How body postures affect gaze control in scene viewing under specific task conditions

Gaze movements during visual exploration of natural scenes are typically investigated with the static picture viewing paradigm in the laboratory. While this paradigm is attractive for its highly controlled conditions, limitations in the generalizability of the resulting findings to more natural viewing behavior have been raised frequently. Here, we address the combined influences of body posture and viewing task on gaze behavior with the static picture viewing paradigm under free viewing as a baseline condition. We recorded gaze data using mobile eye tracking during postural manipulations in scene viewing. Specifically, in Experiment 1, we compared gaze behavior during head-supported sitting and quiet standing under two task conditions. We found that task affects temporal and spatial gaze parameters, while posture produces no effects on temporal and small effects on spatial parameters. In Experiment 2, we further investigated body posture by introducing four conditions (sitting with chin rest, head-free sitting, quiet standing, standing on an unstable platform). Again, we found no effects on temporal and small effects on spatial gaze parameters. In our experiments, gaze behavior is largely unaffected by body posture, while task conditions readily produce effects. We conclude that results from static picture viewing may allow predictions of gaze statistics under more natural viewing conditions, however, viewing tasks should be chosen carefully because of their potential effects on gaze characteristics.

Early lifetime experience of urban living predicts social attention in real world crowds

More than half of the world's population is currently living in cities, with more and more people moving to densely populated areas. The experience of growing up and living in crowded environments might influence the way we explore our social environment, mainly how we attend to others. Yet, we know little about how urbanicity affects this vital function of our social life. In two studies, we use mobile eye-tracking to measure participants' social attention, while walking through a shopping mall. Results show that social density of participants' native place impacts how frequently they look at passing strangers. People who experienced more city living from birth to early adolescence, attend more to strangers' faces than their rural counterparts. Our findings demonstrate that the early experience of urban upbringing configures social attention in adulthood. The urbanicity-related bias towards social gazing might reflect a more efficient processing of social information in urban natives.

Navigating through the experienced environment: Insights from mobile eye tracking

Researchers are acutely interested in how people engage in social interactions and navigate their environment. However, in striving for experimental or laboratory control, we often instead present individuals with representations of social and environmental constructs and infer how they would behave in more dynamic and contingent interactions. Mobile eye-tracking (MET) is one approach to connecting the laboratory to the experienced environment. MET superimposes gaze patterns captured through head or eye-glass mounted cameras pointed at the eyes onto a separate camera that captures the visual field. As a result, MET allows researchers to examine the world from the point of view of the individual in action. This review touches on the methods and questions that can be asked with this approach, illustrating how MET can provide new insight into social, behavioral, and cognitive processes from infancy through old age.

Quantitative comparison of a mobile and a stationary video-based eye-tracker

Vision represents the most important sense of primates. To understand visual processing, various different methods are employed—for example, electrophysiology, psychophysics, or eye-tracking. For the latter method, researchers have recently begun to step outside the artificial environments of laboratory setups toward the more natural conditions we usually face in the real world. To get a better understanding of the advantages and limitations of modern mobile eye-trackers, we quantitatively compared one of the most advanced mobile eye-trackers available, the EyeSeeCam, with a commonly used laboratory eye-tracker, the EyeLink II, serving as a gold standard. We aimed to investigate whether or not fully mobile eye-trackers are capable of providing data that would be adequate for direct comparisons with data recorded by stationary eye-trackers. Therefore, we recorded three different, commonly used eye movements—fixations, saccades, and smooth-pursuit eye movements—with both eye-trackers, in successive standardized paradigms in a laboratory setting with eight human subjects. Despite major technical differences between the devices, most eye movement parameters were not statistically different between the two systems. Differences could only be found in overall gaze accuracy and for time-critical parameters such as saccade duration, for which a higher sample frequency is especially useful. Although the stationary EyeLink II system proved to be superior, especially on a single-subject or even a single-trial basis, the ESC showed similar performance for the averaged parameters across both trials and subjects. We concluded that modern mobile eye-trackers are well-suited to providing reliable oculomotor data at the required spatial and temporal resolutions.

Head movement compensation and multi-modal event detection in eye-tracking data for unconstrained head movements

BACKGROUND

The complexity of analyzing eye-tracking signals increases as eye-trackers become more mobile. The signals from a mobile eye-tracker are recorded in relation to the head coordinate system and when the head and body move, the recorded eye-tracking signal is influenced by these movements, which render the subsequent event detection difficult.

NEW METHOD

The purpose of the present paper is to develop a method that performs robust event detection in signals recorded using a mobile eye-tracker. The proposed method performs compensation of head movements recorded using an inertial measurement unit and employs a multi-modal event detection algorithm. The event detection algorithm is based on the head compensated eye-tracking signal combined with information about detected objects extracted from the scene camera of the mobile eye-tracker.

RESULTS

The method is evaluated when participants are seated 2.6m in front of a big screen, and is therefore only valid for distant targets. The proposed method for head compensation decreases the standard deviation during intervals of fixations from 8° to 3.3° for eye-tracking signals recorded during large head movements.

COMPARISON WITH EXISTING METHODS

The multi-modal event detection algorithm outperforms both an existing algorithm (I-VDT) and the built-in-algorithm of the mobile eye-tracker with an average balanced accuracy, calculated over all types of eye movements, of 0.90, compared to 0.85 and 0.75, respectively for the compared algorithms.

CONCLUSIONS

The proposed event detector that combines head movement compensation and information regarding detected objects in the scene video enables for improved classification of events in mobile eye-tracking data.

Accuracy and re-test reliability of mobile eye-tracking in Parkinson's disease and older adults

Mobile eye-tracking is important for understanding the role of vision during real-world tasks in older adults (OA) and people with Parkinson's disease (PD). However, accuracy and reliability of such devices have not been established in these populations. We used a novel protocol to quantify accuracy and reliability of a mobile eye-tracker in OA and PD. A mobile eye-tracker (Dikablis) measured the saccade amplitudes of 20 OA and 14 PD on two occasions. Participants made saccades between targets placed 5°, 10° and 15° apart. Impact of visual correction (glasses) on saccadic amplitude measurement was also investigated in 10 OA. Saccade amplitude accuracy (median bias) was -1.21° but a wide range of bias (-7.73° to 5.81°) was seen in OA and PD, with large vertical saccades (15°) being least accurate. Reliability assessment showed a median difference between sessions of <1° for both groups, with poor to good relative agreement (Spearman rho: 0.14 to 0.85). Greater accuracy and reliability was observed in people without visual correction. Saccade amplitude can be measured with variable accuracy and reliability using a mobile eye-tracker in OA and PD. Human, technological and study-specific protocol factors may introduce error and are discussed along with methodological recommendations.