Eye Movement Recordings Research Articles

EOG Region Detection using Fuzzy k-NN for Virtual Reality Applications

Virtual Reality (VR) systems have become widespread for a decade with the mass production of VR headsets. Advancement in the VR industry benefits both biomedical and computer gaming fields to create better Human-Computer Interface (HCI) applications. In this study, Electrooculogram (EOG) signals are studied on a calibrated A4 paper to simulate reading and tracking eye movement in different regions for VR user interface applications. For that reason, eye activity features from EOG are used to identify relative 2D spatial coordinates and classified with the fuzzy k-Nearest Neighbor (fuzzy k-NN) method. Within the experimental setup, different behaviors such as blinking and depth focus change signals are recorded with constant depth regional borders are analyzed on an A4 paper with reading eye movement recordings. In experimental results, fuzzy k-NN classification results are obtained from observed regional eye movement. The study shows that the fuzzy k-NN method to detect regions at a reading distance is feasible for user interface applications in VR. So, by setting rendering focus at the detected regional area, eye strain can be reduced during prolonged VR sessions especially when reading and/or on user interfaces.

Lessons learned from a multimodal sensor-based eHealth approach for treating pediatric obsessive-compulsive disorder.

The present study investigates the feasibility and usability of a sensor-based eHealth treatment in psychotherapy for pediatric obsessive-compulsive disorder (OCD), and explores the promises and pitfalls of this novel approach. With eHealth interventions, therapy can be delivered in a patient's home environment, leading to a more ecologically valid symptom assessment and access to experts even in rural areas. Furthermore, sensors can help indicate a patient's emotional and physical state during treatment. Finally, using sensors during exposure with response prevention (E/RP) can help individualize therapy and prevent avoidance behavior. In this study, we developed and subsequently evaluated a multimodal sensor-based eHealth intervention during 14 video sessions of cognitive-behavioral therapy (CBT) in 20 patients with OCD aged 12-18. During E/RP, we recorded eye movements and gaze direction via eye trackers, and an ECG chest strap captured heart rate (HR) to identify stress responses. Additionally, motion sensors detected approach and avoidance behavior. The results indicate a promising application of sensor-supported therapy for pediatric OCD, such that the technology was well-accepted by the participants, and the therapeutic relationship was successfully established in the context of internet-based treatment. Patients, their parents, and the therapists all showed high levels of satisfaction with this form of therapy and rated the wearable approach in the home environment as helpful, with fewer OCD symptoms perceived at the end of the treatment. The goal of this study was to gain a better understanding of the psychological and physiological processes that occur in pediatric patients during exposure-based online treatment. In addition, 10 key considerations in preparing and conducting sensor-supported CBT for children and adolescents with OCD are explored at the end of the article. This approach has the potential to overcome limitations in eHealth interventions by allowing the real-time transmission of objective data to therapists, once challenges regarding technical support and hardware and software usability are addressed. www.ClinicalTrials.gov, identifier (NCT05291611).

Study of Eye Movements Abnormalities in Epilepsy

ABSTRACT Idiopathic epilepsy (IE), is a group of epileptic syndromes with no structural brain lesion, but with microstructural changes in neuronal networks leading to neuropsychological consequences. Therefore, the assessment of saccadic eye movements can provide insight into the integrity of cerebral networks as it involves large cortical and subcortical brain areas and circuitries. Describe saccadic eye movement abnormalities in patients with IE and correlate them with disease characteristics and antiseizure medication. Case–control study including IE patients followed in the Neurology Department of Razi University Hospital and healthy controls matched. Participants underwent a recording of saccadic eye movements. Pursuit, prosaccade, and anti-saccade tasks were performed. 115 patients and 98 matched healthy controls were included. The gender ratio (male to female) was 0.6. The mean age at onset was 16.3 ± 12 years. Diagnosed epileptic syndromes were juvenile myoclonic epilepsy (JME), epilepsy with generalized tonic-clonic seizures, childhood absence epilepsy, temporal lobe epilepsy, frontal lobe epilepsy, and rolandic epilepsy. Saccadic eye movements were impaired in 52.2% of our patients and significantly more altered in those with JME (p = .021). Prolonged horizontal saccades latencies were the most frequent eye movement abnormalities (32.1%), followed by altered horizontal smooth pursuit (22.6%). A positive correlation was found between age at eye movements recording, age at onset, disease duration, global cognitive impairment, and saccadic eye movements. However, no definite relationship was identified. Saccadic eye movement illustrates extending anatomic alterations in IE including frontal and temporoparietal cortical areas and cortico-subcortical circuits. Eye movement recording is a useful and reproducible tool in the assessment of epileptic patients and provides a better understanding of neuronal mechanisms in epilepsy.

