Evaluation of walking activity and gait to identify physical and mental fatigue in neurodegenerative and immune disorders: preliminary insights from the IDEA-FAST feasibility study.

BACKGROUND: Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue. This study explored the relationships between gait characteristics derived from an inertial measurement unit (IMU) and patient-reported fatigue in the IDEA-FAST feasibility study. METHODS: Participants with IMIDs and NDDs (Parkinson's disease (PD), Huntington's disease (HD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjogren's syndrome (PSS), and inflammatory bowel disease (IBD)) wore a lower-back IMU continuously for up to 10 days at home. Concurrently, participants completed PROs (physical fatigue (PF) and mental fatigue (MF)) up to four times a day. Macro (volume, variability, pattern, and acceleration vector magnitude) and micro (pace, rhythm, variability, asymmetry, and postural control) gait characteristics were extracted from the accelerometer data. The associations of these measures with the PROs were evaluated using a generalised linear mixed-effects model (GLMM) and binary classification with machine learning. RESULTS: Data were recorded from 72 participants: PD = 13, HD = 9, RA = 12, SLE = 9, PSS = 14, IBD = 15. For the GLMM, the variability of the non-walking bouts length (in seconds) with PF returned the highest conditional R2, 0.165, and with MF the highest marginal R2, 0.0018. For the machine learning classifiers, the highest accuracy of the current analysis was returned by the micro gait characteristics with an intrasubject cross validation method and MF as 56.90% (precision = 43.9%, recall = 51.4%). Overall, the acceleration vector magnitude, bout length variation, postural control, and gait rhythm were the most interesting characteristics for future analysis. CONCLUSIONS: Counterintuitively, the outcomes indicate that there is a weak relationship between typical gait measures and abnormal fatigue. However, factors such as the COVID-19 pandemic may have impacted gait behaviours. Therefore, further investigations with a larger cohort are required to fully understand the relationship between gait and abnormal fatigue.

[Mental fatigue state recognition method based on convolution neural network and long short-term memory].

The pace of modern life is accelerating, the pressure of life is gradually increasing, and the long-term accumulation of mental fatigue poses a threat to health. By analyzing physiological signals and parameters, this paper proposes a method that can identify the state of mental fatigue, which helps to maintain a healthy life. The method proposed in this paper is a new recognition method of psychological fatigue state of electrocardiogram signals based on convolutional neural network and long short-term memory. Firstly, the convolution layer of one-dimensional convolutional neural network model is used to extract local features, the key information is extracted through pooling layer, and some redundant data is removed. Then, the extracted features are used as input to the long short-term memory model to further fuse the ECG features. Finally, by integrating the key information through the full connection layer, the accurate recognition of mental fatigue state is successfully realized. The results show that compared with traditional machine learning algorithms, the proposed method significantly improves the accuracy of mental fatigue recognition to 96.3%, which provides a reliable basis for the early warning and evaluation of mental fatigue.

Exploratory factor analysis and validity of the virtual reality symptom questionnaire and computer use survey.

The widespread use of virtual reality head-mounted-displays (HMDs) calls for a re-examination of the impact of prolonged exposure to fixed visual displays at close ocular proximity. The purpose of this study is to validate the Virtual Reality Symptoms Questionnaire (VRSQ), created to understand symptoms of prolonged HMDs use, and Computer Use Survey (CUS), created to assess general physical and visual discomfort symptoms. Participants (N = 100) recorded their general discomfort symptoms using the CUS, performed an interactive task using a HMD for thirty minutes, and then answered the CUS again along with the VRSQ. VRSQ, analysed using an exploratory factor analysis, indicated a clear two-factor solution, and demonstrated very good internal consistency (α = 0.873). The CUS, also analysed using an exploratory factor analysis, indicated a four-factor solution, and demonstrated good internal consistency (α = 0.838). Practitioner Summary: A quantitative-experimental study was conducted to explore the factor structure and validate both the Virtual Reality Symptoms Questionnaire (VRSQ), and the Computer Use Survey (CUS). Findings indicate the VRSQ and CUS are precise and accurate survey instruments for evaluating discomfort after VR-HMD use and the latter for computer use. Abbreviations: VRSQ: virtual reality symptom questionnaire; CUS: computer use survey; OLED: organic light-emitting diode; MSQ: pensacola motion symptom questionnaire; SSQ: simulator sickness questionnaire; 3 D: three-dimensional computer generated space; VR: virtual reality; VR-HMD: virtual reality head-mounted-display; HMDs: head-mounted-displays; EFA: exploratory factor analysis.

