Application of Eye Tracking Technology in Aviation, Maritime, and Construction Industries: A Systematic Review

Predicting Emotional Experiences through Eye-Tracking: A Study of Tourists' Responses to Traditional Village Landscapes

This study investigates the relationship between eye-tracking metrics and emotional experiences in the context of cultural landscapes and tourism-related visual stimuli. Fifty-three participants were involved in two experiments: forty-three in the data collection phase and ten in the model validation phase. Eye movements were recorded and the data were analyzed to identify correlations between four eye-tracking metrics-average number of saccades (ANS), total dwell fixation (TDF), fixation count (FC), and average pupil dilation (APD)-and 19 distinct emotional experiences, which were subsequently grouped into three categories: positive, neutral, and negative. The study examined the variations in eye-tracking metrics across architectural, historic, economic, and life landscapes, as well as the three primary phases of a tour: entry, core, and departure. Findings revealed that architectural and historic landscapes demanded higher levels of visual and cognitive engagement, especially during the core phase. Stepwise regression analysis identified four key eye-tracking predictors for emotional experiences, enabling the development of a prediction model. This research underscores the effectiveness of eye-tracking technology in capturing and predicting emotional responses to different landscape types, offering valuable insights for optimizing rural tourism environments and enhancing visitors' emotional experiences.

The after-effects of occupational whole-body vibration on human cognitive, visual, and motor function: A systematic review

Whole-body vibration (WBV) is prevalent in labour-related activities and can have adverse effects on the health and performance of the individuals exposed. However, evidence regarding the extent to which human functionality is affected following occupational WBV exposure has not been collated. The current systematic review sought to synthesize existing literature and assess the strength and direction of evidence regarding the acute after-effects of occupational WBV exposure on cognition, visual function, postural stability, and motor control. We conducted a comprehensive search of AMED, CINAHL, MEDLINE, PubMED, Psychology and Behavioural Sciences Collection, SPORTDiscus, APA PsychInfo, Cochrane Library, EMBASE, HMIC, Global Health, ProQuest Central, Scopus, Web of Science, and the US National Technical Information Service on April 26, 2023. Studies that quantified vibration exposure and measured acute changes in cognition, visual function, postural stability, and motor control from baseline to post-vibration were considered without date restriction. Out of the 2663 studies identified, 32 were eligible for inclusion. Based on the Risk of Bias in Non-Randomized Studies of Exposure (ROBINS-E) tool, the studies demonstrated low (66%), moderate (25%) and high risk of bias (9%). The findings indicate that after exposure to WBV, postural stability either deteriorates or remains unchanged. Inconsistent effects of WBV on cognition were reported, while visual function and motor control showed no pronounced changes following WBV. This might be attributed to assessment limitations such as learning effects in neuropsychological and motor tasks, and non-functional measures of vision employed. There was a lack of consistency in the characterization of vibration exposure and the assessment of associated effects on functional performance. Current evidence is therefore insufficient to provide definitive guidance for updating occupational health and safety regulations regarding WBV. However, this review highlights the potential for WBV to jeopardize post-exposure human performance and, consequently, safety. The completion of the review was supported by a UKRI EPSRC training grant. The review has been registered on PROSPERO (ref CRD42023391075).

Initial Experience of Using First-Person Wearable Video Recording Technology During Central Venous Catheter Placement in the Cardiac Operating Room

OBJECTIVE

The aim of this study was to use wearable video-recording technology to measure precisely the timing of discrete events during perioperative central venous catheter (CVC) placements.

DESIGN

A single-center, observational, exploratory study on the use of wearable video-recording technology during intraoperative CVC placement.

SETTING

The study was conducted at a University Hospital.

PARTICIPANTS

Clinical anesthesia residents, cardiothoracic anesthesia fellows, and attending anesthesiologists participated in this study.

INTERVENTIONS

Participants were asked to use eye-tracking glasses prior to the placement of a CVC in the cardiac operating rooms. No other instruction was given to the participants.

MEASUREMENTS AND MAIN RESULTS

The authors measured the total time to complete the CVC placement, phase-specific time, and specific times of interest. They compared these times across 3 training levels and tested differences with analysis of variance. The authors' findings indicated significant differences in total CVC placement time when the procedure included a pulmonary artery catheter insertion (1,170 ± 364, 923 ± 272, and 596 ± 226 seconds; F2,63 = 12.71, p < 0.0001). Additionally, they found differences in interval times and times of interest. The authors observed a reduction of variability with increasing experience during the CVC placement phase.

CONCLUSIONS

In this observational study, the study authors describe their experience using first-person wearable video-recording technology to precisely measure the timing of discrete events during CVC placement by anesthesia residents and anesthesiologists. Future work will leverage the eye-tracking capabilities of the existing hardware to identify areas of inefficiency to develop actionable targets for interventions that could improve trainee performance and patient safety.

