Fitts’ Law Index of Difficulty Evaluated and Extended for Screen Size Variations

Abstract Tactile feedback added to touchscreens provides users with a high-quality interactive experience. The effect of tactile feedback on typical interaction gestures requires to be evaluated. With a custom-designed electrostatic tactile feedback device, we explore the effects of tactile feedback on zoom-in/out gestures and determine the issues satisfied by the relationship between completion time (CT) and index of difficulty (ID). Specifically, we compare the effect of electrostatic tactile feedback on the efficiency and accuracy of zoom-in/out gestures in three conditions, that is, no tactile feedback, linearly increasing tactile feedback force over operation process, and tactile feedback only in a target area. Then, we study the relationship between CT and ID with tactile feedback added to the target area. Results of experimental data from 12 participants show that tactile feedback added only to a target area can significantly increase operational efficiency and accuracy of zoom-in/out gestures. Furthermore, the relationship between CT and ID agrees well with Fitts’ law, and the correlation coefficient is larger than 0.9.

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Effects of Gain and Index of Difficulty on Mouse Movement Time and Fitts’ Law

IEEE Transactions on Human-Machine Systems ◽

10.1109/thms.2019.2931743 ◽

2019 ◽

Vol 49 (6) ◽

pp. 684-691

Author(s):

Yik Hang Pang ◽

Errol R. Hoffmann ◽

Ravindra S. Goonetilleke

Keyword(s):

Movement Time ◽

Fitts Law ◽

Mouse Movement ◽

Index Of Difficulty

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Effects of Smoking Abstinence on Movement Regulation

Perceptual and Motor Skills ◽

10.2466/pms.2000.90.2.624 ◽

2000 ◽

Vol 90 (2) ◽

pp. 624-630 ◽

Cited By ~ 5

Author(s):

Thomas S. Marzilli ◽

John B. Shea

Keyword(s):

Information Processing ◽

Psychomotor Performance ◽

Movement Time ◽

Smoking Abstinence ◽

Fitts Law ◽

Single Plate ◽

Index Of Difficulty ◽

Psychomotor Tasks ◽

Nicotine Deprivation ◽

Minimal Information

The effect of smoking abstinence on performance of a reciprocal tapping task was investigated. 6 habitual smokers performed a single-plate and two versions of a two-plate tapping task. Fitts' Law was used to compute an index of difficulty (ID) in bits for the tasks which was 0 bits for the single-plate and 3.32 and 4.17 bits for the two-plate versions of the task. While smoking abstinence had no effect on performance of the single-plate tapping task, it increased movement time on performance of both two-plate task versions. These findings may provide a coherent explanation for the prior findings of nicotine deprivation on psychomotor performance in the literature. This explanation suggests that the effects of nicotine deprivation as incurred through smoking abstinence may be on the central mechanisms regulating information-processing rate for successful movement regulation. Thus nicotine deprivation may not affect performance of simple psychomotor tasks which require minimal information processing but will affect the performance of more complex tasks requiring significantly more information processing for successful movement regulation.

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Visual Control of Discrete Aiming Movements

The Quarterly Journal of Experimental Psychology Section A ◽

10.1080/14640748308402136 ◽

1983 ◽

Vol 35 (2) ◽

pp. 311-321 ◽

Cited By ~ 52

Author(s):

Stephen A. Wallace ◽

Karl M. Newell

Keyword(s):

Error Rate ◽

Movement Time ◽

Visual Control ◽

Correction Model ◽

Fitts Law ◽

Rate Analysis ◽

Movement Distance ◽

Rapid Arm Movements ◽

Index Of Difficulty ◽

Highly Correlated

An experiment is reported which investigated the visual control of discrete rapid arm movements. Subjects were required to move as rapidly as possible to several target width-movement distance combinations under both visual and non-visual conditions. The movement time (MT) data were supportive of Fitts' Law in that MT was linearly related and highly correlated to the Index of Difficulty (ID). MT was also similar for different target width-distance combinations sharing the same ID value. The error rate analysis, which compared visual to non-visual Performance, indicated that vision was only used, and to varying degrees, when MT exceeded 200 ms (3.58 ID level). There was some evidence that vision was differentially used within target width-distance combinations sharing the same ID. Estimates of endpoint variability generally reflected the results of the error rate analysis. These results do not support the discrete correction model of Fitts' Law proposed by Keele (1968).

