer et al.

    A device for rapid recording of positioning responses in two dimensions

    Behavior Research Methods, Instruments, and Computers

    (1969)
  • R.J. Bootsma et al.

    The speed–accuracy trade-off in manual prehension: Effects of movement amplitude, object size and object width on kinematic characteristics

    Experimental Brain Research

    (1994)
  • A.M. Brouwer et al.

    The role of memory in visually guided reaching

    Journal of Vision

    (2007)
  • A.M. Brouwer et al.

    Humans use visual and remembered information about object location to plan pointing movements

    Journal of Vision

    (2009)
  • P.M. Fitts

    The information capacity of the human motor system in controlling the amplitude of movement

    Journal of Experimental Psychology

    (1954)
  • P.M. Fitts et al.

    Information capacity of discrete motor responses

    Journal of Experimental Psychology

    (1964)
  • P.M. Fitts et al.

    Information capacity of discrete motor responses under different cognitive sets

    Journal of Experimental Psychology

    (1966)
  • Cited by (0)

    View full text