EOG-Based Human-Computer Interface: 2000-2020 Review.

Electro-oculography (EOG)-based brain-computer interface (BCI) is a relevant technology influencing physical medicine, daily life, gaming and even the aeronautics field. EOG-based BCI systems record activity related to users' intention, perception and motor decisions. It converts the bio-physiological signals into commands for external hardware, and it executes the operation expected by the user through the output device. EOG signal is used for identifying and classifying eye movements through active or passive interaction. Both types of interaction have the potential for controlling the output device by performing the user's communication with the environment. In the aeronautical field, investigations of EOG-BCI systems are being explored as a relevant tool to replace the manual command and as a communicative tool dedicated to accelerating the user's intention. This paper reviews the last two decades of EOG-based BCI studies and provides a structured design space with a large set of representative papers. Our purpose is to introduce the existing BCI systems based on EOG signals and to inspire the design of new ones. First, we highlight the basic components of EOG-based BCI studies, including EOG signal acquisition, EOG device particularity, extracted features, translation algorithms, and interaction commands. Second, we provide an overview of EOG-based BCI applications in the real and virtual environment along with the aeronautical application. We conclude with a discussion of the actual limits of EOG devices regarding existing systems. Finally, we provide suggestions to gain insight for future design inquiries.

Attentional Orienting in Front and Rear Spaces in a Virtual Reality Discrimination Task.

Recent studies on covert attention suggested that the visual processing of information in front of us is different, depending on whether the information is present in front of us or if it is a reflection of information behind us (mirror information). This difference in processing suggests that we have different processes for directing our attention to objects in front of us (front space) or behind us (rear space). In this study, we investigated the effects of attentional orienting in front and rear space consecutive of visual or auditory endogenous cues. Twenty-one participants performed a modified version of the Posner paradigm in virtual reality during a spaceship discrimination task. An eye tracker integrated into the virtual reality headset was used to make sure that the participants did not move their eyes and used their covert attention. The results show that informative cues produced faster response times than non-informative cues but no impact on target identification was observed. In addition, we observed faster response times when the target occurred in front space rather than in rear space. These results are consistent with an orienting cognitive process differentiation in the front and rear spaces. Several explanations are discussed. No effect was found on subjects' eye movements, suggesting that participants did not use their overt attention to improve task performance.

Facing successfully high mental workload and stressors: An fMRI study.

The present fMRI study aimed at highlighting patterns of brain activations and autonomic activity when confronted with high mental workload and the threat of auditory stressors. Twenty participants performed a complex cognitive task in either safe or aversive conditions. Our results showed that increased mental workload induced recruitment of the lateral frontoparietal executive control network (ECN), along with disengagement of medial prefrontal and posterior cingulate regions of the default mode network (DMN). Mental workload also elicited an increase in heart rate and pupil diameter. Task performance did not decrease under the threat of stressors, most likely due to efficient inhibition of auditory regions, as reflected by a large decrement of activity in the superior temporal gyri. The threat of stressors was also accompanied with deactivations of limbic regions of the salience network (SN), possibly reflecting emotional regulation mechanisms through control from dorsal medial prefrontal and parietal regions, as indicated by functional connectivity analyses. Meanwhile, the threat of stressors induced enhanced ECN activity, likely for improved attentional and cognitive processes toward the task, as suggested by increased lateral prefrontal and parietal activations. These fMRI results suggest that measuring the balance between ECN, SN, and DMN recruitment could be used for objective mental state assessment. In this sense, an extra recruitment of task-related regions and a high ratio of lateral versus medial prefrontal activity may represent a relevant marker of increased but efficient mental effort, while the opposite may indicate a disengagement from the task due to mental overload and/or stressors.

Pushing open the door to reality: On facilitating the transitions from virtual to real environments.

The recent rise of virtual reality technology has led researchers to investigate how to adapt transitions to virtual environments. Transitions play a key role in facilitating the return to reality, which is of particular importance when the virtual world is far more agreeable than the real world. In the present study, the efficacy of a door transition - an almost "transparent" door falling out the top of the virtual environment and controlled by the user - was evaluated and compared to two basic transitions: a direct transition and a fading transition. Participants reported a strong preference for the door transition that was evaluated as being smoother, more controllable, and greatly facilitated the return to reality. Moreover, the results showed that the door transition triggered no greater sickness in participants than the two other types of transition.

