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

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.