Decision modeling for a target acquisition task

Attentional biases in stressed or overworked radar operators (airborne or in Combat Information Centers, etc.) may have important operational implications. This study examined the effects of workload and non-workload-related stress on salience bias in a screen-based target selection and engagement task. Results in the control condition confirmed that appreciable baseline salience bias existed. Moreover, in the non-task-related stress condition (noise/anxiety), a significant increase in salience bias was observed. Elevated workload, in contrast, was associated with no significant changes in salience bias. Overall, the results showed stable individual differences in salience bias and suggested that non-workload related stress influenced ‘high bias’ individuals proportionately more than ‘low bias’ individuals-an outcome with potential implications for selection. Subjects were also significantly biased toward the left hemispace, a powerful effect that remained even after the experiment was repeated using subjects’ left instead of right hands.

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Development of a Control Theoretic Alternative to Fitts’ Law With Application to In-Vehicle Touchscreen Interface

Volume 9: 2015 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications ◽

10.1115/detc2015-46341 ◽

2015 ◽

Cited By ~ 1

Author(s):

Chao Wang ◽

Bahram Ravani

Keyword(s):

Physical Interpretation ◽

Model Identification ◽

Human Operator ◽

Target Acquisition ◽

Relative Movement ◽

Brief Treatment ◽

Fitts Law ◽

Proposed Model ◽

Acquisition Task

A control theoretic alternative to Fitts’ Law based on a modified crossover model is proposed. A physical interpretation of the model offers the unification of various different formulations of Fitts’ Law. Model identification and validation is carried out for a target acquisition task using a touchscreen. A brief treatment of noise generated by random relative movement between the human operator and the touchscreen (such as in-vehicle touchscreen based devices) is considered using the proposed model.

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Combined 3-D auditory-visual cueing for a visual target acquisition task

10.1117/12.720924 ◽

2007 ◽

Author(s):

Rachael L. Westergren ◽

Paul R. Havig ◽

Eric L. Heft

Keyword(s):

Visual Target ◽

Target Acquisition ◽

Visual Cueing ◽

Acquisition Task

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The effect of myoelectric prosthesis control strategies and feedback level on adaptation rate for a target acquisition task

2017 International Conference on Rehabilitation Robotics (ICORR) ◽

10.1109/icorr.2017.8009246 ◽

2017 ◽

Cited By ~ 11

Author(s):

Ahmed W. Shehata ◽

Erik J. Scheme ◽

Jonathon W. Sensinger

Keyword(s):

Control Strategies ◽

Target Acquisition ◽

Myoelectric Prosthesis ◽

Acquisition Task ◽

Prosthesis Control ◽

Feedback Level

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A Finite-State Description of Coordination in a Two-Handed Target Acquisition Task

IEEE Transactions on Systems Man and Cybernetics ◽

10.1109/tsmc.1982.4308859 ◽

1982 ◽

Vol 12 (4) ◽

pp. 529-538 ◽

Cited By ~ 7

Author(s):

Richard A. Miller ◽

Richard J. Jagacinski ◽

Rajendra B. Nalavade ◽

Walter W. Johnson

Keyword(s):

Target Acquisition ◽

Finite State ◽

Acquisition Task

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Effects of perceptual depth cues on movement time in a target acquisition task

10.31979/etd.p6sh-wnv8 ◽

2003 ◽

Author(s):

Audra J Ruthruff

Keyword(s):

Movement Time ◽

Target Acquisition ◽

Depth Cues ◽

Acquisition Task

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Human Pilot Parameter Identification For A Simulated Air-To-Ground Target Acquisition Task

International Journal of Modelling and Simulation ◽

10.1080/02286203.1985.11759907 ◽

1985 ◽

Vol 5 (2) ◽

pp. 41-46

Author(s):

Pierre Studer

Keyword(s):

Parameter Identification ◽

Target Acquisition ◽

Ground Target ◽

Acquisition Task

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Eye Movements in Search and Target Acquisition

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1518/107118193784162182 ◽

1993 ◽

Vol 37 (19) ◽

pp. 1305-1309

Author(s):

Deborah P. Birkmire ◽

Robert Karsh ◽

B. Diane Barnette ◽

Ramakrishna Pillalamarri ◽

Samantha DiBastiani

Keyword(s):

Eye Movements ◽

Visual Attention ◽

Target Acquisition ◽

Regression Analyses ◽

Video Images ◽

Eye Fixations ◽

Fixation Durations ◽

Acquisition Task ◽

Global And Local ◽

Different Levels

The frequency distribution of eye fixations and fixation durations during a search and target acquisition task was examined to determine if the allocation of visual attention was related to target, scene, and/or observer characteristics. Ninety computer-generated scenes simulating infrared imagery and containing different levels of clutter and zero, one, two, or three targets were produced. Targets were embedded in these scenes counterbalancing for range and position. Global and local clutter were measured using both statistical variance and probability of edge metrics. Thirty-three aviators, tankers, and infantry soldiers were shown still video images of the 90 scenes and were instructed to search for targets. Results of multiple regression analyses of global clutter, local clutter, range, number of targets, target dimensions, target complexity, and group membershi on eye fixations and fixation durations are given and discussed in terms of search strategies.

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