Visual scanning strategies in the cockpit are modulated by pilots' expertise: A flight simulator study.

During a flight, pilots must rigorously monitor their flight instruments since it is one of the critical activities that contribute to update their situation awareness. The monitoring is cognitively demanding, but is necessary for timely intervention in the event of a parameter deviation. Many studies have shown that a large part of commercial aviation accidents involved poor cockpit monitoring from the crew. Research in eye-tracking has developed numerous metrics to examine visual strategies in fields such as art viewing, sports, chess, reading, aviation, and space. In this article, we propose to use both basic and advanced eye metrics to study visual information acquisition, gaze dispersion, and gaze patterning among novices and pilots. The experiment involved a group of sixteen certified professional pilots and a group of sixteen novice during a manual landing task scenario performed in a flight simulator. The two groups landed three times with different levels of difficulty (manipulated via a double task paradigm). Compared to novices, professional pilots had a higher perceptual efficiency (more numerous and shorter dwells), a better distribution of attention, an ambient mode of visual attention, and more complex and elaborate visual scanning patterns. We classified pilot's profiles (novices-experts) by machine learning based on Cosine KNN (K-Nearest Neighbors) using transition matrices. Several eye metrics were also sensitive to the landing difficulty. Our results can benefit the aviation domain by helping to assess the monitoring performance of the crews, improve initial and recurrent training and ultimately reduce incidents, and accidents due to human error.

Electro-Encephalography and Electro-Oculography in Aeronautics: A Review Over the Last Decade (2010-2020).

Electro-encephalography (EEG) and electro-oculography (EOG) are methods of electrophysiological monitoring that have potentially fruitful applications in neuroscience, clinical exploration, the aeronautical industry, and other sectors. These methods are often the most straightforward way of evaluating brain oscillations and eye movements, as they use standard laboratory or mobile techniques. This review describes the potential of EEG and EOG systems and the application of these methods in aeronautics. For example, EEG and EOG signals can be used to design brain-computer interfaces (BCI) and to interpret brain activity, such as monitoring the mental state of a pilot in determining their workload. The main objectives of this review are to, (i) offer an in-depth review of literature on the basics of EEG and EOG and their application in aeronautics; (ii) to explore the methodology and trends of research in combined EEG-EOG studies over the last decade; and (iii) to provide methodological guidelines for beginners and experts when applying these methods in environments outside the laboratory, with a particular focus on human factors and aeronautics. The study used databases from scientific, clinical, and neural engineering fields. The review first introduces the characteristics and the application of both EEG and EOG in aeronautics, undertaking a large review of relevant literature, from early to more recent studies. We then built a novel taxonomy model that includes 150 combined EEG-EOG papers published in peer-reviewed scientific journals and conferences from January 2010 to March 2020. Several data elements were reviewed for each study (e.g., pre-processing, extracted features and performance metrics), which were then examined to uncover trends in aeronautics and summarize interesting methods from this important body of literature. Finally, the review considers the advantages and limitations of these methods as well as future challenges.

The diagnosticity of psychophysiological signatures: Can we disentangle mental workload from acute stress with ECG and fNIRS?

The ability to identify reliable and sensitive physiological signatures of psychological dimensions is key to developing intelligent adaptive systems that may in turn help to mitigate human error in complex operations. The challenge of this endeavor lies with diagnosticity. Despite different underlying causes, the physiological correlates of workload and acute psychological stress manifest in rather similar ways and can be easily confounded. The current work aimed to build a diagnostic model of mental state through the simultaneous classification of mental workload (varied through three levels of the n-back task) and acute stress (the presence/absence of aversive sounds) with machine learning. Using functional near infrared spectroscopy (fNIRS) and electrocardiography (ECG), the model's classifiers was above-chance to disentangle variations of mental workload from variations of acute stress. Both ECG and fNIRS could predict mental workload level, the best accuracy resulted from the two measures in combination. Stress level could not be accurately diagnosed through ECG alone, only with fNIRS or ECG and fNIRS combined. Individual calibration may be important since stress classification was more accurate for those with higher subjective state anxiety, perhaps due to a greater sensitivity to stress. Mental workload and stress were both better classified with activity in lateral prefrontal regions of the cortex than the medial areas, and the HbO2 signal generally lead to better classification than HHB. The current model represents a step forward to finely discriminate different mental states despite their rather analog physiological correlates.

