Fatigue in the military: towards a fatigue detection test based on the saccadic velocity

A prediction model for the oceanauts' cognitive performance based on the mental workload of typical tasks

High-level cognitive abilities are essential for the oceanauts to successfully complete the tasks, such as assessing cruising positions, operating interface commands, and responding to voice instructions. However, it is still unknown which variables impact oceanauts' cognitive performance and how, and how best to create and implement analytic approaches to predict oceanaut's personalized cognitive performance. As a result, we attempted to conduct cognitive tests trials on four typical activities among oceanauts. Oceanaut cognition characteristics were collected in order to create a quantitative model of cognitive performance. We utilised Radial Basis Functions to predict the oceanauts' cognitive performance and investigated the impact of mental workload, personal characteristics, and comfort on their cognitive performance. The findings indicated that establishing an appropriate level of mental workload for the visual, auditory, cognitive, and psychomotor channels can enhance the oceanaut's cognitive performance of individuals engaged in ocean exploration. It is worth noting that the optimal values for mental workload vary across these channels. Furthermore, the presence of suitable comfort, appropriate age, and a relatively higher level of educational background contribute to the enhancement of cognitive performance among oceanauts.

Research on the Identification of Pilots’ Fatigue Status Based on Functional Near-Infrared Spectroscopy

Fatigue can lead to sluggish responses, misjudgments, flight illusions and other problems for pilots, which could easily bring about serious flight accidents. In this paper, a wearable functional near-infrared spectroscopy (fNIRS) device was used to record the changes of hemoglobin concentration of pilots during flight missions. The data was pre-processed, and 1080 valid samples were determined. Then, mean value, variance, standard deviation, kurtosis, skewness, coefficient of variation, peak value, and range of oxyhemoglobin (HbO2) in each channel were extracted. These indexes were regarded as the input of a stacked denoising autoencoder (SDAE) and were used to train the identification model of pilots’ fatigue state. The identification model of pilots’ fatigue status was established. The identification accuracy of the SDAE model was 91.32%, which was 23.26% and 15.97% higher than that of linear discriminant analysis (LDA) models and support vector machines (SVM) models, respectively. Results show that the SDAE model established in our study has high identification accuracy, which can accurately identify different fatigue states of pilots. Identification of pilots’ fatigue status based on fNIRS has important practical significance for reducing flight accidents caused by pilot fatigue.

Mental fatigue measurement using eye metrics: A systematic literature review

Mental fatigue measurement techniques utilize one or a combination of the cognitive, affective, and behavioral responses of the body. Eye-tracking and electrooculography, which are used to compute eye-based features, have gained momentum with increases in accuracy and robustness of the lightweight equipment emerging in the markets and can be used for objective and continuous assessment of mental fatigue. The main goal of this systematic review was to summarize the various eye-based features that have been used to measure mental fatigue and explore the relation of eye-based features to mental fatigue. The review process, following the preferred reporting items for systematic reviews and meta-analyses, used the electronic databases Web of Science, Scopus, ACM digital library, IEEE Xplore, and PubMed. Of the 1,385 retrieved documents, 34 studies met the inclusion criteria, resulting in 21 useful eye-based features. Categorizing these into eight groups revealed saccades as the most promising category, with saccade mean and peak velocity providing quick access to the cognitive states within 30 min of fatiguing activity. Complex brain networks involving sympathetic and parasympathetic nervous systems control the relation of mental fatigue to tonic pupil size and have the potential to indicate mental fatigue in controlled experimental conditions. Other categories, like blinks, are derived from the field of sleep research and should be used with caution. Several limitations emerged in the analysis, including varied experimental methods, use of dim lighting during the experiment (that could possibly also induce sleepiness), and use of unclear data analysis techniques, thereby complicating comparisons between studies.

Microsaccades in Applied Environments: Real-World Applications of Fixational Eye Movement Measurements

Across a wide variety of research environments, the recording of microsaccades and other fixational eye movements has provided insight and solutions into practical problems. Here we review the literature on fixational eye movements-especially microsaccades-in applied and ecologically-valid scenarios. Recent technical advances allow noninvasive fixational eye movement recordings in real-world contexts, while observers perform a variety of tasks. Thus, fixational eye movement measures have been obtained in a host of real-world scenarios, such as in connection with driver fatigue, vestibular sensory deprivation in astronauts, and elite athletic training, among others. Here we present the state of the art in the practical applications of fixational eye movement research, examine its potential future uses, and discuss the benefits of including microsaccade measures in existing eye movement detection technologies. Current evidence supports the inclusion of fixational eye movement measures in real-world contexts, as part of the development of new or improved oculomotor assessment tools. The real-world applications of fixational eye movement measurements will only grow larger and wider as affordable high-speed and high-spatial resolution eye trackers become increasingly prevalent.

Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue

INTRODUCTION

Fatigue is one of the most crucial factors that contribute to a decrease of the operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role in transport safety. To reduce fatigue-related tragedies and to increase the quality of a healthy life, many studies have focused on exploring effective methods and psychophysiological indicators for detecting and monitoring fatigue. However, those fatigue indicators rose many discrepancies among simulator and field studies, due to the vague conceptualism of fatigue, per se, which hinders the development of fatigue monitoring devices.

METHOD

This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue. Such a study helps to improve research results for a wide range of researchers whose interests lie in the development of in-vehicle fatigue detection devices. First, the nature of fatigue for drivers/pilots is elucidated regarding fatigue types and fatigue responses, which reshapes our understanding of the fatigue issue in the transport industry. Secondly, the widely used objective neurophysiological methods, including electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG), physical movement-based methods, vehicle-based methods, fitness-for-duty test as well as subjective methods (self-rating scales) are introduced. On the one hand, considering the difference between mental fatigue and sleepiness effects, the links between the objective and subjective indicators and fatigue are thoroughly investigated and reviewed. On the other hand, to better determine fatigue occurrence, a new combination of measures is recommended, as a single measure is not sufficient to yield a convincing benchmark of fatigue. Finally, since video-based techniques of measuring eye metrics offer a promising and practical method for monitoring operator fatigue, the relationship between fatigue and these eye metrics, that include blink-based, pupil-based, and saccade-based features, are also discussed. To realize a pragmatic fatigue detector for operators in the future, this paper concludes with a discussion on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.

The effects of flight complexity on gaze entropy: An experimental study with fighter pilots

We studied the effects of task load variations as a function of flight complexity on combat pilots' gaze behavior (i.e., entropy) while solving in-flight emergencies. The second company of the Spanish Army Attack Helicopter Battalion (n = 15) performed three sets of standardized flight exercises with different levels of complexity (low [recognition flights], medium and high [emergency flights]). Throughout the flight exercises we recorded pilots' gaze entropy, as well as pilots' performance (assessed by an expert flight instructor) and subjective ratings of task load (assessed by the NASA-Task Load Index). Furthermore, we used pilots' electroencephalographic (EEG) activity as a reference physiological index for task load variations. We found that pilots' gaze entropy decreased ∼2% (i.e., visual scanning became less erratic) while solving the emergency flight exercises, showing a significant decreasing trend with increasing complexity (p < .05). This is in consonance with the ∼12% increase in the frontal theta band of their EEG spectra during said exercises. Pilots' errors and subjective ratings of task load increased as flight complexity increased (p-values < .05). Gaze data suggest that pilots used nondeterministic visual patterns when the aircraft was in an error-free state (low complexity), and changed their scanning behavior, becoming more deterministic, once emergencies occurred (medium/high complexity). Overall, our findings indicate that gaze entropy can serve as a sensitive index of task load in aviation settings.

Wireless Patrol Sign-In System with Mental Fatigue Detection

Current sign-in methods of patrolling security guards mainly comprise signature, image identification, and fingerprint identification; notably, none of these methods indicate the physical and mental conditions of such guards. In particular, when patrolling security guards perform their duties consecutively for a long period of time, adequate attention should be directed toward their levels of mental fatigue. When a handwriting sign-in system is adopted, security guards may not record their sign-in time accurately, or they may fake signatures during long shifts. In addition, image identification systems cannot comprehensively reflect the physical and mental statuses of on-duty security guards, particularly their levels of fatigue. Monitor fatigue in patrolling security guards is important to avoid burnout and stress in the workplace. Therefore, in this study, a patrolling sign-in system that integrates physiological signals and images was designed. A thermometer, hand dynamometer, and electromyography sensor were combined to measure physiological signals. Results showed that hand grip strength and the median frequency of electromyography signals gradually reduced when muscle fatigue occurred. The system determined whether a security guard had signed in punctually and whether this person should stay on duty. Overall, this system was verified to operate effectively, and it is therefore applicable for monitoring the sign-in of patrolling security guards who work long shifts. This case series study proposed a conceptual prototype of the system; large-scale testing should be performed in subsequent research.

