Eye movement characteristics reflected fatigue development in both young and elderly individuals

EM-COGLOAD: An investigation into age and cognitive load detection using eye tracking and deep learning

Alzheimer's Disease is the most prevalent neurodegenerative disease, and is a leading cause of disability among the elderly. Eye movement behaviour demonstrates potential as a non-invasive biomarker for Alzheimer's Disease, with changes detectable at an early stage after initial onset. This paper introduces a new publicly available dataset: EM-COGLOAD (available at https://osf.io/zjtdq/, DOI: 10.17605/OSF.IO/ZJTDQ). A dual-task paradigm was used to create effects of declined cognitive performance in 75 healthy adults as they carried out visual tracking tasks. Their eye movement was recorded, and time series classification of the extracted eye movement traces was explored using a range of deep learning techniques. The results of this showed that convolutional neural networks were able to achieve an accuracy of 87.5% when distinguishing between eye movement under low and high cognitive load, and 76% when distinguishing between the oldest and youngest age groups.

Evidence for five types of fixation during a random saccade eye tracking task and changes in fixation duration as a function of time-on-task

Our interest was to evaluate changes in fixation duration as a function of time-on-task (TOT) during a random saccade task. We employed a large, publicly available dataset. The frequency histogram of fixation durations was multimodal and modelled as a Gaussian mixture. For this specific task, we found five fixation types. The "ideal" response would be a single accurate saccade after each target movement, with a typical saccade latency of 200-250 msec, followed by a long fixation (> 800 msec) until the next target jump. We found fixations like this, but they comprised only 10% of all fixations and were the first fixation after target movement only 23.4% of the time. More frequently (57.4% of the time), the first fixation after target movement was short (117.7 msec mean) and was commonly followed by a corrective saccade. Across the entire 100 sec of the task, median total fixation duration decreased. This decrease was approximated with a power law fit with R2 = 0.94. A detailed examination of the frequency of each of our five fixation types over time on task (TOT) revealed that the three shortest duration fixation types became more and more frequent with TOT whereas the two longest fixations became less and less frequent. In all cases, the changes over TOT followed power law relationships, with R2 values between 0.73 and 0.93. We concluded that, over the 100 second duration of our task, long fixations are common in the first 15 to 22 seconds but become less common after that. Short fixations are relatively uncommon in the first 15 to 22 seconds but become more and more common as the task progressed. Apparently. the ability to produce an ideal response, although somewhat likely in the first 22 seconds, rapidly declines. This might be related to a noted decline in saccade accuracy over time.

Gaze behavior in open-angle glaucoma patients during visuo-cognitive-motor tasks: a cross-sectional study

This study investigated gaze behavior during visuo-cognitive-motor tasks with a change of movement direction in glaucoma patients and healthy controls. Nineteen glaucoma patients (10 females, 9 males) and 30 healthy sighted controls (17 females, 13 males) participated in this cross-sectional study. Participants performed two visuo-cognitive-motor tasks with a change of movement direction: (i) the "Speed-Court-Test" that involved stepping on different sensors in response to a visual sign displayed on either a large or small screen (165″ and 55″, respectively); (ii) the "Trail-Walking-Test" that required walking to 15 cones labeled with numbers (1-8) or letters (A-G) in an alternately ascending order. During these tasks, the time needed for completing each task was determined and the gaze behavior (e.g., saccade duration, fixation duration) was recorded via eye tracking. Data were analyzed with repeated measures analyses of covariance (ANCOVA; GROUP × SCREEN) and one-way ANCOVA. No differences between groups were found for the time needed to complete the tasks. However, during the "Trail-Walking-Test", the fixation duration was longer for glaucoma patients than for controls (p = 0.016, η p 2  = 0.131). Furthermore, during the "Speed-Court-Test", there was a screen size effect. Irrespective of group, saccade amplitudes were lower (p < 0.001, η p 2  = 0.242) and fixation durations were higher (p = 0.021, η p 2  = 0.125) for the small screen. Fixation durations were longer in glaucoma patients during the cognitively demanding "Trail-Walking-Test", which might indicate a strategy to compensate for their visual impairment.

OculoMotor & Vestibular Endurance Screening (MoVES) Normative, Repeatability, and Reliability Data

This study aims to assess oculomotor and vestibular endurance by utilizing the Oculomotor and Vestibular Endurance Screening (MoVES) assessment in athletes' pre-season and post-season and after a suspected head injury to detect impairment. Athletes (N = 311, 19.4 ± 1.3 years) were recruited to perform the following seven tasks: (1) horizontal saccades, (2) vertical saccades, (3) vergence jumps, (4) horizontal vestibular-oculomotor reflex (VOR), (5) vertical VOR, (6) amplitude of accommodation (AoA), and (7) near point of convergence (NPC). At pre-season, the observed number of eye movements in 60 s are horizontal saccades (74 ± 13 initial 30 s; 67 ± 11 latter 30 s), vertical saccades (70 ± 13; 66 ± 10), vergence jumps (48 ± 12; 45 ± 13), horizontal VOR (38 ± 11; 38 ± 11), and vertical VOR (8 ± 11; 38 ± 11). These results establish a normative database for eye movements within the MoVES assessment and show consistency in the number of movements from pre-season to post-season. The initial results show a trending decrease in the number of eye movements in the initial days post-head injury, which improves to pre-season measures 14-21 days post-injury. This foundation can be used by future studies to explore the extent of binocular and vestibular endurance dysfunctions caused by head injuries that subside within two weeks.

