Recording and analyzing eye-position data using a microcomputer workstation

This paper presents a PC-based eye-position data collection and analysis system. Software routines are described that supplement hardware calibration procedures, improving data-collection accuracy and reducing the number of unusable trials. Collected eye-position data can be remapped over a displayed stimulus image and spatially and temporally represented by parameters such as individual fixations, clusters of fixations (Nodine, Carmody, & Kundel, 1978), cumulative clusters, and gaze durations. An important feature of the system is that the software routines preserve scan-path information that provides a sequential dimension to the analysis of eye-position data. A “hotspot” analysis is also described, which cumulates, across 1 or more observers, the frequency of eye-position landings or “hits” on designated areas of interest for a given stimulus. Experimental applications in the fields of radiology, psychology, and art are provided, illustrating how eye-position data can be interpreted both in signal detection and in information-processing frameworks using the present methods of analysis.

[1]  M. Just,et al.  Eye fixations and cognitive processes , 1976, Cognitive Psychology.

[2]  R. Almond.  The therapeutic community. , 1971, Scientific American.

[3]  H L Kundel,et al.  The influence of prior knowledge on visual search strategies during the viewing of chest radiographs. , 1969, Radiology.

[4]  P. Locher,et al.  SYMMETRY CATCHES THE EYE , 1987 .

[5]  D. Chakraborty,et al.  Free-response methodology: alternate analysis and a new observer-performance experiment. , 1990, Radiology.

[6]  E. Krupinski,et al.  The Role of Formal Art Training on Perception and Aesthetic Judgment of Art Compositions , 2017 .

[7]  H L Kundel,et al.  Searching for lung nodules. A comparison of human performance with random and systematic scanning models. , 1987, Investigative radiology.

[8]  D. Noton,et al.  Eye movements and visual perception. , 1971, Scientific American.

[9]  P. Locher,et al.  The role of scanpaths in the recognition of random shapes , 1974 .

[10]  W. E. Miller,et al.  Lung cancer detected during a screening program using four-month chest radiographs. , 1983, Radiology.

[11]  R. Glaser,et al.  Expertise in a complex skill: Diagnosing x-ray pictures. , 1988 .

[12]  Harold L. Kundel,et al.  Performance of a computer system for recording eye fixations using limbus reflection , 1980 .

[13]  D. Berlyne,et al.  Aesthetics and Psychobiology , 1975 .

[14]  Leonard F. M. Scinto,et al.  An algorithm for determining clusters, pairs or singletons in eye-movement scan-path records , 1986 .

[15]  C. Latimer,et al.  Eye-movement data: Cumulative fixation time and cluster analysis , 1988 .

[16]  E. Krupinski,et al.  Searching for lung nodules. Visual dwell indicates locations of false-positive and false-negative decisions. , 1989, Investigative radiology.

[17]  D. Oakes,et al.  Statistical Methods for Comparative Studies , 1980 .

[18]  E. Krupinski,et al.  Computer-displayed eye position as a visual aid to pulmonary nodule interpretation. , 1990, Investigative radiology.

[19]  H L Kundel,et al.  Visual search patterns and experience with radiological images. , 1972, Radiology.