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Articles

Measuring dwell time percentage from head-mounted eye-tracking data – comparison of a frame-by-frame and a fixation-by-fixation analysis

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Pages 712-721 | Received 31 Jan 2014, Accepted 13 Nov 2014, Published online: 20 Dec 2014
 

Abstract

Although analysing software for eye-tracking data has significantly improved in the past decades, the analysis of gaze behaviour recorded with head-mounted devices is still challenging and time-consuming. Therefore, new methods have to be tested to reduce the analysis workload while maintaining accuracy and reliability. In this article, dwell time percentages to six areas of interest (AOIs), of six participants cycling on four different roads, were analysed both frame-by-frame and in a ‘fixation-by-fixation’ manner. The fixation-based method is similar to the classic frame-by-frame method but instead of assigning frames, fixations are assigned to one of the AOIs. Although some considerable differences were found between the two methods, a Pearson correlation of 0.930 points out a good validity of the fixation-by-fixation method. For the analysis of gaze behaviour over an extended period of time, the fixation-based approach is a valuable and time-saving alternative for the classic frame-by-frame analysis.

Abstract

Practitioner Summary: A fixation-by-fixation analysis is compared with a frame-by-frame method to analyse dwell time percentage. Although some considerable differences were found between the two methods, a high correlation indicates that the results are very similar. Therefore the fixation-by-fixation method could be a valuable and time-saving alternative for the frame-by-frame analysis.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

Additional information

Funding

We thank Fran Ketels and Ilse Picavet for helping with data collection. This research was funded by the life line campaign of the Research Foundation of Flanders [FWO G.A115.11N].

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