Oculomotor dynamics in skilled soccer players: The effects of sport expertise and strenuous physical effort

The ability to quickly locate objects within the visual field has a significant influence on athletic performance. Saccades are conjugate eye movements responsible for the rapid shift that brings a new part of the visual field into foveal vision. The aim of this study was to investigate the effects of sport expertise and intense physical effort on saccade dynamics during a free-viewing visual search task in skilled soccer players. Two groups of male subjects participated in this study: 18 soccer players and 18 non-athletes as the control group. Two sessions of visual search tasks without a sport-specific design were employed. Eye movements during the visual search tasks were recorded binocularly. Between pre- and post-test sessions, athletes performed a maximal incremental treadmill test. Cardiorespiratory parameters were measured continuously. Capillary lactate samples were collected. Pre-test findings indicated that athletes, in comparison to non-athletes, achieve higher values of the following characteristics of saccades (1) average acceleration, (2) acceleration peak, (3) deceleration peak, and (4) average velocity. An increase in post-test saccade duration and a decrease in post-test saccade velocity was observed in athletes due to the strenuous physical effort in relation to the pre-test state. Athletes may transfer high saccadic function efficiency to non-specific visual stimuli. The findings partially confirm that physical exertion can reduce oculomotor efficiency in athletes.

An Evaluation Method of Visualization Using Visual Momentum Based on Eye-Tracking Data

A new method based on eye-tracking data — visual momentum (VM) — was introduced to quantitatively evaluate a dynamic interactive visualization interface. We extracted the dimensionless factors from the raw eye-tracking data, including the fixation time factor [Formula: see text], the saccade amplitude factor D and the fixation number factor [Formula: see text]. A predictive regression model of VM was deduced by eye movement factors and the performance response time (RT). In Experiment 1, the experimental visualization materials were designed with six effectiveness levels according to design techniques proposed by Woods to improve VM (total replacement, fixed format data replacement, long shot, perceptual landmark and spatial representation) and were tested in six parallel subject groups. The coefficients of the regression model were calculated from the data of 42 valid subjects in Experiment 1. The mean VM of each group exhibited an increasing trend with an increase in design techniques. The data of the performance and eye tracking among the combined high VM group, middle VM group and low VM group indicated significant differences. The data analysis indicates that the results were consistent with the previous qualitative research of VM. We tested and verified this regression model in Experiment 2 with another dynamic interactive visualization. The results indicated that the VM calculated by the regression model was significantly correlated with the performance data. Therefore, the virtual parameter VM can be a quantitative indicator for evaluating dynamic visualization. It could be a useful evaluation method for the dynamic visualization in general working environments.

Monitoring driver fatigue using a single-channel electroencephalographic device: A validation study by gaze-based, driving performance, and subjective data

Driver fatigue can impair performance as much as alcohol does. It is the most important road safety concern, causing thousands of accidents and fatalities every year. Thanks to technological developments, wearable, single-channel EEG devices are now getting considerable attention as fatigue monitors, as they could help drivers to assess their own levels of fatigue and, therefore, prevent the deterioration of performance. However, the few studies that have used single-channel EEG devices to investigate the physiological effects of driver fatigue have had inconsistent results, and the question of whether we can monitor driver fatigue reliably with these EEG devices remains open. Here, we assessed the validity of a single-channel EEG device (TGAM-based chip) to monitor changes in mental state (from alertness to fatigue). Fifteen drivers performed a 2-h simulated driving task while we recorded, simultaneously, their prefrontal brain activity and saccadic velocity. We used saccadic velocity as the reference index of fatigue. We also collected subjective ratings of alertness and fatigue, as well as driving performance. We found that the power spectra of the delta EEG band showed an inverted U-shaped quadratic trend (EEG power spectra increased for the first hour and half, and decreased during the last thirty minutes), while the power spectra of the beta band linearly increased as the driving session progressed. Coherently, saccadic velocity linearly decreased and speeding time increased, suggesting a clear effect of fatigue. Subjective data corroborated these conclusions. Overall, our results suggest that the TGAM-based chip EEG device is able to detect changes in mental state while performing a complex and dynamic everyday task as driving.

An Inverse-Linear Logistic Model of The Main Sequence

A model of the main sequence is proposed based on the logistic function. The model’s fit to the peak velocity-amplitude relation resembles an S curve, simultaneously allowing control of the curve’s asymptotes at very small and very large amplitudes, as well as its slope over the mid-amplitude range. The proposed inverse-linear logistic model is also able to express the linear relation of duration and amplitude. We demonstrate the utility and robustness of the model when fit to aggregate data at the smalland mid-amplitude ranges, namely when fitting microsaccades, saccades, and superposition of both. We are confident the model will suitably extend to the largeamplitude range of eye movements.