Perceptual inference corrects function word errors in reading: Errors that are not noticed do not disrupt eye movements

Both everyday experience and laboratory research demonstrate that readers often fail to notice errors such as an omitted or repeated function word. This phenomenon challenges central tenets of reading and sentence processing models, according to which each word is lexically processed and incrementally integrated into a syntactic representation. One solution would propose that apparent failure to notice such errors reflects post-perceptual inference; the reader does initially perceive the error, but then unconsciously ’corrects’ the perceived string. Such a post-perceptual account predicts that when readers fail to explicitly notice an error, the error will nevertheless disrupt reading, at least fleetingly. We present a large-scale eyetracking experiment investigating whether disruption is detectable in the eye movement record when readers fail to notice an omitted or repeated two-letter function word in naturalistic sentences. Readers failed to notice both omission and repetition errors over 36% of the time. In an analysis that included all trials, both omission and repetition resulted in pronounced eye movement disruption, compared to reading of grammatical control sentences. But in an analysis including only trials on which readers failed to notice the errors, neither type of error disrupted eye movements on any measure. Indeed, there was evidence in some measures that reading was relatively fast on the trials on which errors were missed. It does not appear that when an error is not consciously noticed, it is initially perceived, and then later corrected; rather, linguistic knowledge influences what the reader perceives.

Efficient diagnostic classification of diverse pathologies through contextual eye movement data analysis with a novel hybrid architecture

The analysis of eye movements has proven valuable for understanding brain function and the neuropathology of various disorders. This research aims to utilize eye movement data analysis as a screening tool for differentiation between eight different groups of pathologies, including scholar, neurologic, and postural disorders. Leveraging a dataset from 20 clinical centers, all employing AIDEAL and REMOBI eye movement technologies this study extends prior research by considering a multi-annotation setting, incorporating information from recordings from saccade and vergence eye movement tests, and using contextual information (e.g. target signals and latency of the eye movement relative to the target and confidence level of the quality of eye movement recording) to improve accuracy while reducing noise interference. Additionally, we introduce a novel hybrid architecture that combines the weight-sharing feature of convolution layers with the long-range capabilities of the transformer architecture to improve model efficiency and reduce the computation cost by a factor of 3.36, while still being competitive in terms of macro F1 score. Evaluated on two diverse datasets, our method demonstrates promising results, the most powerful discrimination being Attention & Neurologic; with a macro F1 score of up to 78.8%; disorder. The results indicate the effectiveness of our approach in classifying eye movement data from different pathologies and different clinical centers accurately, thus enabling the creation of an assistant tool in the future.

About the Possibility of Using Fixation Microsaccades to Improve the Quality of Visible Images in the Foveal Zone

The article is devoted to the description and analysis of a computer model that was created by D. S. Lebedev to demonstrate the possibility of a positive effect of fixation microsaccadic eye movements on the perception of small stimuli. The model is based on the assumption that in the process of fixing the gaze on the test stimulus, several “neural images” of this stimulus, resulting from microsaccades, are summed up in the brain. The series of summed neural images correspond to a sequence of shifted positions of the optical image of a stimulus on the retina. To accurately superimpose neural images on each other, a mechanism for compensating fixation saccadic microshifts is introduced into the model, identical to the mechanism that ensures the constancy of spatial perception in the case of macrosaccades, i.e. when turning the eyes to view large objects or scenes. The author of the model assessed the possibility of improving the quality of visible images by increasing the signal-to-noise ratio, which can be achieved using realistic spatiotemporal parameters of test images, neural noise and eye micromovements, selected bу means of literature analysis. Results of model calculation obtained for the specific parameters of the retina and eye movements showed that the considered summation mechanism with compensation for saccadic shifts can progressively improve the quality of visible test stimuli when the number of summed neural images increases to approximately seven or eight, after which the positive effect practically does not increase. In this article, based on the material of recordings of eye movements in relevant experiments, the degree of realism of this model is discussed.