Improving eye-tracking calibration accuracy using symbolic regression.

Eye tracking systems have recently experienced a diversity of novel calibration procedures, including smooth pursuit and vestibulo-ocular reflex based calibrations. These approaches allowed collecting more data compared to the standard 9-point calibration. However, the computation of the mapping function which provides planar gaze positions from pupil features given as input is mostly based on polynomial regressions, and little work has investigated alternative approaches. This paper fills this gap by providing a new calibration computation method based on symbolic regression. Instead of making prior assumptions on the polynomial transfer function between input and output records, symbolic regression seeks an optimal model among different types of functions and their combinations. This approach offers an interesting perspective in terms of flexibility and accuracy. Therefore, we designed two experiments in which we collected ground truth data to compare vestibulo-ocular and smooth pursuit calibrations based on symbolic regression, both using a marker or a finger as a target, resulting in four different calibrations. As a result, we improved calibration accuracy by more than 30%, with reasonable extra computation time.

Assessment of Ocular and Physiological Metrics to Discriminate Flight Phases in Real Light Aircraft.

OBJECTIVE: The purpose of the present study was to find psychophysiological proxies that are straightforward to use and could be implemented in actual flight conditions to accurately discriminate pilots' workload levels. BACKGROUND: Piloting an aircraft is a complex activity where cognitive limitations may jeopardize flight safety. There is a need to implement solutions to monitor pilots' workload level to improve flight safety. There has been recent interest in combining psychophysiological measurements. Most of these studies were conducted in flight simulators at the group level, limiting the interpretation of the results. METHODS: We conducted an experiment with 11 pilots performing two standard traffic patterns in a light aircraft. Five metrics were derived from their ocular and cardiac activities and were evaluated through three flight phases: takeoff, downwind, and landing. RESULTS: Statistical analyses showed that the saccadic rate was the most efficient metric to distinguish between the three flight phases. In addition, a classifier trained on the ocular data collected from the first run predicted the flight phase within a second run with an accuracy of 75%. No gain in the classifier accuracy has been found by combining cardiac and ocular metrics. CONCLUSIONS: Ocular-based metrics may be more suitable than cardiac ones to provide relevant information on pilots' flying activity in operational settings. APPLICATIONS: Electrocardiographic and eye-tracking devices could be implemented in future cockpits as additional flight data for accident analysis, an objective pilot's state evaluation for training, and proxies for human-machine interactions to improve flight safety.

Author Correction: Mental workload and neural efficiency quantified in the prefrontal cortex using fNIRS.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Scanpath visualization and comparison using visual aggregation techniques.

We demonstrate the use of different visual aggregation techniques to obtain non-cluttered visual representations of scanpaths. First, fixation points are clustered using the mean-shift algorithm. Second, saccades are aggregated using the Attribute-Driven Edge Bundling (ADEB) algorithm that handles a saccades direction, onset timestamp, magnitude or their combination for the edge compatibility criterion. Flow direction maps, computed during bundling, can be visualized separately (vertical or horizontal components) or as a single image using the Oriented Line Integral Convolution (OLIC) algorithm. Furthermore, cosine similarity between two flow direction maps provides a similarity map to compare two scanpaths. Last, we provide examples of basic patterns, visual search task, and art perception. Used together, these techniques provide valuable insights about scanpath exploration and informative illustrations of the eye movement data.

Uncertainty visualization of gaze estimation to support operator-controlled calibration.

In this paper, we investigate how visualization assets can support the qualitative evaluation of gaze estimation uncertainty. Although eye tracking data are commonly available, little has been done to visually investigate the uncertainty of recorded gaze information. This paper tries to fill this gap by using innovative uncertainty computation and visualization. Given a gaze processing pipeline, we estimate the location of this gaze position in the world camera. To do so we developed our own gaze data processing which give us access to every stage of the data transformation and thus the uncertainty computation. To validate our gaze estimation pipeline, we designed an experiment with 12 participants and showed that the correction methods we proposed reduced the Mean Angular Error by about 1.32 cm, aggregating all 12 participants' results. The Mean Angular Error is 0.25° (SD=0.15°) after correction of the estimated gaze. Next, to support the qualitative assessment of this data, we provide a map which codes the actual uncertainty in the user point of view.