ETMT: A Tool for Eye-Tracking-Based Trail-Making Test to Detect Cognitive Impairment

The growing number of people with cognitive impairment will significantly increase healthcare demand. Screening tools are crucial for detecting cognitive impairment due to a shortage of mental health experts aiming to improve the quality of life for those living with this condition. Eye tracking is a powerful tool that can provide deeper insights into human behavior and inner cognitive processes. The proposed Eye-Tracking-Based Trail-Making Test, ETMT, is a screening tool for monitoring a person's cognitive function. The proposed system utilizes a fuzzy-inference system as an integral part of its framework to calculate comprehensive scores assessing visual search speed and focused attention. By employing an adaptive neuro-fuzzy-inference system, the tool provides an overall cognitive-impairment score, allowing psychologists to assess and quantify the extent of cognitive decline or impairment in their patients. The ETMT model offers a comprehensive understanding of cognitive abilities and identifies potential deficits in various domains. The results indicate that the ETMT model is a potential tool for evaluating cognitive impairment and can capture significant changes in eye movement behavior associated with cognitive impairment. It provides a convenient and affordable diagnosis, prioritizing healthcare resources for severe conditions while enhancing feedback to practitioners.

Hidden Semi-Markov Models-Based Visual Perceptual State Recognition for Pilots

Pilots' loss of situational awareness is one of the human factors affecting aviation safety. Numerous studies have shown that pilot perception errors are one of the main reasons for a lack of situational awareness without a proper system to detect these errors. The main objective of this study is to examine the changes in pilots' eye movements during various flight tasks from the perspective of visual awareness. The pilot's gaze rule scanning strategy is mined through cSPADE, while a hidden semi-Markov model-based model is used to detect the pilot's visuoperceptual state, linking the correlation between the hidden state and time. The performance of the proposed algorithm is then compared with that of the hidden Markov model (HMM), and the more flexible hidden semi-Markov model (HSMM) is shown to have an accuracy of 93.55%.

Quotidian Profile of Vergence Angle in Ambulatory Subjects Monitored With Wearable Eye Tracking Glasses

Purpose

Wearable eye trackers record gaze position as ambulatory subjects navigate their environment. Tobii Pro Glasses 3 were tested to assess their accuracy and precision in the measurement of vergence angle.

Methods

Four subjects wore the eye tracking glasses, with their head stabilized, while fixating at a series of distances corresponding to vergence demands of: 0.25, 0.50, 1, 2, 4, 8, 16, and 32°. After these laboratory trials were completed, 10 subjects wore the glasses for a prolonged period while carrying out their customary daily pursuits. A vergence profile was compiled for each subject and compared with interpupillary distance.

Results

In the laboratory, the eye tracking glasses were comparable in accuracy to remote video eye trackers, outputting a mean vergence value within 1° of demand at all angles except 32°. In ambulatory subjects, the glasses were less accurate, due to tracking interruptions and measurement errors, partly mitigated by the application of data filters. Nonetheless, a useful record of vergence behavior was obtained in every subject. Vergence profiles often had a bimodal distribution, reflecting a preponderance of activities at near (mobile phone and computer) or far (driving and walking). As expected, vergence angle correlated with interpupillary distance.

Conclusions

Wearable eye tracking glasses make it possible to compile a nearly continuous record of vergence angle over hours, which can be correlated with the corresponding visual scene viewed by ambulatory subjects.

Translational Relevance

This technology provides new insight into the diversity of human ocular motor behavior and may become useful for the diagnosis of disorders that affect vergence function such as: convergence insufficiency, Parkinson disease, and strabismus.

Mobile eye tracking applied as a tool for customer experience research in a crowded train station

Train stations have increasingly become crowded, necessitating stringent requirements in the design of stations and commuter navigation through these stations. In this study, we explored the use of mobile eye tracking in combination with observation and a survey to gain knowledge on customer experience in a crowded train station. We investigated the utilization of mobile eye tracking in ascertaining customers' perception of the train station environment and analyzed the effect of a signalization prototype (visual pedestrian flow cues), which was intended for regulating pedestrian flow in a crowded underground passage. Gaze behavior, estimated crowd density, and comfort levels (an individual's comfort level in a certain situation), were measured before and after the implementation of the prototype. The results revealed that the prototype was visible in conditions of low crowd density. However, in conditions of high crowd density, the prototype was less visible, and the path choice was influenced by other commuters. Hence, herd behavior appeared to have a stronger effect than the implemented signalization prototype in conditions of high crowd density. Thus, mobile eye tracking in combination with observation and the survey successfully aided in understanding customers' perception of the train station environment on a qualitative level and supported the evaluation of the signalization prototype the crowded underground passage. However, the analysis process was laborious, which could be an obstacle for its practical use in gaining customer insights.