Visual Attention Distribution of Pilot Flying vs. Pilot Monitoring During Different Flight Phases

With the continuous maturation of technology and the deepening of human-centered design philosophy, eye tracking technology has gradually been applied in research studies for the optimization of flight deck design in commercial aviation. While these studies have focused solely on Pilot Flying (PF), without considering the visual attention distribution of Pilot Monitoring (PM). The purpose of this study was to analyze and compare the visual attention distribution of PF and PM during different flight phases, providing more comprehensive guidance and optimization suggestion to the flight deck design in commercial aviation. This study was conducted in the A320 full-motion flight simulator, with eye tracking technology recording eye movements of PF and PM in the same flight crew simultaneously. The result showed significant differences in three eye movement metrics between PF and PM, not only throughout the whole common manual circuit but also within specific flight phases. Additionally, the results indicated that in certain flight phases, PF and PM exhibited statistically significant correlations in certain eye movement metrics for specific areas of the flight deck. However, in most other instances, no statistically significant correlations were observed between the eye movement metrics of PF and PM. Therefore, the future design of flight decks may benefit from considering differentiation between PF and PM sides in certain flight phases or areas. Additionally, it can be beneficial to make dynamic adjustments to the current flight deck display and control interface while maintaining the existing layout design.

ORASIS-MAE Harnesses the Potential of Self-Learning from Partially Annotated Clinical Eye Movement Records

Self-supervised learning (SSL) has gained significant attention in the past decade for its capacity to utilize non-annotated datasets to learn meaningful data representations. In the medical domain, the challenge of constructing large annotated datasets presents a significant limitation, rendering SSL an ideal approach to address this constraint. In this study, we introduce a novel pretext task tailored to stimulus-driven eye movement data, along with a denoising task to improve the robustness against simulated eye tracking failures. Our proposed task aims to capture both the characteristics of the pilot (brain) and the motor (eye) by learning to reconstruct the eye movement position signal using up to 12.5% of the unmasked eye movement signal patches, along with the entire REMOBI target signal. Thus, the encoder learns a high-dimensional representation using a multivariate time series of length 8192 points, corresponding to approximately 40 s. We evaluate the learned representation on screening eight distinct groups of pathologies, including dyslexia, reading disorder, and attention deficit disorder, across four datasets of varying complexity and size. Furthermore, we explore various head architecture designs along with different transfer learning methods, demonstrating promising results with improvements of up to approximately 15%, leading to an overall macro F1 score of 61% and 61.5% on the Saccade and the Vergence datasets, respectively. Notably, our method achieves macro F1 scores of 64.7%, 66.1%, and 61.1% for screening dyslexia, reading disorder, and attention deficit disorder, respectively, on clinical data. These findings underscore the potential of self-learning algorithms in pathology screening, particularly in domains involving complex data such as stimulus-driven eye movement analysis.

Gaze cueing improves pattern recognition of histology learners.

Experts perceive and evaluate domain-specific visual information with high accuracy. In doing so, they exhibit eye movements referred to as "expert gaze" to rapidly focus on task-relevant areas. Using eye tracking, it is possible to record these implicit gaze patterns and present them to histology novice learners during training. This article presents a comprehensive evaluation of such expert gaze cueing on pattern recognition of medical students in histology. For this purpose, 53 students were randomized into two groups over eight histology sessions. The control group was presented with an instructional histology video featuring voice commentary. The gaze cueing group was presented the same video, but with an additional overlay of a live recording of the expert's eye movements. Afterward, students' pattern recognition was assessed through 20 image-based tasks (5 retention, 15 transfer) and their cognitive load with the Paas scale. Results showed that gaze cueing significantly outperformed the control group (p = 0.007; d = 0.40). This effect was evident for both, retention (p = 0.003) and transfer tasks (p = 0.046), and generalized across different histological contexts. The cognitive load was similar in both groups. In conclusion, gaze cueing helps histology novice learners to develop their pattern recognition skills, offering a promising method for histology education. Histology educators could benefit from this instructional strategy to provide new forms of attentional guidance to learners in visually complex learning environments.

