Improving on Human’s Movement Time Model for Pointing Task - Introducing the Target Position Factor into Fitts’ Law

2012 ◽  
Vol 433-440 ◽  
pp. 2349-2355
Author(s):  
Jun Min Du ◽  
Hai Wen Shi
Keyword(s):  
Movement Time ◽  
Target Position ◽  
Model Fit ◽  
Time Data ◽  
Conventional Model ◽  
Time Model ◽  
Fitts Law ◽  
Pointing Movement ◽  
Starting Point ◽  
Pointing Movements

The experiments were aimed at determining the effect of target position on movement time when performing a target pointing movement task. 21 subjects performed pointing movements with 72 conditions of various target position. The movement time data were collected. It was shown that the starting point position and target position greatly affect the movement time. As a result, the movement times were not explained satisfactorily by the conventional Fitts’ model. The conventional model was improved by introducing the target position factor into. Compared with the conventional Fitts’ model, the new model could describe the data better, both in term of contribution value (r2) and the standard error of the residual between the predicted value by model fit and the measured movement time.

Fitting Motivation to Fitts’ Law : Effect of a Penalty Contingency on Controlled Movement

2018 ◽  
Vol 62 (1) ◽  
pp. 265-269 ◽  
Author(s):  
Douglas J. Gillan ◽  
Randolph G. Bias
Keyword(s):  
Movement Time ◽  
Movement Control ◽  
Target Size ◽  
Movement Behavior ◽  
Target Acquisition ◽  
Computer Screen ◽  
Fitts Law ◽  
Starting Point ◽  
Movement Distance ◽  
Index Of Difficulty

An experiment examined the effect of a penalty on performance of target acquisition movements, focusing on overall movement time, the fit of the data to Fitts’ Law, and ballistic and homing submovements. Fitts’ Law, MT = a + b[Index of Difficulty], where Index of Difficulty (ID) = log2[Movement distance/target size], focuses on the control of the movement by external stimuli, rather than the consequences of a movement. In this study, participants moved a cursor on a computer screen from a starting point to a target with movement distance and target size varying systematically. In the Penalty condition, when the movement missed the target, the computer screen went blank and the next trial was delayed for 30 seconds. In the Nonpenalty condition, participants did not receive a penalty for missing the target. The results showed that receiving a penalty led to higher movement times, a higher Fitts’ Law slope parameter, fewer errors, and fewer nonerror overshoots of the target. Also, receiving penalties resulted in target acquisition movements with less time spent in the ballistic submovement. The results show that consequences of a movement control movement behavior.

scholarly journals Both Sides Now: Both Height and Width of the Target Matter for Applying Fitts’ Law to Pointing Using a Mouse

2019 ◽  
Vol 63 (1) ◽  
pp. 381-385
Author(s):  
Douglas J. Gillan
Keyword(s):  
User Interface ◽  
Interface Design ◽  
Movement Time ◽  
User Interface Design ◽  
Task Environment ◽  
Target Height ◽  
Fitts Law ◽  
Starting Point ◽  
Direction Of Movement ◽  
Index Of Difficulty

Research on target acquisition has focused on two features of the task environment – the distance moved and the size of the target in the direction of movement. The present research examined the effect of the size of the target in the direction orthogonal to the direction of movement (typically called the target height) on the time to move to a target. The experiment varied the Index of Difficulty (ID) (by varying the distance moved and the target width) and the target height in a task in which participants moved a cursor from a starting point to the target. The results found that (1) movement time was linearly related to ID at each of three levels of target height, (2) movement time increased as target height decreased, and (3) the slope of the function relating movement time to ID decreased as target height decreased. The discussion addresses two possible explanations for the results, how Fitts’ Law might be modified to take target height into account, and how the results could be applied to user interface design.