Towards tacit knowledge mining within context: Visual cognitive graph model and eye movement image interpretation

Visual attention is one of the most important brain cognitive functions, which filters the rich information of the outside world to ensure the efficient operation of limited cognitive resources. The underlying knowledge, i.e., tacit knowledge, hidden in the human attention allocation performances, is context-related and is hard to be expressed by experts, but it is essential for novice operator training and interaction system design. Traditional models of visual attention allocation and corresponding analysis methods seldomly involve task contextual information or present the tacit knowledge in an explicit and quantified way. Thus, it is challenging to pass on the expert's tacit knowledge to the novice or utilize it to construct an interaction system by employing traditional methods. Therefore, this paper first proposes a new model called the visual cognitive graph model based on graph theory to model the visual attention allocation associated with the task context. Then, based on this graph model, utilize the data mining method to reveal attention patterns within context to quantitatively analyze the operator's tacit knowledge during operation tasks. We introduced three physical quantities derived from graph theory to describe the tacit knowledge, which can be used directly to construct an interaction system or operator training. For example, discover the essential information within the task context, the relevant information affecting critical information, and the bridge information revealing the decision-making process. We tested the proposed method in the example of flight operation, the comparison results with the traditional eye movement graph model demonstrate that the proposed visual cognitive model can compromise the task context. The comparison results with the statistical analysis method demonstrate that our tacit knowledge mining method can reveal the underlying knowledge hidden in the visual information. Finally, we give practical applications in the examples of operator training guidance and adaptive interaction system. Our proposed method can explore more in-depth knowledge of visual information, such as the correlations of different obtained information and the way operator obtains information, most of which are even not noticed by operators themselves.

A Review of AI Cloud and Edge Sensors, Methods, and Applications for the Recognition of Emotional, Affective and Physiological States

Affective, emotional, and physiological states (AFFECT) detection and recognition by capturing human signals is a fast-growing area, which has been applied across numerous domains. The research aim is to review publications on how techniques that use brain and biometric sensors can be used for AFFECT recognition, consolidate the findings, provide a rationale for the current methods, compare the effectiveness of existing methods, and quantify how likely they are to address the issues/challenges in the field. In efforts to achieve the key goals of Society 5.0, Industry 5.0, and human-centered design better, the recognition of emotional, affective, and physiological states is progressively becoming an important matter and offers tremendous growth of knowledge and progress in these and other related fields. In this research, a review of AFFECT recognition brain and biometric sensors, methods, and applications was performed, based on Plutchik's wheel of emotions. Due to the immense variety of existing sensors and sensing systems, this study aimed to provide an analysis of the available sensors that can be used to define human AFFECT, and to classify them based on the type of sensing area and their efficiency in real implementations. Based on statistical and multiple criteria analysis across 169 nations, our outcomes introduce a connection between a nation's success, its number of Web of Science articles published, and its frequency of citation on AFFECT recognition. The principal conclusions present how this research contributes to the big picture in the field under analysis and explore forthcoming study trends.

An Investigation on the Influence of Operation Experience on Virtual Hazard Perception Using Wearable Eye Tracking Technology

Poor electrical hazard recognition is a widespread issue in the production industry. Hazard perception has impacts workers' hazard recognition, causing them to experience unanticipated hazard exposure and suffer catastrophic injuries. To improve the factors of affecting hazard perception, the current study examined hazard recognition as an everyday visual search task. A comparative test was carried out combining the advantages and disadvantages of the two test methods. It was confirmed that the virtual image test data can replace the real image test data and demonstrate superior flexible settings performance, so the virtual image test method is used. A hazard perception test method based on wearable eye tracking technology was proposed to analyze the eye-tracking data (i.e., fixation, count, search duration, mean fixation duration, eye tracking, and hazard recognition performance feedback) were compared between experts in the field of electrical safety: skilled workers with at least five years of work experience and workers who had been on the job for less than a year. It was found that experts had a better hazard recognition accuracy and missed detection rate than other workers. Experts' hazards research track was more concised and paid less attention time. This advantage is most obvious in complex risk environments. The findings also suggest that workers who have different working years was not obvious visual search patterns other than the search duration. As can be seen the work experience is not an absolute factor in improving hazard perception. The present research will be useful to understand the influence of working years on hazard perception and provide a theoretical basis for corresponding training.

Assessment of the Effect of Cleanliness on the Visual Inspection of Aircraft Engine Blades: An Eye Tracking Study

Background-The visual inspection of aircraft parts such as engine blades is crucial to ensure safe aircraft operation. There is a need to understand the reliability of such inspections and the factors that affect the results. In this study, the factor 'cleanliness' was analysed among other factors. Method-Fifty industry practitioners of three expertise levels inspected 24 images of parts with a variety of defects in clean and dirty conditions, resulting in a total of N = 1200 observations. The data were analysed statistically to evaluate the relationships between cleanliness and inspection performance. Eye tracking was applied to understand the search strategies of different levels of expertise for various part conditions. Results-The results show an inspection accuracy of 86.8% and 66.8% for clean and dirty blades, respectively. The statistical analysis showed that cleanliness and defect type influenced the inspection accuracy, while expertise was surprisingly not a significant factor. In contrast, inspection time was affected by expertise along with other factors, including cleanliness, defect type and visual acuity. Eye tracking revealed that inspectors (experts) apply a more structured and systematic search with less fixations and revisits compared to other groups. Conclusions-Cleaning prior to inspection leads to better results. Eye tracking revealed that inspectors used an underlying search strategy characterised by edge detection and differentiation between surface deposits and other types of damage, which contributed to better performance.