Non-invasive detection of mental fatigue in construction equipment operators through geometric measurements of facial features

INTRODUCTION

Prolonged operation of construction equipment could lead to mental fatigue, which can increase the chances of human error-related accidents as well as operators' ill-health. The objective detection of operators' mental fatigue is crucial for reducing accident risk and ensuring operator health. Electroencephalography, photoplethysmography, electrodermal activity, and eye-tracking technology have been used to mitigate this issue. These technologies are invasive and wearable sensors that can cause irritation and discomfort. Geometric measurements of facial features can serve as a noninvasive alternative approach. Its application in detecting mental fatigue of construction equipment operators has not been reported in the literature. Although the application of facial features has been widespread in other domains, such as drivers and other occupation scenarios, their ecological validity for construction excavator operators remains a knowledge gap.

METHOD

This study proposed employing geometric measurements of facial features to detect mental fatigue in construction equipment operators' facial features. In this study, seventeen operators performed excavation operations. Mental fatigue was labeled subjectively and objectively using NASA-TLX scores and EDA values. Based on geometric measurements, facial features (eyebrow, mouth outer, mouth corners, head motion, eye area, and face area) were extracted.

RESULTS

The results showed that there was significant difference in the measured metrics for high fatigue compared to low fatigue. Specifically, the most noteworthy variation was for the eye and face area metrics, with mean differences of 45.88% and 26.9%, respectively.

CONCLUSIONS

The findings showed that geometrical measurements of facial features are a useful, noninvasive approach for detecting the mental fatigue of construction equipment operators.

High-Frequency Discrete-Interval Binary Sequence in Asynchronous C-VEP-Based BCI for Visual Fatigue Reduction

In code-modulated visual evoked potential (c-VEP) based BCI systems, flickering visual stimuli may result in visual fatigue. Thus, we introduced a discrete-interval binary sequence (DIBS) as visual stimulus modulation, with its power spectrum optimized to emphasize high-frequency components (40 Hz-60 Hz). 8 and 17 subjects participated, respectively, in offline and online experiments on a 4-target asynchronous c-VEP-based BCI system designed to realize a high positive predictive value (PPV), a low false positive rate (FPR) during idle states, and a high true positive rate (TPR) in control states, while minimizing visual fatigue level. Two visual stimuli modulations were introduced and compared: a maximum length sequence (m-sequence) and the high-frequency discrete-interval binary sequence (DIBS). The decoding algorithm was compared among the canonical correlation analysis (CCA), the task-related component analysis (TRCA), and two approaches of sub-band component weight calculation (the traditional method and the proportional method) for FBCCA and FBTRCA. In the online experiments, the average PPV, FPR and TPR achieved, respectively [Formula: see text], [Formula: see text], [Formula: see text] with m-sequence, while [Formula: see text], [Formula: see text] and [Formula: see text] with DIBS. Estimated by objective eye-related metrics and a subjective questionnaire, the visual fatigue in DIBS cases is significantly smaller than that in m-sequence cases. In this study, the feasibility of a novel modulation approach for visual fatigue reduction was proved in an asynchronous c-VEP system, while maintaining comparable performance to existing methods, which provides further insights towards enhancing this field's long-term viability and user-friendliness.

Understanding mental fatigue and its detection: a comparative analysis of assessments and tools

Mental fatigue has shown to be one of the root causes of decreased productivity and overall cognitive performance, by decreasing an individual's ability to inhibit responses, process information and concentrate. The effects of mental fatigue have led to occupational errors and motorway accidents. Early detection of mental fatigue can prevent the escalation of symptoms that may lead to chronic fatigue syndrome and other disorders. To date, in clinical settings, the assessment of mental fatigue and stress is done through self-reported questionnaires. The validity of these questionnaires is questionable, as they are highly subjective measurement tools and are not immune to response biases. This review examines the wider presence of mental fatigue in the general population and critically compares its various detection techniques (i.e., self-reporting questionnaires, heart rate variability, salivary cortisol levels, electroencephalogram, and saccadic eye movements). The ability of these detection tools to assess inhibition responses (which are sensitive enough to be manifested in a fatigue state) is specifically evaluated for a reliable marker in identifying mentally fatigued individuals. In laboratory settings, antisaccade tasks have been long used to assess inhibitory control and this technique can potentially serve as the most promising assessment tool to objectively detect mental fatigue. However, more studies need to be conducted in the future to validate and correlate this assessment with other existing measures of mental fatigue detection. This review is intended for, but not limited to, mental health professionals, digital health scientists, vision researchers, and behavioral scientists.