Effect of Mindfulness Training on Fatigue and Recovery in Elite Volleyball Athletes: A Randomized Controlled Follow-Up Study.

Volleyball is a team sport with high physical and perceptual-cognitive demand, hence, increasing the perception of physical and mental fatigue during a competition. To alleviate fatigue (physical and mental), mindfulness and music have been proposed. The aim of this study was to analyze the effect of mindfulness-based mental versus music training on mental fatigue, physical fatigue, and recovery in elite competitive female volleyball athletes using a randomized two-controlled study with follow-up. Participants were 30 elite female Brazilian volleyball athletes. Athletes were randomly assigned to the following groups: 1) mindfulness-based mental training group (MBMT); 2) music-based training group (MBT); or 3) control group (CG). Three variables were evaluated as follows: 1) recovery based on total quality recovery; 2) mental fatigue visual analog scale; and 3) physical fatigue visual analog scale. Regarding recovery, there was no difference between the MBMT, MBT, and CG groups (p > 0.05). A difference in mental fatigue was noted between MBT and CG at follow-up [F(2,26) = 5.71, p = 0.009; large]. Regarding physical fatigue, there was no difference between the MBMT, MBT, and CG groups (p > 0.05). The mindfulness intervention effectively attenuated the mental fatigue caused by competition in volleyball athletes. These results will assist coaches and staff in providing fatigue management and reinforce the applicability of mental training in sports.

Stochastic Multichannel Ranking with Brain Dynamics Preferences.

A driver's cognitive state of mental fatigue significantly affects his or her driving performance and more important, public safety. Previous studies have leveraged reaction time (RT) as the metric for mental fatigue and aim at estimating the exact value of RT using electroencephalogram (EEG) signals within a regression model. However, due to the easily corrupted and also nonsmooth properties of RTs during data collection, methods focusing on predicting the exact value of a noisy measurement, RT generally suffer from poor generalization performance. Considering that human RT is the reflection of brain dynamics preference (BDP) rather than a single regression output of EEG signals, we propose a novel channel-reliability-aware ranking (CArank) model for the multichannel ranking problem. CArank learns from BDPs using EEG data robustly and aims at preserving the ordering corresponding to RTs. In particular, we introduce a transition matrix to characterize the reliability of each channel used in the EEG data, which helps in learning with BDPs only from informative EEG channels. To handle large-scale EEG signals, we propose a stochastic-generalized expectation maximum (SGEM) algorithm to update CArank in an online fashion. Comprehensive empirical analysis on EEG signals from 40 participants shows that our CArank achieves substantial improvements in reliability while simultaneously detecting noisy or less informative EEG channels.

On the relation between dimensions of fatigue and depression in adolescents and young adults with acquired brain injury.

Complaints of fatigue following acquired brain injury (ABI) are often associated with depression. However, the nature of this relationship is unclear; furthermore, research among young people with ABI is limited. The objective of this cross-sectional study was (1) to investigate levels of depression in young outpatients with ABI (15-30 years old) and (2) to determine how different dimensions of fatigue relate to depression. Five dimensions of fatigue were assessed with the Multidimensional Fatigue Inventory (MFI-20), and depression was assessed with the Major Depression Inventory (MDI). Mann-Whitney U-tests and multiple regression analyses were conducted. The ABI group (n = 105), on average 23.7 years old (SD = 4.2) and 31 months post-injury (SD = 61), had elevated levels of fatigue and depression compared to a convenience sample of 160 healthy controls, all p's < .001. In multivariate analyses, the predominantly mental dimensions of fatigue, General Fatigue, Mental Fatigue, and Reduced Motivation, were independently associated with MDI, all p's < .01, while the physical dimensions, Physical Fatigue and Reduced Activity, were not. Distinctions within the concept of fatigue may be important in relation to depression, and future research could benefit from adopting a multidimensional approach in the development of more targeted and effective treatments of fatigue and depression following ABI.

Psychometric properties of the fatigue questionnaire EORTC QLQ-FA12 and proposal of a cut-off value for young adults with cancer.