Oculomotor and Vestibular Deficits in Friedreich Ataxia - Systematic Review and Meta-Analysis of Quantitative Measurements.

Disease-specific oculomotor assessments play a crucial role in the early diagnosis of hereditary cerebellar ataxias. Whereas several studies have reported on quantitative oculomotor and vestibular measurements in Friedreich's Ataxia (FRDA), the value of specific oculomotor paradigms remains unclear. We aimed to address this knowledge gap through a systematic literature review and providing disease-specific recommendations for a tailored set of eye-movement recordings in FRDA. MEDLINE and Embase were searched for studies reporting on quantitative oculomotor and/or vestibular measurements in FRDA-patients. Data on oculomotor and vestibular parameters were extracted and correlations with a range of clinical parameters were sought. Included studies (n = 17) reported on 185 patients. Abnormalities observed included the presence of saccadic intrusions (143/161) such as square-wave jerks (SWJ, 90/109) and ocular flutter (21/43), impaired eccentric gaze-holding (40/104), abnormal pursuit (81/93) and angular vestibulo-ocular reflex (aVOR) deficits (39/48). For visually-guided saccades (VGS), we frequently observed increases in saccade latency (27/38) and dysmetric saccades (71/93), whereas saccade velocity was more often preserved (37/43). Augmented anti-saccade (AS) latency, downbeat nystagmus and frequent macro-SWJ correlated with disease duration. Increased AS-latency and VGS-latency, frequent macro-SWJ, reduced aVOR-gain and augmented aVOR peak-latency correlated with disease severity. A broad range of oculomotor and vestibular deficits are documented in the literature. Impairments in pursuit, saccades and aVOR-responses are most commonly reported, and as such, should be prioritized as disease markers. Quantitative oculomotor testing in FRDA may facilitate early diagnosis and prove valuable in monitoring disease progression and treatment response.

Markers of musical expertise in a sight-reading task: An eye-tracking study.

Classical music pianists of five different conservatory levels, from undergraduate to professional, were tested on a sight-reading task with eye-movement recording. They had to sight read both tonal classical scores that followed the rules specific to Western tonal music, and atonal contemporary scores, which do not follow these rules. This study aimed at determining the extent to which eye movements and musical performance metrics can account for the level of sight-reading expertise. First, the results indicated that with the acquisition of expertise, musicians process visual information more rapidly (increasing their played tempo while decreasing average fixation duration and their number of fixations), more structurally (tending to increase their eye-hand span), and more accurately (increasing their sight-reading accuracy). Second, when they sight read contemporary scores compared to classical scores, musicians decreased their played tempo, tended to be less accurate, increased their number of fixations, and tended to decrease their eye-hand span. Finally, expertise effects were moderated by the type of score. These results suggest (a) that visual perception is progressively shaped through music reading expertise and through domain-specific knowledge acquisition, (b) that tonal-specific cues play a significant role to use an efficient eye-movement behavior and (c) that the benefit conferred by expert prior music-specific knowledge seems to be even greater for sight-reading tonal rather than atonal scores. Our findings are discussed in the light of expert memory theories (long-term working memory theory; Ericsson & Kintsch, 1995; template theory, Gobet & Simon, 1996). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The speed and phase of locomotion dictate saccade probability and simultaneous low-frequency power spectra.

Every day we make thousands of saccades and take thousands of steps as we explore our environment. Despite their common co-occurrence in a typical active state, we know little about the coordination between eye movements, walking behaviour and related changes in cortical activity. Technical limitations have been a major impediment, which we overcome here by leveraging the advantages of an immersive wireless virtual reality (VR) environment with three-dimensional (3D) position tracking, together with simultaneous recording of eye movements and mobile electroencephalography (EEG). Using this approach with participants engaged in unencumbered walking along a clear, level path, we find that the likelihood of eye movements at both slow and natural walking speeds entrains to the rhythm of footfall, peaking after the heel-strike of each step. Compared to previous research, this entrainment was captured in a task that did not require visually guided stepping - suggesting a persistent interaction between locomotor and visuomotor functions. Simultaneous EEG recordings reveal a concomitant modulation entrained to heel-strike, with increases and decreases in oscillatory power for a broad range of frequencies. The peak of these effects occurred in the theta and alpha range for slow and natural walking speeds, respectively. Together, our data show that the phase of the step-cycle influences other behaviours such as eye movements, and produces related modulations of simultaneous EEG following the same rhythmic pattern. These results reveal gait as an important factor to be considered when interpreting saccadic and time-frequency EEG data in active observers, and demonstrate that saccadic entrainment to gait may persist throughout everyday activities.

