Scan path during change-detection visual search

Srikrishnaraja Mahadas, Courtney Semkewyc, Shradha Suresh, George K. Hung

Research output: Contribution to journalArticlepeer-review


When observing a particular image or object, one's perception depends upon prior expectations, memory, and cognitive abilities. It is hypothesized that cognitive processing in the form of top-down or bottom-up processing could be determined via analysis of the eye fixation scan path. To assess the variations in scan paths, 7 subjects underwent 5 change-detection trials. During each trial, they were presented with a specific set of images via a MATLAB program, in which the original image alternated with a modified image consisting of a single change. An open-source program called GazeRecorder was used to track the subject's eye movements and to record the eye fixations. The scan path was then analyzed through the use of a 4 by 4 grid pattern superimposed on the image to determine the subject's eye fixation distribution pattern in terms of Boxes Viewed and Concentration within a single area. It was determined that higher Concentration was positively correlated with faster Detection Speed (R = 0.84), while higher number of Boxes Viewed was negatively correlated with Detection Speed (R = −0.71). Among the subjects, the more optimal scan paths were found in those with a balance between Concentration and Boxes Viewed, as subjects with a more balanced approach had the greatest Accuracy (p = 0.02). This indicates an optimal scan path involves both top-down and bottom-up processing to more efficiently identify a change. Moreover, the methodology developed in this study could be used in the home or clinic for quantitative assessment of improvement following therapy in patients with neurological deficits.

Original languageEnglish (US)
Article number104233
JournalComputers in Biology and Medicine
StatePublished - Apr 2021

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Computer Science Applications


  • Bottom-up
  • Boxes viewed
  • Change detection
  • Concentration
  • Detection speed
  • Eye fixation
  • GazeRecorder
  • Scan path
  • Top-down


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