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A New Approach to Modeling the Prediction of Movement Time

Mathematics ◽

10.3390/math9141585 ◽

2021 ◽

Vol 9 (14) ◽

pp. 1585

Author(s):

Chiuhsiang Joe Lin ◽

Chih-Feng Cheng

Keyword(s):

Movement Time ◽

Human Movement ◽

Average Amount Of Information ◽

Movement Response ◽

New Approach ◽

Fitts Law ◽

Proposed Model ◽

Index Of Difficulty ◽

Human Movement Response ◽

Better Than

Fitts’ law predicts the human movement response time for a specific task through a simple linear formulation, in which the intercept and the slope are estimated from the task’s empirical data. This research was motivated by our pilot study, which found that the linear regression’s essential assumptions are not satisfied in the literature. Furthermore, the keystone hypothesis in Fitts’ law, namely that the movement time per response will be directly proportional to the minimum average amount of information per response demanded by the particular amplitude and target width, has never been formally tested. Therefore, in this study we developed an optional formulation by combining the findings from the fields of psychology, physics, and physiology to fulfill the statistical assumptions. An experiment was designed to test the hypothesis in Fitts’ law and to validate the proposed model. To conclude, our results indicated that movement time could be related to the index of difficulty at the same amplitude. The optional formulation accompanies the index of difficulty in Shannon form and performs the prediction better than the traditional model. Finally, a new approach to modeling movement time prediction was deduced from our research results.

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

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931218621061 ◽

2018 ◽

Vol 62 (1) ◽

pp. 265-269 ◽

Cited By ~ 1

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.

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A Logarithmic Speed-Difficulty Trade-off in Speech Production

Motor Control ◽

10.1123/mcj.15.1.52 ◽

2011 ◽

Vol 15 (1) ◽

pp. 52-67 ◽

Cited By ~ 2

Author(s):

Mark L. Latash ◽

Irina L. Mikaelian

Keyword(s):

Task Difficulty ◽

Native Speakers ◽

Cognitive Tasks ◽

Trade Off ◽

Fitts Law ◽

European Languages ◽

Speech Time ◽

Index Of Difficulty ◽

Picture Description ◽

Task Features

We explored the relations between task difficulty and speech time in picture description tasks. Six native speakers of Mandarin Chinese (CH group) and six native speakers or Indo-European languages (IE group) produced quick and accurate verbal descriptions of pictures in a self-paced manner. The pictures always involved two objects, a plate and one of the three objects (a stick, a fork, or a knife) located and oriented differently with respect to the plate in different trials. An index of difficulty was assigned to each picture. CH group showed lower reaction time and much lower speech time. Speech time scaled linearly with the log-transformed index of difficulty in all subjects. The results suggest generality of Fitts’ law for movement and speech tasks, and possibly for other cognitive tasks as well. The differences between the CH and IE groups may be due to specific task features, differences in the grammatical rules of CH and IE languages, and possible use of tone for information transmission.

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LenSelect: Object Selection in Virtual Environments by Dynamic Object Scaling

Frontiers in Virtual Reality ◽

10.3389/frvir.2021.684677 ◽

2021 ◽

Vol 2 ◽

Author(s):

Rene Weller ◽

Waldemar Wegele ◽

Christoph Schröder ◽

Gabriel Zachmann

Keyword(s):

Virtual Environments ◽

User Study ◽

State Of The Art ◽

Selection Process ◽

Main Idea ◽

Object Selection ◽

Fitts Law ◽

Occluded Objects ◽

Index Of Difficulty ◽

Test Scenarios

AbstractWe present a novel selection technique for VR called LenSelect. The main idea is to decrease the Index of Difficulty (ID) according to Fitts’ Law by dynamically increasing the size of the potentially selectable objects. This facilitates the selection process especially in cases of small, distant or partly occluded objects, but also for moving targets. In order to evaluate our method, we have defined a set of test scenarios that covers a broad range of use cases, in contrast to often used simpler scenes. Our test scenarios include practically relevant scenarios with realistic objects but also synthetic scenes, all of which are available for download. We have evaluated our method in a user study and compared the results to two state-of-the-art selection techniques and the standard ray-based selection. Our results show that LenSelect performs similar to the fastest method, which is ray-based selection, while significantly reducing the error rate by 44%.

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