Eye Movement Behavior Research Articles

Restricted truncal sagittal movements of rapid eye movement behaviour disorder

Unlike sleep-walkers, patients with rapid-eye-movement-behaviour disorder (RBD) rarely leave the bed during the re-enactment of their dreams. RBD movements may be independent of spatial co-ordinates of the ‘outside-world’, and instead rely on (allocentric) brain-generated virtual space-maps, as evident by patients’ limited truncal/axial movements. To confirm this, a semiology analysis of video-polysomnography records of 38 RBD patients was undertaken and paradoxically restricted truncal/thoraco-lumbar movements during complex dream re-enactments demonstrated.

Oculomotor Abnormalities during Reading in the Offspring of Late-Onset Alzheimer's Disease.

Eye movement patterns during reading are well defined and documented. Each eye movement ends up in a fixation point, which allows the brain to process the incoming information and program the following saccade. In this work, we investigated whether eye movement alterations during a reading task might be already present in middle-aged, cognitively normal offspring of late-onset Alzheimer's disease (O-LOAD). 18 O-LOAD and 18 age-matched healthy individuals with no family history of LOAD participated in the study. Participants were seated in front of a 20-inch LCD monitor, and single sentences were presented on it. Eye movements were recorded with an eye tracker with a sampling rate of 1000 Hz. Analysis of eye movements during reading revealed that O-LOAD displayed more fixations, shorter saccades, and shorter fixation durations than controls. The present study shows that O-LOAD experienced alterations in their eye movements during reading. O-LOAD eye movement behavior could be considered an initial sign of oculomotor impairment. Hence, the evaluation of eye movement during reading might be a useful tool for monitoring well-defined cognitive resources.

What Is the Prognostic Significance of Rapid Eye Movement Sleep Without Atonia in a Polysomnogram?

Freud said we are lucky to be paralyzed during sleep, so we cannot act out our dreams. Atonia of skeletal muscles normally present during rapid eye movement sleep prevents us from acting out our dreams. Observing rapid eye movement sleep without atonia in a polysomnogram in older adults first and foremost warrants consideration of rapid eye movement behavior disorder. Seventy-five to 90% of older adults with isolated rapid eye movement behavior disorder will develop a neurodegenerative disease within 15 years, most often a synucleinopathy. Rapid eye movement sleep without atonia in those younger than 50 years is commonly found in individuals with narcolepsy and those taking antidepressant medications.

Detection of Rapid Eye Movement Behaviour Sleep Disorder using Time and Frequency Analysis of EEG Signal Applied on C4-A1 Channels

Article Detection of Rapid Eye Movement Behaviour Sleep Disorder using Time and Frequency Analysis of EEG Signal Applied on C4-A1 Channels was published on February 18, 2022 in the journal Physical Sciences Reviews (volume 0, issue 0).

Stereopsis and Eye Movement Abnormalities in Parkinson's Disease and Their Clinical Implications.

BackgroundParkinson’s disease (PD) is not exclusively a motor disorder. Among non-motor features, patients with PD possess sensory visual dysfunctions. Depth perception and oculomotor deficits can significantly impact patients’ motor performance. Stereopsis and eye behavioral study using 3D stimuli may help determine their implications in disease status.ObjectiveThe objective of this study is to investigate stereopsis and eye movement abnormalities in PD with reliable tools and their correlation with indicators of PD severity. We hypothesize that patients with PD exhibit different eye behaviors and that these differences may correlate to the severity of motor symptoms and cognitive status.MethodsControl and PD participants were first evaluated for visual acuity, visual field, contrast acuity, and stereo perception with 2D and Titmus stereotests, followed by the assessment with a 3D active shutter system. Eye movement behaviors were assessed by a Tobii X2-60 eye tracker.ResultsScreening visual tests did not reveal any differences between the PD and control groups. With the 3D active shutter system, the PD group demonstrated significantly worse stereopsis. The preserved cognitive function was correlated to a more intact stereo function. Patients with PD had longer visual response times, with a higher number of fixations and bigger saccade amplitude, suggesting fixation stabilization difficulties. Such changes showed a positive correlation with the severity of motor symptoms and a negative correlation with normal cognitive status.ConclusionWe assessed stereopsis with a 3D active shutter system and oculomotor behaviors with the Tobii eye tracker. Patients with PD exhibit poorer stereopsis and impaired oculomotor behaviors during response time. These deficits were correlated with PD motor and cognitive status. The visual parameters may potentially serve as the clinical biomarkers for PD.