Fatigue Assessment from Facial Videos using Deep Neural Networks and Engineered Features Informed by Domain Knowledge

Fatigue impairs cognitive and motor function, potentially leading to mishaps in high-pressure occupations such as aviation and emergency medical services. The current approach is primarily based on self-assessment, which is subjective and error-prone. An objective method is needed to detect severe and likely dangerous levels of fatigue quickly and accurately. Here, we present a quantitative evaluation tool that uses less than two minutes of facial video, captured using an iPad, to assess fatigue vs. alertness. The tool is fast, easy to use, and scalable since it uses cameras readily available on consumer-electronic devices. We compared the classification performance between a Long Short-Term Memory (LSTM) deep neural network and a Random Forest (RF) classifier applied to engineered features informed by domain knowledge. The preliminary results on an 11-subject dataset show that RF outperforms LSTM, with added interpretability on the features used. For the RF classifiers, the average areas under the receiver operating characteristic curve, based on the 11-fold and individualized 11-fold cross validations, are 0.72 ± 0.16 and 0.8 ± 0.12, respectively. Equal error rates are 0.34 and 0.26, respectively. This study presents a promising approach for rapid fatigue detection. Additional data will be collected to assess the generalizability across populations.

Fatigue and Human Performance: An Updated Framework

Fatigue has been defined differently in the literature depending on the field of research. The inconsistent use of the term fatigue complicated scientific communication, thereby limiting progress towards a more in-depth understanding of the phenomenon. Therefore, Enoka and Duchateau (Med Sci Sports Exerc 48:2228-38, 2016, [3]) proposed a fatigue framework that distinguishes between trait fatigue (i.e., fatigue experienced by an individual over a longer period of time) and motor or cognitive task-induced state fatigue (i.e., self-reported disabling symptom derived from the two interdependent attributes performance fatigability and perceived fatigability). Thereby, performance fatigability describes a decrease in an objective performance measure, while perceived fatigability refers to the sensations that regulate the integrity of the performer. Although this framework served as a good starting point to unravel the psychophysiology of fatigue, several important aspects were not included and the interdependence of the mechanisms driving performance fatigability and perceived fatigability were not comprehensively discussed. Therefore, the present narrative review aimed to (1) update the fatigue framework suggested by Enoka and Duchateau (Med Sci Sports Exerc 48:2228-38, 2016, [3]) pertaining the taxonomy (i.e., cognitive performance fatigue and perceived cognitive fatigue were added) and important determinants that were not considered previously (e.g., effort perception, affective valence, self-regulation), (2) discuss the mechanisms underlying performance fatigue and perceived fatigue in response to motor and cognitive tasks as well as their interdependence, and (3) provide recommendations for future research on these interactions. We propose to define motor or cognitive task-induced state fatigue as a psychophysiological condition characterized by a decrease in motor or cognitive performance (i.e., motor or cognitive performance fatigue, respectively) and/or an increased perception of fatigue (i.e., perceived motor or cognitive fatigue). These dimensions are interdependent, hinge on different determinants, and depend on body homeostasis (e.g., wakefulness, core temperature) as well as several modulating factors (e.g., age, sex, diseases, characteristics of the motor or cognitive task). Consequently, there is no single factor primarily determining performance fatigue and perceived fatigue in response to motor or cognitive tasks. Instead, the relative weight of each determinant and their interaction are modulated by several factors.

Correlation between Eye Movements and Asthenopia: A Prospective Observational Study

Purpose: To analyze the correlation between eye movements and asthenopia so as to explore the possibility of using eye-tracking techniques for objective assessment of asthenopia. Methods: This prospective observational study used the computer visual syndrome questionnaire to assess the severity of asthenopia in 93 enrolled college students (age 20−30) who complained about asthenopia. Binocular accommodation and eye movements during the reading task were also examined. The correlations between questionnaire score and accommodation examination results and eye movement parameters were analyzed. Differences in eye movement parameters between the first and last reading paragraphs were compared. The trends in eye movement changes over time were observed. Results: About 81.7% of the subjects suffered from computer visual syndrome. Computer visual syndrome questionnaire total score was positively correlated with positive relative accommodation (p < 0.05). In the first reading paragraph, double vision was positively correlated with unknown saccades (all p < 0.05). Difficulty focusing at close range was positively correlated with total fixation duration, total visit duration, and reading speed (all p < 0.05). Feeling that sight was worsening was positively correlated with regressive saccades (p < 0.05). However, visual impairment symptoms were not significantly correlated with any accommodative function. In a total 20 min reading, significantly reduced eye movement parameters were: total fixation duration, fixation count, total visit duration, visit count, fixation duration mean, and reading speed (all p < 0.01). The eye movement parameters that were significantly increased were: visit duration mean and unknown saccades (all p < 0.001). Conclusion: Eye tracking could be used as an effective assessment for asthenopia. Among the various eye movement parameters, a decrease in fixation duration and counts may be one of the potential indicators related to asthenopia.

