Browsing by Subject "Eye tracking"

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  • Kaakinen, Johanna; Simola, Jaana (2020)
    Thirty-nine participants listened to 28 neutral and horror excerpts of Stephen King short stories while constantly tracking their emotional arousal. Pupil size was measured with an Eyelink 1000+, and participants rated valence and transportation after each story. In addition to computing mean pupil size across 1-sec intervals, we extracted blink count and used detrended fluctuation analysis (DFA) to obtain the scaling exponents of long-range temporal correlations (LRTCs) in pupil size time-series. Pupil size was expected to be sensitive also to emotional arousal, whereas blink count and LRTC’s were expected to reflect cognitive engagement. The results showed that self-reported arousal increased, pupil size was overall greater, and the decreasing slope of pupil size was flatter for horror than for neutral stories. Horror stories induced higher transportation than neutral stories. High transportation was associated with a steeper increase in self-reported arousal across time, stronger LRTCs in pupil size fluctuations, and lower blink count. These results indicate that pupil size reflects emotional arousal induced by the text content, while LRTCs and blink count are sensitive to cognitive engagement associated with transportation, irrespective of the text type. The study demonstrates the utility of pupillometric measures and blink count to study literature reception.
  • Puurtinen, Marjaana; Hoppu, Ulla; Puputti, Sari; Mattila, Saila; Sandell, Mari (2021)
    Mobile eye tracking (MET) enables the recording of gaze data in less-controlled research environments, but best practices for its use in studies about visual attention to foods are yet undetermined. This study supports the building of a coherent framework for this methodological approach by discussing current eye-tracking trends in the field, applying MET in an experiment with real foods, and proposing methodological approaches for future studies. In the experiment, 32 female participants' gaze data were recorded while they inspected a salad buffet for 20 s and then assembled a self-choice salad. The functionality of fixation, scanpath, and pupil size measures was investigated, focusing on associations between eye movements and food item color and position, eye movements and food item preference, and pupil size and selected measures. Dish placement affected the relative amount of visits to a single food item, whereas food item color and preference were not associated with the examined measures. The pupil-size measure did not function with the elderly participants. Importantly, a simple cluster analysis, based on a scanpath and a food selection measure, helped to illustrate different profiles of food view and selection. It was determined that food item position should be carefully considered in MET studies involving real foods, and scanpath measures could be useful in bringing forth behavioral differences that are not revealed by fixation parameters alone. Importantly, identifying "attention-action" profiles by combining eyetracking and other measures seems to be a fruitful way of approaching individual differences in food viewing and selection.
  • Lappi, Otto; Rinkkala, Paavo; Pekkanen, Jami (2017)
    In this paper we present and qualitatively analyze an expert driver’s gaze behavior in natural driving on a real road, with no specific experimental task or instruction. Previous eye tracking research on naturalistic tasks has revealed recurring patterns of gaze behavior that are surprisingly regular and repeatable. Lappi (2016) identified in the literature seven “qualitative laws of gaze behavior in the wild”: recurring patterns that tend to go together, the more so the more naturalistic the setting, all of them expected in extended sequences of fully naturalistic behavior. However, no study to date has observed all in a single experiment. Here, we wanted to do just that: present observations supporting all the “laws” in a single behavioral sequence by a single subject. We discuss the laws in terms of unresolved issues in driver modeling and open challenges for experimental and theoretical development.