Movement Time to an Array of Controls

1993 ◽  
Vol 37 (9) ◽  
pp. 625-629 ◽  
Author(s):  
Errol R. Hoffmann
Keyword(s):  
Mathematical Model ◽  
Theoretical Result ◽  
Movement Time ◽  
Element Model ◽  
Optimum Control ◽  
Fitts Law ◽  
Model Based ◽  
Array Density

Two tasks in which subjects aim at an array of devices were considered: moving to one knob within an array and moving the finger on a numeric keypad. It was shown by a mathematical model based on Fitts' law, that when the array density is specified for the array of knobs or keys, there is an optimum control size for minimum movement time. The theoretical result was obtained by considering a two-element model of the movement, the first being a reach to the general location of the control and the second describing the insertion of the fingers into the space between adjacent controls. As the first element has a movement time that decreases with increase of control size and the second a time increasing with control size, there is an optimum control size where the movement time is a minimum.

scholarly journals Inter-trial effects in priming of pop-out: Comparison of computational updating models

2021 ◽  
Vol 17 (9) ◽  
pp. e1009332
Author(s):  
Fredrik Allenmark ◽  
Ahu Gokce ◽  
Thomas Geyer ◽  
Artyom Zinchenko ◽  
Hermann J. Müller ◽  
...  
Keyword(s):  
Model Comparison ◽  
Response Times ◽  
Target Position ◽  
Preceding Trial ◽  
Target Color ◽  
Model Parameters ◽  
Target Feature ◽  
Modeling Framework ◽  
Trial Effect ◽  
Starting Point

In visual search tasks, repeating features or the position of the target results in faster response times. Such inter-trial ‘priming’ effects occur not just for repetitions from the immediately preceding trial but also from trials further back. A paradigm known to produce particularly long-lasting inter-trial effects–of the target-defining feature, target position, and response (feature)–is the ‘priming of pop-out’ (PoP) paradigm, which typically uses sparse search displays and random swapping across trials of target- and distractor-defining features. However, the mechanisms underlying these inter-trial effects are still not well understood. To address this, we applied a modeling framework combining an evidence accumulation (EA) model with different computational updating rules of the model parameters (i.e., the drift rate and starting point of EA) for different aspects of stimulus history, to data from a (previously published) PoP study that had revealed significant inter-trial effects from several trials back for repetitions of the target color, the target position, and (response-critical) target feature. By performing a systematic model comparison, we aimed to determine which EA model parameter and which updating rule for that parameter best accounts for each inter-trial effect and the associated n-back temporal profile. We found that, in general, our modeling framework could accurately predict the n-back temporal profiles. Further, target color- and position-based inter-trial effects were best understood as arising from redistribution of a limited-capacity weight resource which determines the EA rate. In contrast, response-based inter-trial effects were best explained by a bias of the starting point towards the response associated with a previous target; this bias appeared largely tied to the position of the target. These findings elucidate how our cognitive system continually tracks, and updates an internal predictive model of, a number of separable stimulus and response parameters in order to optimize task performance.

Factors Affecting Remote Positioning Performance

1995 ◽  
Vol 39 (4) ◽  
pp. 282-286
Author(s):  
Shang H. Hsu ◽  
Chien C. Huang
Keyword(s):  
Movement Time ◽  
Interactive Effect ◽  
Vertical Movement ◽  
Movement Direction ◽  
Movement Amplitude ◽  
Distance Ratio ◽  
Factors Affecting ◽  
Fitts Law ◽  
Movement Distance ◽  
Two Measures

The purpose of this study was to investigate the effects of target width, movement direction, movement amplitude, and remote distance on remote positioning performance. Movement time and movement distance ratio were taken as measures of remote positioning performance. It was found that the effects of target width, movement amplitude, and movement direction on the two measures were significant. The effect of remote distance was significant only for movement distance ratio. The magnitude of the effect of target width on movement time was larger than that of movement amplitude; a modification of Fitts' Law was thus proposed. Moreover, there was an interactive effect between target width and movement direction- i.e., movement direction had an effect only when the target width was small. Among the eight movement directions, upward vertical movement was the best for remote positioning. The results shed some light onto the design of remote control user interface.