360-Degree Video Bandwidth Reduction: Technique and Approaches Comprehensive Review

Recently, the usage of 360-degree videos has prevailed in various sectors such as education, real estate, medical, entertainment and more. The development of the Virtual World “Metaverse” demanded a Virtual Reality (VR) environment with high immersion and a smooth user experience. However, various challenges are faced to provide real-time streaming due to the nature of high-resolution 360-degree videos such as high bandwidth requirement, high computing power and low delay tolerance. To overcome these challenges, streaming methods such as Dynamic Adaptive Streaming over HTTP (DASH), Tiling, Viewport-Adaptive and Machine Learning (ML) are discussed. Moreover, the superiorities of the development of 5G and 6G networks, Mobile Edge Computing (MEC) and Caching and the Information-Centric Network (ICN) approaches to optimize the 360-degree video streaming are elaborated. All of these methods strike to improve the Quality of Experience (QoE) and Quality of Service (QoS) of VR services. Next, the challenges faced in QoE modeling and the existing objective and subjective QoE assessment methods of 360-degree video are presented. Lastly, potential future research that utilizes and further improves the existing methods substantially is discussed. With the efforts of various research studies and industries and the gradual development of the network in recent years, a deep fake virtual world, “Metaverse” with high immersion and conducive for daily life working, learning and socializing are around the corner.

Fatigue and Arousal Modulations Revealed by Saccade and Pupil Dynamics

Saccadic eye movements are directed to the objects of interests and enable high-resolution visual images in the exploration of the visual world. There is a trial-to-trial variation in saccade dynamics even in a simple task, possibly attributed to arousal fluctuations. Previous studies have showed that an increase of fatigue level over time, also known as time-on-task, can be revealed by saccade peak velocity. In addition, pupil size, controlled by the autonomic nervous system, has long been used as an arousal index. However, limited research has been done with regards to the relation between pupil size and saccade behavior in the context of trial-to-trial variation. To investigate fatigue and arousal effects on saccadic and pupillary responses, we used bright and emotional stimuli to evoke pupillary responses in tasks requiring reactive and voluntary saccade generation. Decreased voluntary saccade peak velocities, reduced tonic pupil size and phasic pupillary responses were observed as time-on-task increased. Moreover, tonic pupil size affected saccade latency and dynamics, with steeper saccade main sequence slope as tonic pupil size increased. In summary, saccade dynamics and tonic pupil size were sensitive to fatigue and arousal level, together providing valuable information for the understanding of human behavior.

Blink duration is increased in concussed youth athletes: a validity study using eye tracking in male youth and adult athletes of selected contact sports

OBJECTIVE

Diagnosing a sports-related concussion (SRC) remains challenging, and research into diagnostic tools is limited. This study investigated whether selected eye tracking variables would be a valid tool to diagnose and monitor SRC in adult and youth participants in selected contact sports, such as Rugby Union (rugby) and football (soccer).

METHODS

This prospective cohort study, with 70 concussed and 92 non-concussed adult and youth athletes, assessed the validity of five previously selected eye tracking variables for SRC diagnostics and management. The performance between concussed and age-matched control (non-concussed) athletes, as well as between three successive testing sessions in the concussed athletes were compared. Self-paced saccade count in adult group; blink duration in the memory-guided saccade and sinusoidal smooth pursuit tasks, proportion of antisaccade errors, and gain of diagonal smooth pursuit in the youth group were assessed.

RESULTS

The youth concussed group had higher blink duration in the fast memory-guided saccades task (p = 0.001, η2 = 0.17) and a tendency for higher blink duration in the sinusoidal smooth pursuit task (p = 0.016, η2 = 0.06) compared to the youth control group. In both tasks the blink duration in the concussed youth group decreased from session 1 to session 2 by 24% and 18%, accordingly, although statistical significance was not reached. The concussed adult group demonstrated a lower number of self-paced saccades compared to controls (p = 0.05, η2 = 0.09), which gradually increased, with the largest difference between session 1 and session 3 (p = 0.02).

CONCLUSIONS

Blink duration in youth athletes holds promise as a valid metric for concussion diagnostics and monitoring. It is recommended to focus future studies on comparing eye tracking performance within the same concussed athletes over time rather than comparing them to healthy controls.

Relationship between Eye Blink Frequency and Incremental Exercise among Young Healthy Men

The aim of the study was to verify the correlation between the frequency of blinking and aerobic physical exercise. The research subjects were 13 healthy man aged 23.3 ± 1 year. Measurements of the blink rate and eye closure times were performed during a progressive aerobic test on a cycle ergometer. During the test, power was gradually increased every minute by 25 W, starting from 50 W. Data acquisition involved using a GoPro camera mounted to the helmet of the research subject. The test continued until the research subject refused to continue. The subjects did not know the goal of the test, in order to ensure objectivity and obtain natural results. The largest number of statistically significant differences was observed between the initial stages and 250 W, as well as between 250 W and 325 W. The analysis showed no significant differences in blink rate, eye closure time, and single blink time in terms of heart rate ranges. Regression models were also determined for eye closure time, blink frequency, and single blink time. The analysis showed that blink frequency and eye closure time were determined by a group of factors (the value of cycle ergometer load power, heart rate, body weight, adipose tissue mass, fat-free mass, and total body water and body surface ratio).