Visual Fatigue Estimation by Eye Tracker with Regression Analysis

The traditional way to detect visual fatigue is to use the questionnaire or to use critical fusion frequency of high-frequency exchanges due to eye fatigue. The objective of this study was to explore whether eye movement behavior can be used as an objective tool to detect visual fatigue. Thirty-three participants were tested in this study. Their subjective visual fatigue survey, critical fusion frequency, and eye tracker of one minute gaze were measured before and after 20 minutes visual fatigue task. There were significant differences before and after visual fatigue task on survey and eye tracker-derived features. By multiple regression analysis with four eye tracker features, total fixation time duration of the inner circle, longest continuous duration of inner circle viewing time, maximum saccade distance, and focus radius, the regression R square value was greater than 0.9 for all critical fusion frequency data and when subjective visual fatigue assessment was greater than 12 points. In conclusion, eye movement behavior can be used to detect visual fatigue more sensitively even than the traditional critical flicker fusion assessment. Eye tracker can also provide well regression model to fit traditional critical fusion frequency measurement and subjective visual fatigue survey.

Oculomotor and Perceptual Measures of Visual Motion Sensitivity in Patients With Chronic Dizziness Symptoms.

The purpose of this study was to provide empirical data describing the relationship between behavioral responses to dynamic visual motion in adults with chronic dizziness symptoms with and without clinically identifiable peripheral vestibular impairment. Prospective, quasi-experimental study including individuals with chronic dizziness symptoms with identified unilateral peripheral vestibular impairment (n=27), and individuals with chronic dizziness symptoms without identified vestibular impairment (n=26). We measured (a) visual perception of verticality in a dynamic background, (b) postural displacement in a dynamic background, (c) eye movement behaviors in various visual contexts, and (d) self-rating degree of anxiety. Status of peripheral vestibular function was not a significant predictor of behavioral responses to visual motion. The data show that the ability to fixate on a visual target was predictive of postural control in a dynamic visual background. Trial-to-trial variability in verticality responses and degree of self-rated anxiety were also associated with postural control. Apart from vestibular function, oculomotor control is important for maintaining control of whole-body motor responses during exposure to a dynamic visual stimulus. Vertical perception precision-not accuracy-may be more important for understanding real-world consequences of visual motion sensitivity. Traditional diagnostic evaluations focusing exclusively on characterizing the peripheral vestibular system may not provide insight into the behaviors associated with visual motion sensitivity.

Eye Movement Patterns Can Distinguish Schizophrenia From the Major Affective Disorders and Healthy Control Subjects.

Background and hypothesisNo objective tests are currently available to help diagnosis of major psychiatric disorders. This study evaluates the potential of eye movement behavior patterns to predict schizophrenia subjects compared to those with major affective disorders and control groups.Study designEye movements were recorded from a training set of UK subjects with schizophrenia (SCZ; n = 120), bipolar affective disorder (BPAD; n = 141), major depressive disorder (MDD; n = 136), and healthy controls (CON; n = 142), and from a hold-out set of 133 individuals with proportional group sizes. A German cohort of SCZ (n = 60) and a Scottish cohort of CON subjects (n = 184) acted as a second semi-independent test set. All patients met DSMIV and ICD10 criteria for SCZ, BPAD, and MDD. Data from 98 eye movement features were extracted. We employed a gradient boosted (GB) decision tree multiclass classifier to develop a predictive model. We calculated the area under the curve (AUC) as the primary performance metric.Study resultsEstimates of AUC in one-versus-all comparisons were: SCZ (0.85), BPAD (0.78), MDD (0.76), and CON (0.85). Estimates on part-external validation were SCZ (0.89) and CON (0.65). In all cases, there was good specificity but only moderate sensitivity. The best individual discriminators included free viewing, fixation duration, and smooth pursuit tasks. The findings appear robust to potential confounders such as age, sex, medication, or mental state at the time of testing.ConclusionsEye movement patterns can discriminate schizophrenia from major mood disorders and control subjects with around 80% predictive accuracy.

Fixation and Blink Eye Movement Behavior in Dyslexic and Non-Dyslexic English Readers

This study identifies eye movement differences amongst dyslexic and non-dyslexic groups during varying visual reading stimuli. Four ocular metrics are investigated: fixation duration, regression count, blink count and blink duration. In this study, 24 participants were divided into two groups dyslexic (n = 11) and non-dyslexic (n = 13) to read an electronic reading stimulus under different visual typographic conditions. A t-test analysis of each group was conducted for each ocular metric. Significant differences were observed amongst three of the four ocular metrics: fixation duration (p 0.001), regression count (p p p

Memory-driven eye movements prospectively predict dementia in people at risk of Alzheimer's disease.