BACKGROUND: Young adult patients with cancer have to deal with their disease in an eventful phase of life. A common side effect of cancer and its treatment is cancer-related fatigue (CRF), a phenomenon which can thwart successful coping with developmental tasks. The aims of this study were to assess the psychometric properties of the EORTC QLQ-FA12, a new instrument for assessing physical, emotional and cognitive fatigue, in young adults with cancer, and to propose a cut-off value that indicates a need for further more specific diagnostics. METHODS: In a sample of young adults who were first diagnosed with cancer between the ages of 18 and 39 years old, we assess the composite and item reliabilities as well as discriminant validity of the subscales for the EORTC QLQ-FA12. We also discuss two possible ways to calculate a summarizing score when conducting a receiver operating characteristic (ROC) analysis to find the cut-off value. RESULTS: The EORTC QLQ-FA12 fit the sample (CFI = 0.96, SRMR = 0.04), had discriminant validity regarding its subscales and every subscale showed convergent validity (composite reliabilities were 0.92 for physical, 0.89 for emotional and 0.74 for cognitive fatigue). The sum of the first ten items with a range of 0 to 30 revealed a cut-off value of twelve or more with 91% sensitivity and 77% specificity. CONCLUSION: The new instrument EORTC QLQ-FA12 is able to distinguish between physical, emotional, and cognitive fatigue in young adult patients. It enables us to study different concepts of general fatigue without the need for additional items, and can be used as a screening instrument for young adults. Future research should investigate the multidimensional character of CRF.

Fatigue Risk Management: The Impact of Anesthesiology Residents' Work Schedules on Job Performance and a Review of Potential Countermeasures.

Long duty periods and overnight call shifts impair physicians' performance on measures of vigilance, psychomotor functioning, alertness, and mood. Anesthesiology residents typically work between 64 and 70 hours per week and are often required to work 24 hours or overnight shifts, sometimes taking call every third night. Mitigating the effects of sleep loss, circadian misalignment, and sleep inertia requires an understanding of the relationship among work schedules, fatigue, and job performance. This article reviews the current Accreditation Council for Graduate Medical Education guidelines for resident duty hours, examines how anesthesiologists' work schedules can affect job performance, and discusses the ramifications of overnight and prolonged duty hours on patient safety and resident well-being. We then propose countermeasures that have been implemented to mitigate the effects of fatigue and describe how training programs or practice groups who must work overnight can adapt these strategies for use in a hospital setting. Countermeasures include the use of scheduling interventions, strategic naps, microbreaks, caffeine use during overnight and extended shifts, and the use of bright lights in the clinical setting when possible or personal blue light devices when the room lights must be turned off. Although this review focuses primarily on anesthesiology residents in training, many of the mitigation strategies described here can be used effectively by physicians in practice.

Cross-Cultural Validation of the Korean Version of the Chalder Fatigue Scale.

PURPOSE: University students are vulnerable to fatigue. If not adequately dealt with, fatigue might develop into various health problems and negatively affect quality of life (QOL). The present study examined psychometric properties of the Korean version of the Chalder Fatigue Scale (K-CFQ) in university students. METHOD: Data were obtained from two samples of undergraduate students in Korea. The first dataset (N = 557) was collected in a cross-sectional survey in 2015 and the second dataset (N = 338) from a longitudinal survey with three time points over a semester period in 2016. Participants completed measures of fatigue, QOL, depression, anxiety, and sleep quality. RESULTS: Three-factor model (physical fatigue, low energy, and mental fatigue) rather than the original two-factor model (physical and mental fatigue) provided a better goodness of fit indices to the data. Internal consistency of the K-CFQ was satisfactory, with Cronbach's α value of 0.88 for the total scale and those of subscales ranging from 0.73 to 0.87. Its convergent validity was supported by its significant association with anxiety, depression, sleep quality, and QOL. Significant association between T1 K-CFQ with physical QOL at T2 and T3 supported its predictive validity. Its known-group validity was proven with higher K-CFQ scores observed in the participants with depression and those with poor sleep quality. CONCLUSIONS: Current results suggest that K-CFQ is a valid and reliable measure of fatigue, and a better model fit of the three-factor structure of the K-CFQ implies potential cross-cultural differences in the dimensionality of fatigue.

Measurement properties of the Chinese version of the Mental Fatigue Scale for patients with traumatic brain injury.