Eye-Tracker Study of Influence of Affective Disruptive Content on User's Visual Attention and Emotional State

When reading interesting content or searching for information on a website, the appearance of a pop-up advertisement in the middle of the screen is perceived as irritating by a recipient. Interrupted cognitive processes are considered unwanted by the user but desired by advertising providers. Diverting visual attention away from the main content is intended to focus the user on the appeared disruptive content. Is the attempt to reach the user by any means justified? In this study, we examined the impact of pop-up emotional content on user reactions. For this purpose, a cognitive experiment was designed where a text-reading task was interrupted by two types of affective pictures: positive and negative ones. To measure the changes in user reactions, an eye-tracker (for analysis of eye movements and changes in gaze points) and an iMotion Platform (for analysis of face muscles' movements) were used. The results confirm the impact of the type of emotional content on users' reactions during cognitive process interruptions and indicate that the negative impact of cognitive process interruptions on the user can be reduced. The negative content evoked lower cognitive load, narrower visual attention, and lower irritation compared to positive content. These results offer insight on how to provide more efficient Internet advertising.

Detecting Soldiers' Fatigue Using Eye-Tracking Glasses: Practical Field Applications and Research Opportunities

INTRODUCTION

Objectively determining soldiers' fatigue levels could help prevent injuries or accidents resulting from inattention or decreased alertness. Eye-tracking technologies, such as optical eye tracking (OET) and electrooculography (EOG), are often used to monitor fatigue. Eyeblinks-especially blink frequency and blink duration-are known as easily observable and valid biomarkers of fatigue. Currently, various eye trackers (i.e., eye-tracking glasses) are available on the market using either OET or EOG technologies. These wearable eye trackers offer several advantages, including unobtrusive functionality, practicality, and low costs. However, several challenges and limitations must be considered when implementing these technologies in the field to monitor fatigue levels. This review investigates the feasibility of eye tracking in the field focusing on the practical applications in military operational environments.

MATERIALS AND METHOD

This paper summarizes the existing literature about eyeblink dynamics and available wearable eye-tracking technologies, exposing challenges and limitations, as well as discussing practical recommendations on how to improve the feasibility of eye tracking in the field.

RESULTS

So far, no eye-tracking glasses can be recommended for use in a demanding work environment. First, eyeblink dynamics are influenced by multiple factors; therefore, environments, situations, and individual behavior must be taken into account. Second, the glasses' placement, sunlight, facial or body movements, vibrations, and sweat can drastically decrease measurement accuracy. The placement of the eye cameras for the OET and the placement of the electrodes for the EOG must be chosen consciously, the sampling rate must be minimal 200 Hz, and software and hardware must be robust to resist any factors influencing eye tracking.

CONCLUSION

Monitoring physiological and psychological readiness of soldiers, as well as other civil professionals that face higher risks when their attention is impaired or reduced, is necessary. However, improvements to eye-tracking devices' hardware, calibration method, sampling rate, and algorithm are needed in order to accurately monitor fatigue levels in the field.

Eye tracking to assess concussions: an intra-rater reliability study with healthy youth and adult athletes of selected contact and collision team sports

Eye movements that are dependent on cognition hold promise in assessing sports-related concussions but research on reliability of eye tracking measurements in athletic cohorts is very limited. This observational test-retest study aimed to establish whether eye tracking technology is a reliable tool for assessing sports-related concussions in youth and adult athletes partaking in contact and collision team sports. Forty-three youth (15.4 ± 2.2 years) and 27 adult (22.2 ± 2.9 years) Rugby Union and soccer players completed the study. Eye movements were recorded using SMIRED250mobile while participants completed a test battery twice, with a 1-week interval that included self-paced saccade (SPS), fixation stability, memory-guided sequence (MGS), smooth pursuit (SP), and antisaccades (AS) tasks. Intra-class correlation coefficient (ICC), measurement error (SEM) and smallest real difference (SRD) were calculated for 47 variables. Seventeen variables achieved an ICC > 0.50. In the adults, saccade count in SPS had good reliability (ICC = 0.86, SRD = 146.6 saccades). In the youth, the average blink duration in MGS had excellent reliability (ICC = 0.99, SRD = 59.4 ms); directional errors in AS tasks and gain of diagonal SP had good reliability (ICC = 0.78 and 0.77, SRD = 25.3 and 395.1%, respectively). Four metrics were found in this study to be reliable candidates for further biomarker validity research in contact and collision sport cohorts. Many variables failed to present a sufficient level of robustness for a practical diagnostic tool; possibly, because athletic cohorts have higher homogeneity, along with latent adverse effects of undetected concussions and repetitive head impacts. Since reliability of a measure can influence type II error, effect sizes, and confidence intervals, it is strongly advocated to conduct dedicated reliability evaluations prior to any validity studies.

Evaluation of eyestrain with vertical electrooculogram

BACKGROUND AND OBJECTIVE

Eyestrain has been increasingly severe in our lives and works as the progress of computers and smartphones. Evaluating eyestrain helps to prevent and relieve eyestrain. Our study aimed to evaluate eyestrain by analyzing vertical electrooculogram (VEOG).