Oculomotor behaviors linked to cognitive performance revealed neurocognitive features of Alzheimer's disease (AD) that can enhance the accuracy of its assessment and diagnosis. A sample of 107 participants (i.e., 65 mild cognitive impairment [MCI] and 42 controls) were recruited and followed up for 40 months. At baseline, they underwent assessment with the ViewMind digital biomarker, which draws cognitive-related patterns of eye movement while people perform the visual short-term memory binding task. Baseline data predicted that 36 patients with MCI would progress to the AD clinical syndrome (ADS Progressing). The remaining 29 MCI patients were predicted to remain as MCI or progress to other forms of dementia. After 40 months of follow-up, 94% of ADS Progressing patients had received a diagnosis of dementia, whereas none of the non-ADS Progressing had. The analysis of eye movement behavior combined with cognitive markers for AD can effectively predict progression to ADS among patients with MCI.

Research on drivers' hazard perception in plateau environment based on visual characteristics

A good visual search mode is an important prerequisite for a driver to perceive the hazard in the traffic environment timely and accurately. However, hypoxia conditions in the plateau environment might affect drivers' cognitive and judgment ability, posing potential threats to safe driving. This study analyzed the eye movement behaviors of drivers when faced with traffic hazards in the plateau environment, to examine the impact level of altitude on drivers’ perception and reaction. Nine typical traffic hazard scenarios were investigated at four locations with four different altitudes, including Linzhi, Lhasa, Naqu, and Yanghu Scenic Area based on UC-WIN / ROAD driving simulation software. Then, drivers’ visual search modes were analyzed according to drivers’ eye movement data collected by ASL Mobile Eye monocular eye tracker. As the altitude increased, the drivers’ first fixation time and the average saccade amplitude decreased, while the fixation duration percentage increased. Drivers with fewer years of driving experience had a larger percentage of fixation duration and a smaller saccade amplitude. In addition, a shorter acclimation period also negatively influenced the percentage of fixation time. The increase of altitude would weaken the drivers' visual sensitivity and cognitive processing ability of hazard information, which would reduce drivers' hazard perception skills, and the increase of driving experience might help alleviate such negative impacts to some extent. Based on the visual characteristics of traffic hazard scenarios obtained in this paper, the training of highly accident-prone drivers can be guided specifically to improve their visual search strategies, thereby improving driving safety.

Affective Computing for Late-Life Mood and Cognitive Disorders.

Affective computing (also referred to as artificial emotion intelligence or emotion AI) is the study and development of systems and devices that can recognize, interpret, process, and simulate emotion or other affective phenomena. With the rapid growth in the aging population around the world, affective computing has immense potential to benefit the treatment and care of late-life mood and cognitive disorders. For late-life depression, affective computing ranging from vocal biomarkers to facial expressions to social media behavioral analysis can be used to address inadequacies of current screening and diagnostic approaches, mitigate loneliness and isolation, provide more personalized treatment approaches, and detect risk of suicide. Similarly, for Alzheimer's disease, eye movement analysis, vocal biomarkers, and driving and behavior can provide objective biomarkers for early identification and monitoring, allow more comprehensive understanding of daily life and disease fluctuations, and facilitate an understanding of behavioral and psychological symptoms such as agitation. To optimize the utility of affective computing while mitigating potential risks and ensure responsible development, ethical development of affective computing applications for late-life mood and cognitive disorders is needed.

Assessing Deception in Questionnaire Surveys With Eye-Tracking.

Deceit often occurs in questionnaire surveys, which leads to the misreporting of data and poor reliability. The purpose of this study is to explore whether eye-tracking could contribute to the detection of deception in questionnaire surveys, and whether the eye behaviors that appeared in instructed lying still exist in spontaneous lying. Two studies were conducted to explore eye movement behaviors in instructed and spontaneous lying conditions. The results showed that pupil size and fixation behaviors are both reliable indicators to detect lies in questionnaire surveys. Blink and saccade behaviors do not seem to predict deception. Deception resulted in increased pupil size, fixation count and duration. Meanwhile, respondents focused on different areas of the questionnaire when lying versus telling the truth. Furthermore, in the actual deception situation, the linear support vector machine (SVM) deception classifier achieved an accuracy of 74.09%. In sum, this study indicates the eye-tracking signatures of lying are not restricted to instructed deception, demonstrates the potential of using eye-tracking to detect deception in questionnaire surveys, and contributes to the questionnaire surveys of sensitive issues.

A comparison of reading, in people with simulated and actual central vision loss, with static text, horizontally scrolling text, and rapid serial visual presentation.