OBJECTIVES: To translate the Mental Fatigue Scale into a Chinese version (CMFS), to develop a more valid and precise CMFS by using an item response theory-based model, and to examine the reliability and validity of the CMFS. METHODS: One hundred and fifty adults having traumatic brain injury for at least 6 months were included. Each participant completed a battery of questionnaires (i.e. the Chinese version of the Chalder Fatigue Scale [ChCFS], Chinese version of the Clinically Useful Depression Outcome Scale [CUDOS-Chinese], and CMFS). Two-parameter graded response models were used to evaluate the location and discrimination performance of the CMFS. The reliability and validity of the CMFS were also evaluated. RESULTS: One item investigating 'increased sleep at night' (item 14) was removed because it had a low discrimination value (0.86) and provided less information. The internal consistency and test-retest reliability of the 13-item CMFS were high (0.92 and 0.96, respectively). The CMFS score was positively correlated with the ChCFS and the CUDOS-Chinese scores (r = 0.77 and 0.80, respectively). CONCLUSION: The CMFS provides reliable and valid information on mental fatigue for future research and clinical practice involving patients with traumatic brain injury.

Operationalising cognitive fatigability in multiple sclerosis: A Gordian knot that can be cut?

BACKGROUND: Researchers have attempted to operationalise objective measures of cognitive fatigability in multiple sclerosis (MS) to overcome the perceived subjectivity of patient-reported outcomes of fatigue (PROs). Measures of cognitive fatigability examine decrements in performance during sustained neurocognitive tasks. OBJECTIVE: This personal viewpoint briefly summarises available evidence for measures of cognitive fatigability in MS and considers their overall utility. RESULTS: Studies suggest there may be a construct that is distinct from self-reported fatigue, reflecting a new potential intervention target. However, assessments vary and findings across and within measures are inconsistent. Few measures have been guided by a coherent theory, and those identified are likely to be influenced by other confounds, such as cognitive impairment caused more directly by disease processes, depression and assessment biases. CONCLUSION: Future research may benefit from (a) developing a guiding theory of cognitive fatigability, (b) examining ecological and construct validity of existing assessments and (c) exploring whether the more promising cognitive fatigability measures are correlated with impaired functioning after accounting for possible confounds. Given the issues raised, we caution that our purposes as researchers may be better served by continuing our search for a more objective cognitive fatigability construct that runs in parallel with improving, rather than devaluing, current PROs.

Development and Validation of the State-Trait Inventory of Cognitive Fatigue in Community-Dwelling Older Adults.

OBJECTIVE: To develop and validate a subjective measure of cognitive fatigue-the State-Trait Inventory of Cognitive Fatigue-in community-dwelling older adults. DESIGN: Scale development and test construction. SETTING: Community-dwelling older adults enrolled in a longitudinal cohort aging study. PARTICIPANTS: Participants (N=175) were healthy, English-speaking, community-dwelling adults, age ≥65 years. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: State-Trait Inventory of Cognitive Fatigue total, cognitive fatigue, motivation, mental effort, and boredom summation scores for both state and trait forms. RESULTS: Principal component analysis yielded the expected 4 components for both state and trait forms: cognitive fatigue, mental effort, motivation, and boredom. All components had good reliability. There was good convergent validity as measured by the strong positive relation between cognitive fatigue and a subjective measure of general fatigue, even after controlling for depressive symptoms. Greater subjective cognitive fatigue was associated with worse performance on measures thought to be more sensitive to aspects of executive functioning. CONCLUSIONS: This study developed and established the psychometric properties of a new instrument for the subjective measurement of cognitive fatigue for use in community-dwelling older adults. The State-Trait Inventory of Cognitive Fatigue's relatively brief administration time (<10min; mean, 5.6±2.9) and strong psychometric properties support its utility in both research and clinical settings. Future studies should establish the psychometric properties of this scale in other populations and examine its predictive utility for relevant clinical outcomes.

Assessment and treatment of mental fatigue after a traumatic brain injury.

Mental fatigue is a frequently occurring symptom after mild, moderate or severe traumatic brain injury (TBI). Such mental fatigue may become a long-lasting problem, irrespective of severity and even after recovery from other neurological or psychiatric symptoms. Two characteristics of this mental fatigue are that patients easily become exhausted and there is generally a long recovery time. There is a need to increase knowledge and awareness of mental fatigue as it interferes considerably with work, studies, and social activities. Assessment is difficult and few treatment studies have been carried out. For the purposes of assessment, the development of the Mental Fatigue Scale is described here, and we also summarise the few treatment studies found for fatigue after TBI. Symptom alleviation is reported through Mindfulness-Based Stress Reduction (MBSR), light therapy and for the psychostimulant methylphenidate and the dopamine stabiliser (-)-OSU6162. However, more knowledge of the origin of mental fatigue and its underlying mechanisms is needed for development of more efficient therapeutic methods. Prospective randomised trials focusing on long-term outcomes are warranted and should include both pharmacological and non-pharmacological treatments.