METHODS

21 young subjects were asked to watch a video on the computer for a totally 120 minutes each, during which the VEOG signal was acquired using only three electrodes, and the questionnaire was answered every 30 minutes. The VEOG signal was divided into four 30-minute phases, from which VEOG signal power probability (VEOGSPP) features and blink features were extracted. The blink features include the changes of blink number (BN), group blinks number (GBN) and ratio (GBR), mean blink amplitude (Mean_BA) and duration (Mean_BD), mean blink duration at 50% (Mean_BD50), mean closing duration (Mean_CD) and opening duration (Mean_OD), mean opening duration at early 50% (Mean_ODE50) and late 50% (Mean_ODL50), mean blink maximum rising slope (Mean_BMRS) and falling slope (Mean_BMFS).

RESULTS

The results showed that the VEOGSPP in the high-frequency band (0.8-6.3Hz), BN, GBN, and GBR significantly increased while the VEOGSPP in the low-frequency band (0.1-0.4Hz), Mean_BA, Mean_OD, and Mean_ODL50 significantly decreased with eyestrain (P<0.05).

CONCLUSIONS

In conclusion, eyestrain induced by watching videos for a long time could be well evaluated by analyzing the VEOG signal.

OculoMotor Assessment Tool Test Procedure and Normative Data

SIGNIFICANCE

This study establishes normative data and a testing procedure for the oculomotor assessment tool. The oculomotor assessment tool standardizes visual targets for the Vestibular/OculoMotor Screening assessment and provides additional metrics that may aid in the differentiation between those with normal and those with abnormal oculomotor function potentially caused by a concussion.

PURPOSE

This study aimed to assess the oculomotor endurance of healthy participants with no self-reported history of concussions using the oculomotor assessment tool.

METHODS

Healthy participants (n = 376, average age of 20.4 years, range of 11 to 34 years, with no self-reported history of concussions) were recruited to perform the following three tasks for 60 seconds each: (1) horizontal saccades, (2) vertical saccades, and (3) vergence jumps. The participants were instructed to alternate visual fixation between two targets for each of the tasks as fast as they could without overshooting or undershooting the visual target. The differences in the number of eye movements between the initial and latter 30 seconds of the 1-minute test were analyzed.

RESULTS

A statistical difference (P < .001) was observed in the number of eye movements for all three tasks (horizontal saccades [70 ± 15 for initial 30 seconds, 63 ± 13 for latter 30 seconds], vertical saccades [68 ± 14, 63 ± 13], and vergence jumps [43 ± 11, 39 ± 10]) between the initial and latter 30 seconds. No significant differences were identified in the number of eye movements or the change in eye movements between the initial and latter 30 seconds based on sex.

CONCLUSIONS

These results establish a normative database for various eye movements. These data could potentially be used to compare different patient populations who have binocular endurance dysfunctions potentially due to traumatic brain injury, such as patients with concussion(s).

Mental fatigue prediction during eye-typing

Mental fatigue is a common problem associated with neurological disorders. Until now, there has not been a method to assess mental fatigue on a continuous scale. Camera-based eye-typing is commonly used for communication by people with severe neurological disorders. We designed a working memory-based eye-typing experiment with 18 healthy participants, and obtained eye-tracking and typing performance data in addition to their subjective scores on perceived effort for every sentence typed and mental fatigue, to create a model of mental fatigue for eye-typing. The features of the model were the eye-based blink frequency, eye height and baseline-related pupil diameter. We predicted subjective ratings of mental fatigue on a six-point Likert scale, using random forest regression, with 22% lower mean absolute error than using simulations. When additionally including task difficulty (i.e. the difficulty of the sentences typed) as a feature, the variance explained by the model increased by 9%. This indicates that task difficulty plays an important role in modelling mental fatigue. The results demonstrate the feasibility of objective and non-intrusive measurement of fatigue on a continuous scale.

Eyeblink Detection in the Field: A Proof of Concept Study of Two Mobile Optical Eye-Trackers

Introduction

High physical and cognitive strain, high pressure, and sleep deficit are part of daily life for military professionals and civilians working in physiologically demanding environments. As a result, cognitive and physical capacities decline and the risk of illness, injury, or accidents increases. Such unfortunate outcomes could be prevented by tracking real-time physiological information, revealing individuals’ objective fatigue levels. Oculometrics, and especially eyeblinks, have been shown to be promising biomarkers that reflect fatigue development. Head-mounted optical eye-trackers are a common method to monitor these oculometrics. However, studies measuring eyeblink detection in real-life settings have been lacking in the literature. Therefore, this study aims to validate two current mobile optical eye-trackers in an unrestrained military training environment.

Materials and Method

Three male participants (age 20.0 ± 1.0) of the Swiss Armed Forces participated in this study by wearing three optical eye-trackers, two VPS16s (Viewpointsystem GmbH, Vienna, Austria) and one Pupil Core (Pupil Labs GmbH, Berlin, Germany), during four military training events: Healthcare education, orienteering, shooting, and military marching. Software outputs were analyzed against a visual inspection (VI) of the video recordings of participants’ eyes via the respective software. Absolute and relative blink numbers were provided. Each blink detected by the software was classified as a “true blink” (TB) when it occurred in the software output and the VI at the same time, as a “false blink” (FB) when it occurred in the software but not in the VI, and as a “missed blink” (MB) when the software failed to detect a blink that occurred in the VI. The FBs were further examined for causes of the incorrect recordings, and they were divided into four categories: “sunlight,” “movements,” “lost pupil,” and “double-counted”. Blink frequency (i.e., blinks per minute) was also analyzed.