Enhancing Archaeological Teaching Through Eye-Tracking: A Pilot Study on Eye Movement Modelling Examples and Teaching Artefact Analysis

AbstractVisual analysis of artefacts is fundamental to archaeological research. However, learning and teaching the methods of artefact analysis can be challenging, since it is cognitively demanding to observe and explain how visual processing works. This paper addresses this challenge and evaluates eye movement modelling examples, a newly adopted method for teaching visual analysis of artefacts. Educational materials containing recordings of eye movements of experts analysing artefacts have been shown to be beneficial to students. As a consequence, they may boost the accessibility of archaeological knowledge, both for in-class and remote education.

The way we look at an image or a webpage can reveal personality traits

Personality is a central concept and a cross-domain explanatory factor in psychology to characterize and differentiate individuals. Surprisingly, among the many studies on oculomotor behavior, only a few have investigated how personality influences the exploration of a visual stimulus. Due to the limited number of existing studies, it is still uncertain if markers of personality in eye movements are always observable in eye movements across various exploration contexts. Here, introducing a novel concept of gaze-based signatures of personality, we used visual exploration metrics to detect personality signatures across various exploration contexts (visual search and free-viewing on images and webpages) in 91 participants. Personality data were collected as in the reference paper that validated the French version of the Big Five Inventory. Linear regression analyses demonstrated that while Extraversion and Openness to Experience did not correlate with any particular exploration metric, the other three traits–Conscientiousness, Agreeableness, and Neuroticism–correlated robustly with all exploration metrics in different visual exploration contexts. Our study provides evidence for the capture of the gaze-based signature of personality from very brief eye movement recordings.

Triggered saccadic oscillations: case series and review of the literature.

Saccadic oscillations (SOs) mostly occur spontaneously, but can be occasionally triggered by various stimuli. To determine clinical characteristics and underlying mechanisms of triggered SOs, we analyzed the clinical features and quantitative eye-movement recordings of six new patients and 10 patients in the literature who exhibited with triggered SOs. Eleven of the 16 patients (69%) had a lesion involving cerebellum and/or brainstem such as cerebellar degeneration, cerebellitis, or cerebellar infarction. The other causes were vestibular migraine (n = 2), multiple sclerosis (n = 1), Krabbe disease (n = 1), and idiopathic (n = 1). Vestibular stimulation was the most common trigger (n = 11, 69%), followed by removal of visual fixation (n = 4, 25%), hyperventilation (n = 1), light (n = 1), and blink (n = 1). The types of triggered SOs were varied which included ocular flutter (n = 13), opsoclonus (n = 3), vertical SOs (n = 2), and macrosaccadic oscillations (n = 1). Three patients exhibited downbeat nystagmus either before (n = 1) or after (n = 2) the onset of SOs. The frequency of triggered SOs ranged from 4 to 15Hz, and oscillations with smaller amplitudes had higher frequencies and smaller peak velocities. SOs can be triggered by the modulation of unstable saccadic neural networks through vestibular and visual inputs in lesions of the brainstem and cerebellum.

Application of a New Device for Vision Relaxation in Computer Users.