Predictors of cognitive and physical fatigue in post-acute mild-moderate traumatic brain injury.

Post-traumatic fatigue (PTF) is a common, disabling, and often chronic symptom following traumatic brain injury (TBI). Yet, the impact of chronic cognitive and physical fatigue and their associations with psychiatric, sleep, cognitive, and psychosocial sequelae in mild-moderate TBI remain poorly understood. Sixty Veterans with a history of mild-moderate TBI and 40 Veteran controls (VC) were administered the Modified Fatigue Impact Scale, a validated measure of TBI-related cognitive and physical fatigue as well as measures of neuropsychiatric, psychosocial, sleep, and objective cognitive functioning. Compared to VC, TBI Veterans endorsed significantly greater levels of cognitive and physical fatigue. In TBI, psychiatric symptoms, sleep disturbance, and post-traumatic amnesia (PTA) were associated with both cognitive and physical fatigue, while loss of consciousness (LOC) and poor attention/processing speed were related to elevations in cognitive fatigue only. In regression analyses, anxiety, sleep disturbance, and LOC significantly predicted cognitive fatigue, while only post-traumatic stress symptoms and PTA contributed to physical fatigue. Cognitive and physical fatigue are problematic symptoms following mild-moderate TBI that are differentially associated with specific injury and psychiatric sequelae. Findings provide potential symptom targets for interventions aimed at ameliorating fatigue, and further underscore the importance of assessing and treating fatigue as a multi-dimensional symptom following TBI.

Investigating the effects of caffeine on executive functions using traditional Stroop and a new ecologically-valid virtual reality task, the Jansari assessment of Executive Functions (JEF(©)).

OBJECTIVE: Caffeine has been shown to have effects on certain areas of cognition, but in executive functioning the research is limited and also inconsistent. One reason could be the need for a more sensitive measure to detect the effects of caffeine on executive function. This study used a new non-immersive virtual reality assessment of executive functions known as JEF(©) (the Jansari Assessment of Executive Function) alongside the 'classic' Stroop Colour-Word task to assess the effects of a normal dose of caffeinated coffee on executive function. METHOD: Using a double-blind, counterbalanced within participants procedure 43 participants were administered either a caffeinated or decaffeinated coffee and completed the 'JEF(©)' and Stroop tasks, as well as a subjective mood scale and blood pressure pre- and post condition on two separate occasions a week apart. JEF(©) yields measures for eight separate aspects of executive functions, in addition to a total average score. RESULTS: Findings indicate that performance was significantly improved on the planning, creative thinking, event-, time- and action-based prospective memory, as well as total JEF(©) score following caffeinated coffee relative to the decaffeinated coffee. The caffeinated beverage significantly decreased reaction times on the Stroop task, but there was no effect on Stroop interference. CONCLUSION: The results provide further support for the effects of a caffeinated beverage on cognitive functioning. In particular, it has demonstrated the ability of JEF(©) to detect the effects of caffeine across a number of executive functioning constructs, which weren't shown in the Stroop task, suggesting executive functioning improvements as a result of a 'typical' dose of caffeine may only be detected by the use of more real-world, ecologically valid tasks.

Listening effort and fatigue: what exactly are we measuring? A British Society of Audiology Cognition in Hearing Special Interest Group 'white paper'.

OBJECTIVE: There is growing interest in the concepts of listening effort and fatigue associated with hearing loss. However, the theoretical underpinnings and clinical meaning of these concepts are unclear. This lack of clarity reflects both the relative immaturity of the field and the fact that research studies investigating listening effort and fatigue have used a variety of methodologies including self-report, behavioural, and physiological measures. DESIGN: This discussion paper provides working definitions for listening effort and listening-related fatigue. Using these definitions as a framework, methodologies to assess these constructs are reviewed. RESULTS: Although each technique attempts to characterize the same construct (i.e. the clinical presentation of listening effort and fatigue), different assumptions are often made about the nature of these phenomena and their behavioural and physiological manifestations. CONCLUSION: We suggest that researchers consider these assumptions when interpreting their data and, where possible, make predictions based on current theoretical knowledge to add to our understanding of the underlying mechanisms of listening effort and listening-related fatigue. FOREWORD: Following recent interest in the cognitive involvement in hearing, the British Society of Audiology (BSA) established a Special Interest Group on Cognition in Hearing in May 2013. In an exploratory group meeting, the ambiguity surrounding listening effort and fatigue was discussed. To address this problem, the group decided to develop a 'white paper' on listening effort and fatigue. This is a discussion document followed by an international set of commentaries from leading researchers in the field. An approach was made to the editor of the International Journal of Audiology who agreed to this suggestion. This paper, and the associated commentaries that follow, are the result.