Reading with central vision loss (CVL), as caused by macular disease, may be enhanced by presenting text using dynamic formats such as horizontally scrolling text or rapid serial visual presentation (RSVP). The rationale for these dynamic text formats is that they can be read while holding gaze away from the text, potentially supporting reading while using the eccentric viewing strategy. This study was designed to evaluate the practice of reading with CVL, with passages of text presented as static sentences, with horizontal scrolling sentences, or as single-word RSVP. In separate studies, normally sighted participants with a simulated (artificial) central scotoma, controlled by an eye-tracker, or participants with CVL resulting from macular degeneration read passages of text using the eccentric viewing technique. Comprehension was better overall with scrolling text when reading with a simulated CVL, whereas RSVP produced lower overall comprehension and high error rates. Analysis of eye movement behavior showed that participants consistently adopted a strategy of making multiple horizontal saccades on the text itself. Adherence to using eccentric viewing was better with RSVP, but this did not translate into better reading performance. Participants with macular degeneration and an actual CVL also showed the highest comprehension and lowest error rates with scrolling text and the lowest comprehension and highest errors with RSVP. We conclude that scrolling text can support effective reading in people with CVL and has potential as a reading aid.

Differences in Sleep Disorders between HIV-Infected Persons and Matched Controls with Sleep Problems: A Matched-Cohort Study Based on Laboratory and Survey Data.

Objectives: Sleep disturbances are prevalent problems among human immunodeficiency virus (HIV)-infected persons. The recognition of comorbid sleep disorders in patients with HIV is currently hampered by limited knowledge of sleep-related symptoms, sleep architecture, and types of sleep disorders in this population. We aimed to compare the differences in sleep-related symptoms and polysomnography-based sleep disorders between HIV-infected persons and controls. Methods: The study evaluated 170 men with a Pittsburgh sleep quality index scores greater than 5, including 44 HIV-infected men and 126 male controls who were frequency-matched by sex, age (±3.0 years) and BMI (±3.0 kg/m2). For all participants, an overnight sleep study using a Somte V1 monitor was conducted. Differences in sleep-related symptoms and sleep disorders between HIV-infected patients and controls were examined using t-tests or chi-square tests. Results: HIV-infected persons with sleep disturbances more often had psychological disturbances (72.7% vs. 40.5%, p < 0.001) and suspected rapid eye movement behavior disorder (25.0% vs. 4.8%, p < 0.01) than controls. Sleep-disordered breathing was less common in HIV-infected persons than in controls (56.8% vs. 87.3%, p < 0.001). The mean percentage of rapid eye movement sleep was higher among HIV-infected patients than among controls (20.6% vs. 16.6%, p < 0.001). Nocturia was more common in HIV-infected persons than in controls (40.9% vs. 22.2%, p = 0.02). Conclusions: Psychological disturbances and sleep-disordered breathing can be possible explanations of sleep disturbances in HIV-infected persons in whom sleep-disordered breathing is notable. Further studies are warranted to examine the underlying factors of rapid eye movement behavior disorder among HIV-infected persons with sleep disturbances.

Emotion detection on webpages using biosensors integrated to a window-based dynamic control system

PurposeDetecting emotion on user experience of web applications and browsing is important in many ways. Web designers and developers find such approach quite useful in enhancing navigational features of webpages, and biomedical personnel regularly use computer simulations to monitor and control the behaviour of patients. On the other hand, law enforcement agents rely on human physiological functions to determine the likelihood of falsehood in interrogations. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users' emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors.Design/methodology/approachThe authors propose a novel method-a window dynamic control system that addresses the foregoing issues. Primary data were obtained from laboratory experiments during which forty-four volunteers had their synchronised physiological readings, skin conductance response (SCR), skin temperature (ST), eye movement behaviour and users’ activity attributes taken using biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronised physiological readings and uses them for two purposes. For both detection of optimal emotional responses and users' stress levels. The method's novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage.FindingsResults show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods.Research limitations/implicationsThe paper is limited to using a window control system to detect emotions on webpages, while integrated to biosensors and eye-tracker.Originality/valueThe originality of the proposed model is its resistance to overfitting and its ability to automatically assess human emotion (stress levels) while dealing with specific web contents. The latter is particularly important in that it can be used to predict which contents of webpages cause stress-induced emotions to users when involved in online activities.

