Psychomotor efficiency in users of notebook input devices: Confirmation and restrictions of Fitts' law as an evaluative tool for user-friendly design

2004 ◽  
Author(s):  
Christine Sutter ◽  
Martina Ziefle
Keyword(s):  
Input Devices ◽  
Fitts Law ◽  
Psychomotor Efficiency ◽  
User Friendly

scholarly journals Evaluation of Child–Computer Interaction Using Fitts’ Law: A Comparison between a Standard Computer Mouse and a Head Mouse

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3826
Author(s):  
Cristina Sanchez ◽  
Vanina Costa ◽  
Rodrigo Garcia-Carmona ◽  
Eloy Urendes ◽  
Javier Tejedor ◽  
...  
Keyword(s):  
Motor Control ◽  
Inertial Sensor ◽  
Psychomotor Development ◽  
Fine Motor ◽  
Input Devices ◽  
Fitts Law ◽  
Computer Mouse ◽  
Adults And Children ◽  
Study Participants ◽  
Computer Interaction

This study evaluates and compares the suitability for child–computer interaction (CCI, the branch within human–computer interaction focused on interactive computer systems for children) of two devices: a standard computer mouse and the ENLAZA interface, a head mouse that measures the user’s head posture using an inertial sensor. A multidirectional pointing task was used to assess the motor performance and the users’ ability to learn such a task. The evaluation was based on the interpretation of the metrics derived from Fitts’ law. Ten children aged between 6 and 8 participated in this study. Participants performed a series of pre- and post-training tests for both input devices. After the experiments, data were analyzed and statistically compared. The results show that Fitts’ law can be used to detect changes in the learning process and assess the level of psychomotor development (by comparing the performance of adults and children). In addition, meaningful differences between the fine motor control (hand) and the gross motor control (head) were found by comparing the results of the interaction using the two devices. These findings suggest that Fitts’ law metrics offer a reliable and objective way of measuring the progress of physical training or therapy.

A tool for the rapid evaluation of input devices using Fitts' law models

1993 ◽  
Vol 25 (3) ◽  
pp. 58-63 ◽  
Author(s):  
I. Scott MacKenzie ◽  
William Buxton
Keyword(s):  
Rapid Evaluation ◽  
Input Devices ◽  
Fitts Law

MOUSE AND DISPLAY TABLETS AS CURSOR CONTROL DEVICES

2004 ◽  
Vol 18 (07) ◽  
pp. 1221-1232 ◽  
Author(s):  
ROGER STEVENSON ◽  
JAMES G. PHILLIPS ◽  
TOM J. TRIGGS
Keyword(s):  
User Interfaces ◽  
Relative Efficiency ◽  
Control Device ◽  
Graphical User Interfaces ◽  
Cursor Control ◽  
Fitts Law ◽  
Computer Mouse ◽  
Control Devices ◽  
User Friendly ◽  
Speed And Accuracy

Given the proliferation of touch-sensitive screen technologies, the factors contributing to efficiency of cursor control device were examined to better inform choice and design of Graphical User Interfaces. Fitts' law can be used to describe the relative efficiency of these cursor control devices. Experiment One required 18 participants to move a cursor between targets depicted upon a WACOM PL400 display graphics tablet, over various amplitudes, using a computer mouse or stylus, examining the speed and accuracy of cursor placement. The touch sensitive screen allowed faster acquisition of targets than the mouse. Since the mouse has a higher control/display ratio (gain) than the touch sensitive screen, Experiment Two addressed manipulation of the gain settings on computer mouse performance. Low gain offered some accuracy benefits. Possible posture problems associated with the touch sensitive screen were explored in Experiment Three. Screen orientation had little effect upon cursor positioning performance, suggesting the benefits of the touch sensitive screen can be transferred to user-friendly postures.

A New and Simple Method and Tool for the Evaluation of Input Devices

2002 ◽  
Vol 46 (24) ◽  
pp. 1987-1991
Author(s):  
Detlef Zuehlke ◽  
Lutz Krauss
Keyword(s):  
Software Tool ◽  
Error Rates ◽  
New Method ◽  
Simple Method ◽  
Input Devices ◽  
Fitts Law ◽  
Machine Operators ◽  
Industrial Environments

The known Fitts law model is mainly used in the field of HCI for office applications in order to evaluate interaction devices. This paper presents the new method DEVICE that is also available as free stationary software tool and is applied in the field of HMI for the evaluation of pointing devices. Tests with DEVICE and Fitts' method were conducted with machine operators under industrial environments to determine the suitability of thirty different pointing devices The comparison between DEVICE and Fitts' law model shows, that the results of certain partial tests correlate with each other. DEVICE can be used as substitute for Fitts' law model and offers additional features such as e.g. error rates and pointing deviation. The advantages of DEVICE are shorter test times (only one tenth of the test times required with the Fitts' method), more diverse tests for the test persons, a parameter that can be exactly evaluated by the person who is in charge of the test and the comparability between different studies.

