Extended Fitts' law in three-dimensional pointing tasks

2010 ◽  
Author(s):  
Yeonjoo Cha ◽  
Rohae Myung
Keyword(s):  
Three Dimensional ◽  
Fitts Law

scholarly journals Extended Fitts' Law for Three-Dimensional Environment

2010 ◽  
Vol 29 (6) ◽  
pp. 861-868 ◽  
Author(s):  
Yeon-Joo Cha ◽  
Ro-Hae Myung
Keyword(s):  
Three Dimensional ◽  
Fitts Law

Foot Placement and Response Latency: A Test of Fitts' Law

1980 ◽  
Vol 24 (1) ◽  
pp. 626-628 ◽  
Author(s):  
Howard J Glaser ◽  
Charles G. Halcomb
Keyword(s):  
Response Latency ◽  
Movement Time ◽  
Three Dimensional ◽  
Vertical Plane ◽  
Brake Pedal ◽  
Lateral Separation ◽  
Response Latencies ◽  
Foot Placement ◽  
Fitts Law ◽  
Experimental Response

Response latencies were compared for three-dimensional brake/accelerator placements (depth, height, and lateral separation). Brake pedal width was found to be the only factor significantly affecting movement time. A comparison between Fitts' and Welford's movement time predictions and experimental response latencies resulted in correlations of .549 (p<.0001) and .543 (p<.0001). Neither movement time equations were able to predict response latencies when the brake pedal was placed 2.54 cm behind the vertical plane of the accelerator. Fitts' and Welford's equations are seen to have limited use in predicting three-dimensional foot movements.

Extending Fitts’ Law to three-dimensional obstacle-avoidance movements: support for the posture-based motion planning model

2010 ◽  
Vol 207 (1-2) ◽  
pp. 133-138 ◽  
Author(s):  
Jonathan Vaughan ◽  
Deborah A. Barany ◽  
Anthony W. Sali ◽  
Steven A. Jax ◽  
David A. Rosenbaum
Keyword(s):  
Motion Planning ◽  
Obstacle Avoidance ◽  
Three Dimensional ◽  
Planning Model ◽  
Fitts Law

scholarly journals High-fidelity Musculoskeletal Modeling Reveals a Motor Planning Contribution to the Speed-Accuracy Tradeoff

2019 ◽  
Author(s):  
Mazen Al Borno ◽  
Saurabh Vyas ◽  
Krishna V. Shenoy ◽  
Scott L. Delp
Keyword(s):  
Optimal Control ◽  
Optimal Control Theory ◽  
Three Dimensional ◽  
Motor Planning ◽  
Reaching Movements ◽  
High Fidelity ◽  
Movement Duration ◽  
Fitts Law ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

AbstractThe speed-accuracy tradeoff is a fundamental aspect of goal-directed motor behavior, empirically formalized by Fitts’ law, which relates movement duration to movement distance and target width. Here, we introduce a computational model of three-dimensional upper extremity movements that reproduces well-known features of reaching movements and is more biomechanically realistic than previous models. Critically, these features arise without the need of signal-dependent noise. We analyzed motor cortical neural activity from monkeys reaching to targets of different sizes. We found that the contribution of preparatory neural states to movement duration variability was greater for smaller targets than larger targets, and that movements to smaller targets exhibited less variability in preparatory neural states, but greater movement duration variability. Taken together, these results suggest that Fitts’ law emerges from greater task demands constraining the optimization landscape in a fashion that reduces the number of “good” control solutions (i.e., faster reaches). Thus, the speed-accuracy tradeoff could be a consequence of motor planning variability and optimal control theory, and not exclusively signal-dependent noise, as is currently held.Significance StatementA long-standing challenge in motor neuroscience is to understand the relationship between movement speed and accuracy, known as the speed-accuracy tradeoff. We introduce a computational model of reaching movements based on optimal control theory using a realistic model of musculoskeletal dynamics. The model synthesizes three-dimensional point-to-point reaching movements that reproduce kinematics features reported in motor control studies. Such high-fidelity modeling reveals that the speed-accuracy tradeoff as described by Fitts’ law emerges even without the presence of motor noise, which is commonly believed to underlie the speed-accuracy tradeoff. This suggests an alternative theory based on suboptimal control solutions. The crux of this theory is that some features of human movement are attributable to planning variability rather than execution noise.

Effect of Variable Visual-Feedback Delay on Movement Time

2007 ◽  
Vol 51 (19) ◽  
pp. 1373-1377 ◽  
Author(s):  
Julio C. Mateo ◽  
Robert H. Gilkey ◽  
Jeffrey L. Cowgill
Keyword(s):  
Standard Deviation ◽  
Closed Loop ◽  
Movement Time ◽  
Three Dimensional ◽  
Feedback Delay ◽  
Fitts Law ◽  
Mean Delay ◽  
Delay Variability ◽  
The Mean ◽  
3D Virtual Environment

The effects of variable feedback delays on movement time were examined in a three-dimensional (3D) virtual environment. The participants' task was to use a 3D controller to position a cursor in targets as they appeared in a cubic workspace. Both the mean and standard deviation of the delay between the movement of the controller and the displayed position of the cursor were manipulated. In addition, the size of the targets and the distance between targets were varied. The results suggested that movement times are much more strongly affected by mean delay than by delay variability and that the effect of both variables is greatest during the closed-loop component of the movement. The results are discussed in relation to buffering strategies for reducing delay variability, Fitts' law, and other descriptions of aimed movements.

Extending Fitts' law to a three-dimensional pointing task

2001 ◽  
Vol 20 (6) ◽  
pp. 791-805 ◽  
Author(s):  
Atsuo Murata ◽  
Hirokazu Iwase
Keyword(s):  
Three Dimensional ◽  
Fitts Law ◽  
Pointing Task

scholarly journals High-fidelity musculoskeletal modeling reveals that motor planning variability contributes to the speed-accuracy tradeoff

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Mazen Al Borno ◽  
Saurabh Vyas ◽  
Krishna V Shenoy ◽  
Scott L Delp
Keyword(s):  
Neural Activity ◽  
Three Dimensional ◽  
Motor Planning ◽  
Good Control ◽  
Population Level ◽  
Task Demands ◽  
Movement Speed ◽  
Fitts Law ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

A long-standing challenge in motor neuroscience is to understand the relationship between movement speed and accuracy, known as the speed-accuracy tradeoff. Here, we introduce a biomechanically realistic computational model of three-dimensional upper extremity movements that reproduces well-known features of reaching movements. This model revealed that the speed-accuracy tradeoff, as described by Fitts’ law, emerges even without the presence of motor noise, which is commonly believed to underlie the speed-accuracy tradeoff. Next, we analyzed motor cortical neural activity from monkeys reaching to targets of different sizes. We found that the contribution of preparatory neural activity to movement duration (MD) variability is greater for smaller targets than larger targets, and that movements to smaller targets exhibit less variability in population-level preparatory activity, but greater MD variability. These results propose a new theory underlying the speed-accuracy tradeoff: Fitts’ law emerges from greater task demands constraining the optimization landscape in a fashion that reduces the number of ‘good’ control solutions (i.e., faster reaches). Thus, contrary to current beliefs, the speed-accuracy tradeoff could be a consequence of motor planning variability and not exclusively signal-dependent noise.

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