Mental workload and neural efficiency quantified in the prefrontal cortex using fNIRS.

An improved understanding of how the brain allocates mental resources as a function of task difficulty is critical for enhancing human performance. Functional near infrared spectroscopy (fNIRS) is a field-deployable optical brain monitoring technology that provides a direct measure of cerebral blood flow in response to cognitive activity. We found that fNIRS was sensitive to variations in task difficulty in both real-life (flight simulator) and laboratory settings (tests measuring executive functions), showing increased concentration of oxygenated hemoglobin (HbO2) and decreased concentration of deoxygenated hemoglobin (HHb) in the prefrontal cortex as the tasks became more complex. Intensity of prefrontal activation (HbO2 concentration) was not clearly correlated to task performance. Rather, activation intensity shed insight on the level of mental effort, i.e., how hard an individual was working to accomplish a task. When combined with performance, fNIRS provided an estimate of the participants' neural efficiency, and this efficiency was consistent across levels of difficulty of the same task. Overall, our data support the suitability of fNIRS to assess the mental effort related to human operations and represents a promising tool for the measurement of neural efficiency in other contexts such as training programs or the clinical setting.

Can an aircraft be piloted via sonification with an acceptable attentional cost? A comparison of blind and sighted pilots.

In the aeronautics field, some authors have suggested that an aircraft's attitude sonification could be used by pilots to cope with spatial disorientation situations. Such a system is currently used by blind pilots to control the attitude of their aircraft. However, given the suspected higher auditory attentional capacities of blind people, the possibility for sighted individuals to use this system remains an open question. For example, its introduction may overload the auditory channel, which may in turn alter the responsiveness of pilots to infrequent but critical auditory warnings. In this study, two groups of pilots (blind versus sighted) performed a simulated flight experiment consisting of successive aircraft maneuvers, on the sole basis of an aircraft sonification. Maneuver difficulty was varied while we assessed flight performance along with subjective and electroencephalographic (EEG) measures of workload. The results showed that both groups of participants reached target-attitudes with a good accuracy. However, more complex maneuvers increased subjective workload and impaired brain responsiveness toward unexpected auditory stimuli as demonstrated by lower N1 and P3 amplitudes. Despite that the EEG signal showed a clear reorganization of the brain in the blind participants (higher alpha power), the brain responsiveness to unexpected auditory stimuli was not significantly different between the two groups. The results suggest that an auditory display might provide useful additional information to spatially disoriented pilots with normal vision. However, its use should be restricted to critical situations and simple recovery or guidance maneuvers.

The impact of luminance on tonic and phasic pupillary responses to sustained cognitive load.

Pupillary reactions independent of light conditions have been linked to cognition for a long time. However, the light conditions can impact the cognitive pupillary reaction. Previous studies underlined the impact of luminance on pupillary reaction, but it is still unclear how luminance modulates the sustained and transient components of pupillary reaction - tonic pupil diameter and phasic pupil response. In the present study, we investigated the impact of the luminance on these two components under sustained cognitive load. Fourteen participants performed a novel working memory task combining mathematical computations with a classic n-back task. We studied both tonic pupil diameter and phasic pupil response under low (1-back) and high (2-back) working memory load and two luminance levels (gray and white). We found that the impact of working memory load on the tonic pupil diameter was modulated by the level of luminance, the increase in tonic pupil diameter with the load being larger under lower luminance. In contrast, the smaller phasic pupil response found under high load remained unaffected by luminance. These results showed that luminance impacts the cognitive pupillary reaction - tonic pupil diameter (phasic pupil response) being modulated under sustained (respectively, transient) cognitive load. These findings also support the relationship between the locus-coeruleus system, presumably functioning in two firing modes - tonic and phasic - and the pupil diameter. We suggest that the tonic pupil diameter tracks the tonic activity of the locus-coeruleus while phasic pupil response reflects its phasic activity. Besides, the designed novel cognitive paradigm allows the simultaneous manipulation of sustained and transient components of the cognitive load and is useful for dissociating the effects on the tonic pupil diameter and phasic pupil response.

Neural and psychophysiological correlates of human performance under stress and high mental workload.