Results

Overall, 49.3% and 72.5% of registered eyeblinks were classified as TBs for the VPS16 and Pupil Core, respectively. The VPS16 recorded 50.7% of FBs and accounted for 8.5% of MBs, while the Pupil Core recorded 27.5% of FBs and accounted for 55.5% of MBs. The majority of FBs—45.5% and 73.9% for the VPS16 and Pupil Core, respectively—were erroneously recorded due to participants’ eye movements while looking up, down, or to one side. For blink frequency analysis, systematic biases (±limits of agreement) stood at 23.3 (±43.5) and −4.87 (±14.1) blinks per minute for the VPS16 and Pupil Core, respectively. Significant differences in systematic bias between devices and the respective VIs were found for nearly all activities (P < .05).

Conclusion

An objective physiological monitoring of fatigue is necessary for soldiers as well as civil professionals who are exposed to higher risks when their cognitive or physical capacities weaken. However, optical eye-trackers’ accuracy has not been specified under field conditions—especially not in monitoring fatigue. The significant overestimation and underestimation of the VPS16 and Pupil Core, respectively, demonstrate the general difficulty of blink detection in the field.

Influence of Increasing Task Complexity and Use of Informational Assistance Systems on Mental Workload

(1) Background: Cognitive aspects and complexity in modern manual mixed model assembly are increasing. To reduce mental workload (MWL), informational assistance systems are introduced. The influence of complexity and used assistance system on MWL should be investigated to further improve the implementation of such assistance systems. (2) Methods: Using a simulated close to real-life assembly task a 2 × 3 design was chosen, with two levels of assembly complexity (within subjects) and three different assistance systems (paper, Augmented Reality (AR)-glasses, tablet-between subjects). MWL was measured using either physiological response (electrocardiogram (ECG) and eye-tracking) or performance indicators. (3) Results: An influence of task complexity on MWL can be shown. Additionally, usability based differences between the used assistance systems become more evident with reference to the results of area of interest analysis. (4) Conclusions: Using a multi-modal measurement approach, it is possible to detect complexity-based differences in MWL. Additional research on validity and alignment is needed to further use these for (neuro-) ergonomic considerations and recommendations.

Operators' Load Monitoring and Management

Due to the introduction of highly automated vehicles and systems, the tasks of operators (drivers, pilots, air traffic controllers, production process managers) are in transition from "active control" to "passive monitoring" and "supervising". As a result of this transition, the roles of task load and workload are decreasing while the role of the mental load is increasing, thereby the new type of loads might be defined as information load and communication load. This paper deals with operators' load monitoring and management in highly automated systems. This research (i) introduces the changes in the role of operators and requirements in load management, (ii) defines the operators' models, (iii) describes the possible application of sensors and their integration into the working environment of operators, and (iv) develops the load observation and management concept. There are some examples of analyses of measurements and the concept of validation is discussed. This paper mainly deals with operators, particularly pilots and air traffic controllers (ATCOs).

Eye Movements in Response to Pain-Related Feelings in the Presence of Low and High Cognitive Loads

The affective dimension of pain contributes to pain perception. Cognitive load may influence pain-related feelings. Eye tracking has proven useful for detecting cognitive load effects objectively by using relevant eye movement characteristics. In this study, we investigated whether eye movement characteristics differ in response to pain-related feelings in the presence of low and high cognitive loads. A set of validated, control, and pain-related sounds were applied to provoke pain-related feelings. Twelve healthy young participants (six females) performed a cognitive task at two load levels, once with the control and once with pain-related sounds in a randomized order. During the tasks, eye movements and task performance were recorded. Afterwards, the participants were asked to fill out questionnaires on their pain perception in response to the applied cognitive loads. Our findings indicate that an increased cognitive load was associated with a decreased saccade peak velocity, saccade frequency, and fixation frequency, as well as an increased fixation duration and pupil dilation range. Among the oculometrics, pain-related feelings were reflected only in the pupillary responses to a low cognitive load. The performance and perceived cognitive load decreased and increased, respectively, with the task load level and were not influenced by the pain-related sounds. Pain-related feelings were lower when performing the task compared with when no task was being performed in an independent group of participants. This might be due to the cognitive engagement during the task. This study demonstrated that cognitive processing could moderate the feelings associated with pain perception.

An Eye-tracking based Evaluation on the Effect of Far-infrared Therapy for Relieving Visual Fatigue

Far-infrared (FIR) therapy is attracting great attention in clinical applications, whereas studies on its effect to relieve visual fatigue stay exiguity. This study tried to fill the gap by utilizing two novel eye-tracking parameters, i.e., the fixation frequency (FF) and saccade amplitude (SA), along with traditional indicators (i.e., the eye blink frequency (BF) and subjective score (SS)) of visual fatigue in two eye-tracking tests, i.e., the random digit search and fixed-point gaze. Twenty healthy subjects participated in the experiment during the same period of two consecutive days. A visual stimulus program was presented to each subject before the subjective grading and eye-tracking tests, followed by the relief of eyes with either using a FIR thermal eye mask or physically closing eyes. Finally, subjective grading and eye-tracking tests were re-performed. Results showed that FF and SA, along with BF and SS, were significantly different when measured before and after the eye relief with FIR therapy mask, suggesting that FF and SA were useful in evaluating visual fatigue. In addition, FIR therapy yielded much better performance than eye-closing rest, indicating that FIR therapy had the potential in accelerating the relief of visual fatigue.