This study aims to explore the potential of a novel EYE ROLL device designed to facilitate guided vision relaxation exercises in an open space. A prospective study was performed on 89 participants who perform screenwork for at least four hours daily. All participants were randomly divided into three groups: a Control group with no exercising, a Manual group undertook manual vision relax ation exercises, and an Eyeroll group engaged in EYE ROLL device-assisted vision relaxation exercises. Each participant underwent three evaluations (an initial baseline assessment, a 4-week follow-up, and an 8-week follow-up) with four assessment tools: a comprehensive vision examination, an in-depth questionnaire, saccadic eye movement recordings, and objective accommodation measurements. There was a statistically significant decrease (35% and above) in complaint scores at the 4-week follow-up in both training groups. Although statistically insignificant, complaints continued to decrease after an 8-week period. No significant changes were observed in clinical or objective accommodative parameters. Some variation of visual functions was observed in all groups due to repeated measures. Vision relaxation exercises combined with proper vision ergonomics and working habits can reduce asthenopic complaints. The EYE ROLL device presents a promising tool for integrating these exercises into the working environment.

Effect of topical brinzolamide on visual function and waveform in patients of infantile nystagmus syndrome: A randomized control trial.

To evaluate the effect of topical carbonic anhydrase inhibitor (brinzolamide) versus placebo on visual function and waveforms in infantile nystagmus syndrome (INS). Prospective, placebo-controlled, double-blind, cross-over study. Setting- A tertiary eye care center. Patients- Cases of idiopathic INS with and without abnormal head posture aged ≥10 years who had not received previous treatment for nystagmus. Intervention- Patients were randomized into two groups. Group 1 was given placebo for 3 months, and after a washout period of 7 days started on topical brinzolamide for the next 3 months. In group 2, the order was reversed. The drops were administered topically three times (every 8 hours) in both eyes. Outcome measure- Binocular best corrected visual acuity (BCVA) using the ETDRS chart, eXpanded nystagmus acuity function (NAFX) score and INS waveforms obtained from eye movement recordings, intraocular pressure (IOP) by Goldmann applanation tonometer, near stereopsis by TNO stereo test, and change in abnormal head posture before and after intervention in the null position. A total of 29 cases completed the study (23 with abnormal head posture; 6 without abnormal head posture). While brinzolamide shows improvement in visual acuity and NAFX score in idiopathic INS, its clinical significance needs further evidence.

Enhancing fall risk assessment: instrumenting vision with deep learning during walks

BackgroundFalls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual’s gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait.MethodThe approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset.ResultsVARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications.ConclusionThe instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common.

Realistic About Reference Production: Testing the Effects of Domain Size and Saturation.

Experiments on visually grounded, definite reference production often manipulate simple visual scenes in the form of grids filled with objects, for example, to test how speakers are affected by the number of objects that are visible. Regarding the latter, it was found that speech onset times increase along with domain size, at least when speakers refer to nonsalient target objects that do not pop out of the visual domain. This finding suggests that even in the case of many distractors, speakers perform object-by-object scans of the visual scene. The current study investigates whether this systematic processing strategy can be explained by the simplified nature of the scenes that were used, and if different strategies can be identified for photo-realistic visual scenes. In doing so, we conducted a preregistered experiment that manipulated domain size and saturation; replicated the measures of speech onset times; and recorded eye movements to measure speakers' viewing strategies more directly. Using controlled photo-realistic scenes, we find (1) that speech onset times increase linearly as more distractors are present; (2) that larger domains elicit relatively fewer fixation switches back and forth between the target and its distractors, mainly before speech onset; and (3) that speakers fixate the target relatively less often in larger domains, mainly after speech onset. We conclude that careful object-by-object scans remain the dominant strategy in our photo-realistic scenes, to a limited extent combined with low-level saliency mechanisms. A relevant direction for future research would be to employ less controlled photo-realistic stimuli that do allow for interpretation based on context.

How Scientists Use Webcams to Track Human Gaze

Eye tracking is a technology that can record people’s eye movements and tell scientists what people look at on screens or out in the world. Scientists use eye tracking to understand what people notice or remember; marketing researchers who create ads use eye tracking to see what type of ads or products capture people’s attention; and video game designers use eye tracking to see what parts of a game are confusing to players, so designers can fix the game. Eye-tracking equipment can be expensive and time consuming for researchers to use, so is there another way to record eye movements without buying an eye tracker? There is! Computer scientists can use a computer-based method called machine learning to turn an everyday webcam into an eye tracker. They can even do this with mobile phones! In this article, you will learn about how eye trackers work and the advantages of disadvantages of using webcams to track eyes.