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MASKING OF MOTION CUES BY RANDOM MOTION: COMPARISON OF HUMAN PERFORMANCE WITH A SIGNAL DETECTION MODEL

Posted on:1988-06-10Degree:Ph.DType:Dissertation
University:University of Toronto (Canada)Candidate:GREIG, GLENN LEWISFull Text:PDF
GTID:1478390017457709Subject:Engineering
Abstract/Summary:
This report describes an investigation of human sensitivity to whole-body motion. Specifically, it discusses the ability of human subjects to detect a sinusoidal motion signal superimposed on a background of random motion. The purpose of the study was to determine the conditions in which motion cues are masked or hidden by concurrent random motion. The results have applications to flight simulation, and will also be of interest to other researchers working in the area of human perceptual performance.; It is proposed that for the situation under study, motion perception is a signal-in-noise detection process which can be modelled using signal detection theory. A brief review of signal detection theory is provided. Three ideal detectors adapted from the literature on auditory perception are proposed as potential models for motion perception.; Three motion perception experiments were run. In the first, a rating procedure was used to obtain receiver operating characteristic (ROC) curves for human subjects detecting sinusoidal motion in a background of low power broadband random motion. A good fit to the data was obtained using ROC curves based on Gaussian distributions of signal and noise. The second experiment used a 2-alternative forced choice task to determine the detectability of sinusoidal motion in a variety of noise conditions. The results show that detectability can be expressed as a function of signal-to-noise ratio, and that sinusoidal motion is masked primarily by noise components which are near the signal frequency. The third experiment tested the extent to which noise on one axis masks a signal on another axis. Inter-axis effects were found to be small, but significant. All three experiments provided an estimate of the slope of the psychometric curve.; Of the three ideal detectors considered, the energy detector agrees best with the experimental data. The data are compared in detail with the predictions of the energy detector. A simplified method for estimating signal detectability in arbitrary conditions is presented. Finally, the implications of the results for flight simulation are discussed.
Keywords/Search Tags:Motion, Signal, Human
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