Spontaneous eye blink rate predicts individual differences in exploration and exploitation during reinforcement learning

Spontaneous eye blink rate (sEBR) has been linked to striatal dopamine function and to how individuals make value-based choices after a period of reinforcement learning (RL). While sEBR is thought to reflect how individuals learn from the negative outcomes of their choices, this idea has not been tested explicitly. This study assessed how individual differences in sEBR relate to learning by focusing on the cognitive processes that drive RL. Using Bayesian latent mixture modelling to quantify the mapping between RL behaviour and its underlying cognitive processes, we were able to differentiate low and high sEBR individuals at the level of these cognitive processes. Further inspection of these cognitive processes indicated that sEBR uniquely indexed explore-exploit tendencies during RL: lower sEBR predicted exploitative choices for high valued options, whereas higher sEBR predicted exploration of lower value options. This relationship was additionally supported by a network analysis where, notably, no link was observed between sEBR and how individuals learned from negative outcomes. Our findings challenge the notion that sEBR predicts learning from negative outcomes during RL, and suggest that sEBR predicts individual explore-exploit tendencies. These then influence value sensitivity during choices to support successful performance when facing uncertain reward.

Aging and eye tracking: in the quest for objective biomarkers

Recent applications of eye tracking for diagnosis, prognosis and follow-up of therapy in age-related neurological or psychological deficits have been reviewed. The review is focused on active aging, neurodegeneration and cognitive impairments. The potential impacts and current limitations of using characterizing features of eye movements and pupillary responses (oculometrics) as objective biomarkers in the context of aging are discussed. A closer look into the findings, especially with respect to cognitive impairments, suggests that eye tracking is an invaluable technique to study hidden aspects of aging that have not been revealed using any other noninvasive tool. Future research should involve a wider variety of oculometrics, in addition to saccadic metrics and pupillary responses, including nonlinear and combinatorial features as well as blink- and fixation-related metrics to develop biomarkers to trace age-related irregularities associated with cognitive and neural deficits.

An Evaluation Method of Safe Driving for Senior Adults Using ECG Signals

The elderly are more susceptible to stress than younger people. In particular, heart palpitations are one of the causes of heart failure, which can lead to serious accidents. To prevent heart palpitations, we have devised the Safe Driving Intensity (SDI) and Cardiac Reaction Time (CRT) as new methods of estimating the correlations between effects on the driver's heart and the movement of a vehicle. In SDI measurement, recommended acceleration value of vehicle for safe driving is inferred from the suggested correlation algorithm using machine learning. A higher SDI value than other people means less pressure on the heart. CRT is an estimated value of the occurring time of heart palpitations caused by stressful driving. In particular, it is proved by SDI that elderly subjects tend to overestimate their driving abilities in personal assessment questionnaires. Furthermore, we validated our SDI using other general statistical methods. When comparing the results using a t-test, we obtained reliable results for the equivalent variance. Our results can be used as a basis for evaluating elderly people's driving ability, as well as allowing for the implementation of a personalized safe driving system for the elderly.

An oculometrics-based biofeedback system to impede fatigue development during computer work: A proof-of-concept study

A biofeedback system may objectively identify fatigue and provide an individualized timing plan for micro-breaks. We developed and implemented a biofeedback system based on oculometrics using continuous recordings of eye movements and pupil dilations to moderate fatigue development in its early stages. Twenty healthy young participants (10 males and 10 females) performed a cyclic computer task for 31–35 min over two sessions: 1) self-triggered micro-breaks (manual sessions), and 2) biofeedback-triggered micro-breaks (automatic sessions). The sessions were held with one-week inter-session interval and in a counterbalanced order across participants. Each session involved 180 cycles of the computer task and after each 20 cycles (a segment), the task paused for 5-s to acquire perceived fatigue using Karolinska Sleepiness Scale (KSS). Following the pause, a 25-s micro-break involving seated exercises was carried out whether it was triggered by the biofeedback system following the detection of fatigue (KSS≥5) in the automatic sessions or by the participants in the manual sessions. National Aeronautics and Space Administration Task Load Index (NASA-TLX) was administered after sessions. The functioning core of the biofeedback system was based on a Decision Tree Ensemble model for fatigue classification, which was developed using an oculometrics dataset previously collected during the same computer task. The biofeedback system identified fatigue with a mean accuracy of approx. 70%. Perceived workload obtained from NASA-TLX was significantly lower in the automatic sessions compared with the manual sessions, p = 0.01 Cohen’s d_z = 0.89. The results give support to the effectiveness of integrating oculometrics-based biofeedback in timing plan of micro-breaks to impede fatigue development during computer work.