Fitts and VR: Evaluating Display and Input Devices with Fitts' Law

1997 ◽  
Vol 41 (2) ◽  
pp. 1259-1262 ◽  
Author(s):  
Mike McGee ◽  
Brian Amento ◽  
Patrick Brooks ◽  
Hope Harley
Keyword(s):  
Virtual Reality ◽  
Display Type ◽  
Input Device ◽  
Target Acquisition ◽  
Evaluation Tool ◽  
Acquisition Performance ◽  
Input Devices ◽  
Fitts Law ◽  
Starting Point ◽  
Computer Workstation

This paper describes an experiment using Fitts' Law to evaluate performance in target acquisition tasks comparing a typical virtual reality (VR) display and input device with a typical computer workstation display and input device. The objective was to determine the effects of using VR hardware on target acquisition performance and validate Fitts' Law in a VR setting. Participants performed 2D target acquisition tasks varying width of target, distance of target, and angle of target from starting point. Factors that showed significantly different acquisition times included input device, distance from target, width of target, and angle of target from starting point. Display type did not show significance. In addition, acquisition times significantly increased throughout the experiment, indicating fatigue. Extending the use of Fitts' Law as an evaluation tool for VR systems is discussed.

Exploring the Optimal Number of Trials and Participants for Touchpad Testing Using Fitts-based Tasks

2017 ◽  
Vol 61 (1) ◽  
pp. 367-371
Author(s):  
Angie Avera ◽  
Nicholas Kelling ◽  
Christy Harper ◽  
Rick Burks ◽  
Hannah Bowman
Keyword(s):  
Human Factors ◽  
Sample Size ◽  
Optimal Number ◽  
Input Device ◽  
Primary Input ◽  
Optimal Sample Size ◽  
Input Devices ◽  
Fitts Law ◽  
Optimal Sample ◽  
Testing Performance

With touchpads being the primary input device for many laptop users, the importance of ensuring that laptops have the most functional touchpad has continued to grow. Human Factors practitioners are often tasked with ensuring that touchpads are accurate and efficient input devices. Tasks based on Fitts law to assess point and click performance are commonly used for testing touchpads, however there does not seem to be a widely used standard regarding the number of trials and participants. Testing with more trials and participants than necessary can be time consuming and costly for industry practitioners. This research explored varied numbers of participants and Fitts task trials with the goal of determining the optimal practices to maximize efficiency. Preliminary results indicate that when testing performance with a multidirectional Fitts test, twelve participants is acceptable for device comparison with at least 48 trials. For a sample size of 24 participants, there is evidence to support reducing the number of trials to 24. Implications for examining other testing scenarios for optimal sample size and trial number with the prescribed methodology are discussed.

scholarly journals OpenMaze: An Open-Source Toolbox for Creating Virtual Environment Experiments

2020 ◽  
Author(s):  
Kyle Alsbury-Nealy ◽  
Hongyu Wang ◽  
Cody Howarth ◽  
Alex Gordienko ◽  
Margaret Schlichting ◽  
...  
Keyword(s):  
Open Source ◽  
Virtual Environments ◽  
Ecological Validity ◽  
Input Devices ◽  
Wide Range ◽  
Innovative Solution ◽  
3D Environments ◽  
User Friendly ◽  
3D Virtual Environments ◽  
Psychological Experiments

Incorporating 3D virtual environments into psychological experiments offers an innovative solution for balancing experimental control and ecological validity. Their flexible use, however, has been limited to those researchers with extensive coding experience because the field lacks accessible development tools. We created OpenMaze, an open-source toolbox for the Unity game engine, to overcome this barrier. OpenMaze offers researchers the ability to conduct a wide range of 3D spatial navigation experiment paradigms in fully customized 3D environments. Crucially, because all experiment configurations are defined in user-friendly JavaScript Object Notation (JSON) files, our toolbox allows even those with no prior coding experience to build bespoke tasks. OpenMaze is also compatible with a variety of input devices and operating systems, broadening its possible applications. To demonstrate its advantages, we review and contrast other available software options before guiding the reader through building an experiment in OpenMaze.

Predicting the Success of Design Assistive Input Devices for Disabled People

2014 ◽  
Vol 488-489 ◽  
pp. 930-933
Author(s):  
Ching Tien Shih ◽  
Shu Chen Hsu
Keyword(s):  
Success Rate ◽  
Analytical Framework ◽  
Influential Factors ◽  
System Implementation ◽  
Disabled People ◽  
Input Devices ◽  
Preference Relations ◽  
User Friendly

It is important issue to select and design a suitable Assistive Input Devices (AID) for disabled people. This study applies the Incomplete Linguistic Preference Relations (InLinPreRa) analytical framework to predicting the success of design Assistive Input Devices (AID) for disabled people implementation. The results demonstrate that the five most important influential factors are (C6) User-friendly interface (0.166) (C4) Budget (0.163), (C5) Stability of Device (0.159), (C3) easy to maintain (0.144), (C1) easy to operate (0.126). The prediction success rate for AID for disabled people system implementation is 62.7%.

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