Discrimination of fixations and smooth pursuit movements in high-speed eye-tracking data

A novel three-stage algorithm for detection of fixations and smooth pursuit movements in high-speed eye-tracking data is proposed. In the first stage, a segmentation based on the directionality of the data is performed. In the second stage, four spatial features are computed from the data in each segment. Finally, data are classified into fixations and smooth pursuit movements based on a combination of the spatial features and the properties of neighboring segments. The algorithm is evaluated under the assumption that the intersaccadic intervals represent fixations in data recorded when viewing images, and mainly smooth pursuit movements in data recorded when viewing moving dots. The results show that the algorithm is able to detect 94.3% of the fixations for image stimuli, compared to a previous algorithm with 80.4% detected fixations. For moving dot stimuli the proposed algorithm detects 86.7% smooth pursuit movements compared to 68.0% for the previous algorithm.

Why have microsaccades become larger? Investigating eye deformations and detection algorithms

The reported size of microsaccades is considerably larger today compared to the initial era of microsaccade studies during the 1950s and 1960s. We investigate whether this increase in size is related to the fact that the eye-trackers of today measure different ocular structures than the older techniques, and that the movements of these structures may differ during a microsaccade. In addition, we explore the impact such differences have on subsequent analyzes of the eye-tracker signals. In Experiment I, the movement of the pupil as well as the first and fourth Purkinje reflections were extracted from series of eye images recorded during a fixation task. Results show that the different ocular structures produce different microsaccade signatures. In Experiment II, we found that microsaccade amplitudes computed with a common detection algorithm were larger compared to those reported by two human experts. The main reason was that the overshoots were not systematically detected by the algorithm and therefore not accurately accounted for. We conclude that one reason to why the reported size of microsaccades has increased is due to the larger overshoots produced by the modern pupil-based eye-trackers compared to the systems used in the classical studies, in combination with the lack of a systematic algorithmic treatment of the overshoot. We hope that awareness of these discrepancies in microsaccade dynamics across eye structures will lead to more generally accepted definitions of microsaccades.