A Kinematic Evaluation of Linear and Parabolic Pointing in Virtual Reality

2021 ◽  
Vol 65 (1) ◽  
pp. 86-90
Author(s):  
John Sermarini ◽  
Joseph T. Kider ◽  
Joseph J. LaViola ◽  
Daniel S. McConnell
Keyword(s):  
Virtual Reality ◽  
Virtual Environments ◽  
Movement Time ◽  
Interaction Style ◽  
Task Constraint ◽  
Immersive Virtual Environments ◽  
Pointing Task ◽  
Pointing Movements ◽  
Movement Distance ◽  
Kinematic Evaluation

We present the results of a study investigating the influence of task and effector constraints on the kinematics of pointing movements performed in immersive virtual environments. We compared the effect of target width, as a task constraint, to the effect of movement distance, as an effector constraint, in terms of overall effect on movement time in a pointing task. We also compared a linear ray-cast pointing technique to a parabolic pointing technique to understand how interaction style may be understood in the context of task and effector constraints. The effect of target width as an information constraint on pointing performance was amplified in VR. Pointing technique acted as an effector constraint, with linear ray-cast pointing resulting in faster performance than parabolic pointers.

Gaze Affects Pointing Toward Remembered Visual Targets After a Self-Initiated Step

2004 ◽  
Vol 92 (4) ◽  
pp. 2380-2393 ◽  
Author(s):  
M. A. Admiraal ◽  
N.L.W. Keijsers ◽  
C.C.A.M. Gielen
Keyword(s):  
Visual Information ◽  
Body Movement ◽  
Target Position ◽  
The Body ◽  
Complete Darkness ◽  
Step Size ◽  
Pointing Movement ◽  
Pointing Accuracy ◽  
The Subject ◽  
Variable Errors

We have investigated pointing movements toward remembered targets after an intervening self-generated body movement. We tested to what extent visual information about the environment or finger position is used in updating target position relative to the body after a step and whether gaze plays a role in the accuracy of the pointing movement. Subjects were tested in three visual conditions: complete darkness (DARK), complete darkness with visual feedback of the finger (FINGER), and with vision of a well-defined environment and with feedback of the finger (FRAME). Pointing accuracy was rather poor in the FINGER and DARK conditions, which did not provide vision of the environment. Constant pointing errors were mainly in the direction of the step and ranged from about 10 to 20 cm. Differences between binocular fixation and target position were often related to the step size and direction. At the beginning of the trial, when the target was visible, fixation was on target. After target extinction, fixation moved away from the target relative to the subject. The variability in the pointing positions appeared to be related to the variable errors in fixation, and the co-variance increases during the delay period after the step, reaching a highly significant value at the time of pointing. The significant co-variance between fixation position and pointing is not the result of a mutual dependence on the step, since we corrected for any direct contributions of the step in both signals. We conclude that the co-variance between fixation and pointing position reflects 1) a common command signal for gaze and arm movements and 2) an effect of fixation on pointing accuracy at the time of pointing.

What is Fitts' law about?

1997 ◽  
Vol 20 (2) ◽  
pp. 312-313
Author(s):  
Herbert Heuer
Keyword(s):  
Movement Time ◽  
Fitts Law ◽  
Kinematic Theory

Movement time and accuracy, as defined by Plamondon & Alimi, do not conform to empirical definitions. When definitions are used that conform better to empirical ones, the original predictions of the kinematic theory are no longer valid – as is demonstrated by simulations. Thus the theoretically derived quadratic law and the successful empirical quadratic law seem to be independent of each other.

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.

Application of Fitts' Law to Foot-Pedal Design

1975 ◽  
Vol 17 (4) ◽  
pp. 368-373 ◽  
Author(s):  
Colin G. Drury
Keyword(s):  
Movement Time ◽  
Hand Movements ◽  
Slight Effect ◽  
Fitts Law ◽  
Foot Tapping ◽  
Direction Of Movement

Two experiments on reciprocal foot tapping between pedals showed that a modified version of Fitts' Law can predict movement time for a variety of pedal sizes and separations. Using a relationship between times for reciprocal tapping and single movements found for hand movements, the present results predict closely the movement times obtained under specific conditions by earlier researchers. When pedals are at minimum safe separation it is concluded that pedal widths and direction of movement have only a slight effect on movement time.

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