Redundancy in coding of a visual display as assessed by a signal detection paradigm

1982 ◽  
Author(s):  
Lawrence J. Najjar ◽  
Michael J. Patterson ◽  
Gregory M. Corso
Keyword(s):  
Signal Detection ◽  
Visual Display

A Computer Program Demonstrating the Effect of the Payoff Matrix on the Signal Detection Measure, Beta

1994 ◽  
Vol 21 (2) ◽  
pp. 113-115 ◽  
Author(s):  
Janet D. Larsen
Keyword(s):  
Computer Program ◽  
Signal Detection ◽  
False Alarm ◽  
Response Bias ◽  
Signal Detection Theory ◽  
Visual Display ◽  
Payoff Matrix ◽  
Detection Theory ◽  
Basic Concepts ◽  
Hit Rates

The computer program described in this article demonstrates the basic concepts of signal detection theory and illustrates the effect of changes in the payoff matrix on beta, a measure of response bias. Observers attempt to identify the trials on which there was a signal in a noisy visual display. They earn or lose points for correct or incorrect answers. After three sets of 100 trials, with a different payoff matrix for each set, the program provides observers with their hit rates, false alarm rates, d' scores, and beta scores for the three sets of trials, as well as the total points they have earned for the 300 trials. The program runs on MS-DOS machines and does not require a computer with graphics capabilities.

Redundancy in Coding of a Visual Display as Assessed by a Signal Detection Paradigm

1982 ◽  
Vol 26 (6) ◽  
pp. 586-588 ◽  
Author(s):  
Lawrence J. Najjar ◽  
Michael J. Patterson ◽  
Gregory M. Corso
Keyword(s):  
Visual Search ◽  
Signal Detection ◽  
Performance Measures ◽  
Search Task ◽  
Visual Search Task ◽  
Visual Display ◽  
Black And White ◽  
Objective Performance ◽  
Objective Performance Measures ◽  
Preference Ratings

A signal detection paradigm was applied to performance of a visual search task under varying degrees of shape-color redundant coding and two levels of practice. The coding conditions were (1) Black and White, (2) Totally Nonredundant, (3) Partially Redundant, and (4) Totally Redundant. In addition to the traditional signal detection measures, subjective coding condition preference ratings were also recorded. Generally, the objective performance measures were influenced by practice. However, neither the objective nor the subjective measures were affected by coding conditions. A significant Coding Condition by Practice interaction on the percentage of correct responses was also found.

Detection and Recognition of Multiple Visual Signals in Noise

1989 ◽  
Vol 33 (20) ◽  
pp. 1383-1387 ◽  
Author(s):  
Greg C. Elvers ◽  
Robert D. Sorkin
Keyword(s):  
Signal Detection ◽  
Visual Display ◽  
Detection Theory ◽  
Theory Model ◽  
Visual Signals ◽  
Visual Signal ◽  
Horizontal Line ◽  
Signal Recognition ◽  
Detection Theory Model ◽  
Detection And Recognition

This experiment tested a detection theory model of visual signal detection and recognition. The task employed a visual display consisting of analog gauges arranged in a horizontal line. The signals to be detected and identified were three unique patterns of gauge values embedded in noise. After viewing the display the observers either reported that any of the signals had occurred (1-of-m signal detection) or specified which of the signals (if any) had occurred (1-of-m signal recognition-detection). The results indicated that performance on 1-of-m recognition and detection tasks can be predicted from performance on the component single-signal detection tasks.

The Effects of Visual Displays in Attenuating Discrepancies Between Self-Reported and Physiological Indexes of Stress

2020 ◽  
pp. 1-5
Author(s):  
Jenny J. W. Liu ◽  
Julia Gervasio ◽  
Kenneth Fung ◽  
Kristin Vickers
Keyword(s):  
Social Stress ◽  
Visual Display ◽  
Physiological Measures ◽  
Response Strategies ◽  
Subjective Evaluations ◽  
Stress Task ◽  
Physiological Indexes ◽  
Physiological Outcomes ◽  
Physiological Markers ◽  
The Relationship

Abstract. This study examined whether the relationship between subjective and physiological outcomes of stress, and the responsivity to stressors, are affected by whether participants can see a visual display of their physiological output. Participants were randomly assigned to have a visible view of their physiological output readings, or to a condition in which physiological output readings were out of view. Participants individually completed a 30-min laboratory study including the modified Trier Social Stress Task. Both physiological markers of stress (heart rate and blood pressure) and subjective evaluations of stress (visual analog scale) were measured. Results found little congruency across subjective and physiological measures of stress. The visible visual display condition had elevated physiological arousal, while no group differences were observed in self-reported stress. Findings from the study provide insight into the use of visual physiological displays and hold practical implications for both the measurement of stress in research, and the development of wearable technologies without accompanying response strategies.

Sample Size and the Detection of Correlation--A Signal Detection Account: Comment on Kareev (2000) and Juslin and Olsson (2005).

2005 ◽  
Vol 112 (1) ◽  
pp. 268-279 ◽  
Author(s):  
Richard B. Anderson ◽  
Michael E. Doherty ◽  
Neil D. Berg ◽  
Jeff C. Friedrich
Keyword(s):  
Signal Detection ◽  
Sample Size

So, Whatever Happened to Signal Detection Theory?

1995 ◽  
Vol 40 (10) ◽  
pp. 972-972
Author(s):  
Jerome R. Busemeyer
Keyword(s):  
Signal Detection ◽  
Signal Detection Theory ◽  
Detection Theory

Do logistic regression and signal detection identify different subgroups at risk? Implications for the design of tailored interventions.

2001 ◽  
Vol 6 (1) ◽  
pp. 35-48 ◽  
Author(s):  
Michaela Kiernan ◽  
Helena C. Kraemer ◽  
Marilyn A. Winkleby ◽  
Abby C. King ◽  
C. Barr Taylor
Keyword(s):  
At Risk ◽  
Logistic Regression ◽  
Signal Detection ◽  
Tailored Interventions
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