In our anxiogenic and stressful world, the maintenance of an optimal cognitive performance is a constant challenge. It is particularly true in complex working environments (e.g. flight deck, air traffic control tower), where individuals have sometimes to cope with a high mental workload and stressful situations. Several models (i.e. processing efficiency theory, cognitive-energetical framework) have attempted to provide a conceptual basis on how human performance is modulated by high workload and stress/anxiety. These models predict that stress can reduce human cognitive efficiency, even in the absence of a visible impact on the task performance. Performance may be protected under stress thanks to compensatory effort, but only at the expense of a cognitive cost. Yet, the psychophysiological cost of this regulation remains unclear. We designed two experiments involving pupil diameter, cardiovascular and prefrontal oxygenation measurements. Participants performed the Toulouse N-back Task that intensively engaged both working memory and mental calculation processes under the threat (or not) of unpredictable aversive sounds. The results revealed that higher task difficulty (higher n level) degraded the performance and induced an increased tonic pupil diameter, heart rate and activity in the lateral prefrontal cortex, and a decreased phasic pupil response and heart rate variability. Importantly, the condition of stress did not impact the performance, but at the expense of a psychophysiological cost as demonstrated by lower phasic pupil response, and greater heart rate and prefrontal activity. Prefrontal cortex seems to be a central region for mitigating the influence of stress because it subserves crucial functions (e.g. inhibition, working memory) that can promote the engagement of coping strategies. Overall, findings confirmed the psychophysiological cost of both mental effort and stress. Stress likely triggered increased motivation and the recruitment of additional cognitive resources that minimize its aversive effects on task performance (effectiveness), but these compensatory efforts consumed resources that caused a loss of cognitive efficiency (ratio between performance effectiveness and mental effort).

High Working Memory Load Impairs Language Processing during a Simulated Piloting Task: An ERP and Pupillometry Study.

Given the important amount of visual and auditory linguistic information that pilots have to process, operating an aircraft generates a high working-memory load (WML). In this context, the ability to focus attention on relevant information and to remain responsive to concurrent stimuli might be altered. Consequently, understanding the effects of WML on the processing of both linguistic targets and distractors is of particular interest in the study of pilot performance. In the present work, participants performed a simplified piloting task in which they had to follow one of three colored aircraft, according to specific written instructions (i.e., the written word for the color corresponding to the color of one of the aircraft) and to ignore either congruent or incongruent concurrent auditory distractors (i.e., a spoken name of color). The WML was manipulated with an n-back sub-task. Participants were instructed to apply the current written instruction in the low WML condition, and the 2-back written instruction in the high WML condition. Electrophysiological results revealed a major effect of WML at behavioral (i.e., decline of piloting performance), electrophysiological, and autonomic levels (i.e., greater pupil diameter). Increased WML consumed resources that could not be allocated to the processing of the linguistic stimuli, as indexed by lower P300/P600 amplitudes. Also, significantly, lower P600 responses were measured in incongruent vs. congruent trials in the low WML condition, showing a higher difficulty reorienting attention toward the written instruction, but this effect was canceled in the high WML condition. This suppression of interference in the high load condition is in line with the engagement/distraction trade-off model. We propose that P300/P600 components could be reliable indicators of WML and that they allow an estimation of its impact on the processing of linguistic stimuli.

Frequency analysis of a task-evoked pupillary response: Luminance-independent measure of mental effort.

Pupil diameter is a widely-studied cognitive load measure, which, despite its convenience for non-intrusive operator state monitoring in complex environments, is still not available for in situ measurements because of numerous methodological limitations. The most important of these limitations is the influence of pupillary light reflex. Hence, there is the need of providing a pupil-based cognitive load measure that is independent of light conditions. In this paper, we present a promising technique of pupillary signal analysis resulting in luminance-independent measure of mental effort that could be used in real-time without a priori on luminous conditions. Twenty-two participants performed a short-term memory task under different screen luminance conditions. Our results showed that the amplitude of pupillary dilation due to load on memory was luminance-dependent with higher amplitude corresponding to lower-luminance condition. Furthermore, our experimentation showed that load on memory and luminance factors express themselves differently according to frequency. Therefore, as our statistical analysis revealed, the ratio between low (0-1.6 Hz) and high frequency (1.6-4 Hz) bands (LF/HF ratio) of power spectral densities of pupillary signal is sensitive to the cognitive load but not to luminance. Our results are promising for the measurement of load on memory in ecological settings.