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.

Evaluating the Stroop Test With Older Adults: Construct Validity, Short Term Test-Retest Reliability, and Sensitivity to Mental Fatigue.

We conducted two studies to evaluate the construct validity, short term test-retest reliability, and sensitivity to mental fatigue of the Stroop task when used with older adults. In Study 1, 40 participants visited our lab on two separate days. On the first visit, they took five screening scales, and we measured their height and body mass. On the second visit, they completed the Stroop task twice with a 30-minute interval between assessments. In Study 2, 15 different participants took a 30-minute Flanker/Reverse Flanker task during the interval between the two administrations of the Stroop tasks and they gave subjective ratings of their mental fatigue on the Visual Analogue Scale (VAS) prior to taking either of the Stroop tasks. In Study 1, participants showed a ceiling effect on the Stroop accuracy measure, there was strong concurrent validity for the Stroop with significant score differences between the Stroop's congruent and incongruent conditions (p < .001), and there was excellent response time reliability (ICC = 0.926) on day two when participants took the Stroop twice within a 30-minute inter-test interval. However, there were significant test-retest performance differences with respect to cognitive inhibition (p < .001). In Study 2, mental fatigue from the Flanker/Reverse Flanker test resulted in a significantly worse second Stroop performance (p = .045). We concluded that the Stroop task demonstrated strong concurrent validity and response time reliability among older adults, but it showed sensitivity to mental fatigue, and repeated administrations within the short 30-minute test-retest interval revealed that the most important Stroop measure (cognitive inhibition) was unreliable. We discuss the implications of these findings.

Mental fatigue recognition study based on 1D convolutional neural network and short-term ECG signals.

BACKGROUND: Mental fatigue has become a non-negligible health problem in modern life, as well as one of the important causes of social transportation, production and life accidents. OBJECTIVE: Fatigue detection based on traditional machine learning requires manual and tedious feature extraction and feature selection engineering, which is inefficient, poor in real-time, and the recognition accuracy needs to be improved. In order to recognize daily mental fatigue level more accurately and in real time, this paper proposes a mental fatigue recognition model based on 1D Convolutional Neural Network (1D-CNN), which inputs 1D raw ECG sequences of 5 s duration into the model, and can directly output the predicted fatigue level labels. METHODS: The fatigue dataset was constructed by collecting the ECG signals of 22 subjects at three time periods: 9:00-11:00 a.m., 14:00-16:00 p.m., and 19:00-21:00 p.m., and then inputted into the 19-layer 1D-CNN model constructed in the present study for the classification of mental fatigue in three grades. RESULTS: The results showed that the model was able to recognize the fatigue levels effectively, and its accuracy, precision, recall, and F1 score reached 98.44%, 98.47%, 98.41%, and 98.44%, respectively. CONCLUSION: This study further improves the accuracy and real-time performance of recognizing multi-level mental fatigue based on electrocardiography, and provides theoretical support for real-time fatigue monitoring in daily life.

The measurement of mental fatigue following an overnight on-call duty among doctors using electroencephalogram.

This study aimed to measure the spectral power differences in the brain rhythms among a group of hospital doctors before and after an overnight on-call duty. Thirty-two healthy doctors who performed regular on-call duty in a tertiary hospital in Sarawak, Malaysia were voluntarily recruited into this study. All participants were interviewed to collect relevant background information, followed by a self-administered questionnaire using Chalder Fatigue Scale and electroencephalogram test before and after an overnight on-call duty. The average overnight sleep duration during the on-call period was 2.2 hours (p<0.001, significantly shorter than usual sleep duration) among the participants. The mean (SD) Chalder Fatigue Scale score of the participants were 10.8 (5.3) before on-call and 18.4 (6.6) after on-call (p-value < 0.001). The theta rhythm showed significant increase in spectral power globally after an overnight on-call duty, especially when measured at eye closure. In contrast, the alpha and beta rhythms showed reduction in spectral power, significantly at temporal region, at eye closure, following an overnight on-call duty. These effects are more statistically significant when we derived the respective relative theta, alpha, and beta values. The finding of this study could be useful for development of electroencephalogram screening tool to detect mental fatigue.