Do you see what I see? Mobile eye-tracker contextual analysis and inter-rater reliability

Sam Stuart*, D. Hunt, J. Nell, Alan Godfrey, J. M. Hausdorff, L. Rochester, L. Alcock

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
9 Downloads (Pure)

Abstract

Mobile eye-trackers are currently used during real-world tasks (e.g. gait) to monitor visual and cognitive processes, particularly in ageing and Parkinson’s disease (PD). However, contextual analysis involving fixation locations during such tasks is rarely performed due to its complexity. This study adapted a validated algorithm and developed a classification method to semi-automate contextual analysis of mobile eye-tracking data. We further assessed inter-rater reliability of the proposed classification method. A mobile eye-tracker recorded eye-movements during walking in five healthy older adult controls (HC) and five people with PD. Fixations were identified using a previously validated algorithm, which was adapted to provide still images of fixation locations (n = 116). The fixation location was manually identified by two raters (DH, JN), who classified the locations. Cohen’s kappa correlation coefficients determined the inter-rater reliability. The algorithm successfully provided still images for each fixation, allowing manual contextual analysis to be performed. The inter-rater reliability for classifying the fixation location was high for both PD (kappa = 0.80, 95% agreement) and HC groups (kappa = 0.80, 91% agreement), which indicated a reliable classification method. This study developed a reliable semi-automated contextual analysis method for gait studies in HC and PD. Future studies could adapt this methodology for various gait-related eye-tracking studies.

Original languageEnglish
Pages (from-to)289-296
Number of pages8
JournalMedical and Biological Engineering and Computing
Volume56
Issue number2
Early online date15 Jul 2017
DOIs
Publication statusPublished - 1 Feb 2018

Fingerprint

Dive into the research topics of 'Do you see what I see? Mobile eye-tracker contextual analysis and inter-rater reliability'. Together they form a unique fingerprint.

Cite this