Integration of biosensor to a window-based control system for user emotion detection to static and dynamic visual contents of webpages

Purpose Basic capturing of emotion on user experience of web applications and browsing is important in many ways. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users’ emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors. This paper aims to propose a novel method – a window dynamic control system – that addresses the foregoing issues. Design/methodology/approach Primary data were obtained from laboratory experiments during which 44 volunteers had their synchronized physiological readings – skin conductance response, skin temperature, eye movement behaviour and users activity attributes taken by biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronized physiological readings and uses them for two purposes: for detection of both optimal emotional responses and users’ stress levels. The method’s novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage. Findings The results from the analyses show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison – that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods. Research limitations/implications Graphical simulation and an example scenario are only provided for the control’s system design. Originality/value The novelty of the proposed model is its strained resistance to overfitting and its ability to automatically assess user emotion while dealing with specific web contents. The procedure can be used to predict which contents of webpages cause stress-induced emotions to users.

Emoji Essence: Detecting User Emotional Response on Visual Centre Field with Emoticons

User experience is understood in so many ways, like a one on one interaction (subjective views), online surveys and questionnaires. This is simply so get the user’s implicit response, this paper demonstrates the underlying user emotion on a particular interface such as the webpage visual content based on the context of familiarisation to convey users’ emotion on the interface using emoji, we integrated physiological readings and eye movement behaviour to convey user emotion on the visual centre field of a web interface. The physiological reading is synchronised with the eye tracker to obtain correlating user interaction, and emoticons are used as a form of emotion conveyance on the interface. The eye movement prediction is obtained through a control system’s loop and is represented by different color display of gaze points (GT) that detects a particular user’s emotion on the webpage interface. These are interpreted by the emoticons. Result shows synchronised readings which correlates to area of interests (AOI) of the webpage and user emotion. These are prototypical instances of authentic user response execution for a computer interface and to easily identify user response without user subjective response for better and easy design decisions.

A Bayesian approach to exploring expertise and putting success in adolescent and young adult golfers

ObjectivesPutting behaviour was examined to explore if age influenced performance and the development of motor and perceptual-cognitive expertise during late adolescence and early adulthood. We also examined if motor control and perceptual-cognitive expertise was related to performance on a representative putting task. MethodTwenty elite golfers (15 male; 17–24 years old; mean handicap of 0.5) completed eight straight and eight sloped putts at two distances (8ft/2.44m and 15ft/4.57m), on an indoor golf surface. Participants wore an eye tracker whilst putting and putting performance was assessed via putts holed and eye-movement behaviour, examining Quiet Eye (QE, the duration of the final fixation on the ball). A baseline profile for each participant was created using kinematic stroke data (collected using SAM PuttLab), average putts per round, greens in regulation and current practice hours (subjective self-report measures). ResultsBayesian statistical analysis revealed ‘moderate’ evidence that age and baseline kinematic factors did not influence putting success rates. Eye movement data revealed ‘moderate’ evidence that i) successful performance was associated with less variability in QE duration and ii) extended periods of QE were associated with a decline in performance. Previous experience and current skill level were ruled out as potential confounds. ConclusionOur findings reveal that performance and perceptual-cognitive expertise, did not improve with age. We suggest that post 18 years, age should not be considered a factor in talent development programmes for golf putting. We discuss the benefits of adopting a Bayesian approach and suggest future studies employ longitudinal designs to examine changes in expertise over time.

Gaze Behavior During Navigation and Visual Search of an Open-World Virtual Environment.

Eye tracking has been an essential tool within the vision science community for many years. However, the majority of studies involving eye-tracking technology employ a relatively passive approach through the use of static imagery, prescribed motion, or video stimuli. This is in contrast to our everyday interaction with the natural world where we navigate our environment while actively seeking and using task-relevant visual information. For this reason, an increasing number of vision researchers are employing virtual environment platforms, which offer interactive, realistic visual environments while maintaining a substantial level of experimental control. Here, we recorded eye movement behavior while subjects freely navigated through a rich, open-world virtual environment. Within this environment, subjects completed a visual search task where they were asked to find and count occurrence of specific targets among numerous distractor items. We assigned each participant into one of four target conditions: Humvees, motorcycles, aircraft, or furniture. Our results show a statistically significant relationship between gaze behavior and target objects across Target Conditions with increased visual attention toward assigned targets. Specifically, we see an increase in the number of fixations and an increase in dwell time on target relative to distractor objects. In addition, we included a divided attention task to investigate how search changed with the addition of a secondary task. With increased cognitive load, subjects slowed their speed, decreased gaze on objects, and increased the number of objects scanned in the environment. Overall, our results confirm previous findings and support that complex virtual environments can be used for active visual search experimentation, maintaining a high level of precision in the quantification of gaze information and visual attention. This study contributes to our understanding of how individuals search for information in a naturalistic (open-world) virtual environment. Likewise, our paradigm provides an intriguing look into the heterogeneity of individual behaviors when completing an un-timed visual search task while actively navigating.