Feature Selection for EEG-Based Fatigue Analysis Using Pearson Correlation

The objective was to study changes in EEG time-domain Kolmogorov complexity under different mental fatigue state and to evaluate mental fatigue using Lempel-Ziv complexity analysis of spontaneous EEG in healthy human subjects. EEG data for healthy subjects were acquired using a net of 2 electrodes (Fp1 and Fp2) at PM 4:00, AM 12:00 and AM 3:00 in the 24 hours sleep-deprived mental fatigue experiments. It was presented that initial results for eight subjects examined in three different mental fa-tigue state with 2-channel EEG time-domain Lempel-Ziv complexity computations. It was found that the value of mean Lempel-Ziv com-plexity corresponding to a special mental state fluctuates within the special range and the value of C(n) increases with mental fatigue increasing for the total frequency spectrum. The result in-dicates that the value of C(n) is strongly cor-relative with the mental fatigue state. These re-sults suggest that it may be possible to nonin-vasively differentiate different mental fatigue level according to the value of C(n) for particular mental state from scalp spontaneous EEG data. This method may be useful in further research and efforts to evaluate mental fatigue level ob-jectively. It may also provide a basis for the study of effects of mental fatigue on central neural system.

Introduction: Fatigue is a gradual and cumulative process. This mindset is related to the lack of motivation to make any effort, as well as decreased efficiency, attentiveness, and, eventually, malfunction. Aim: The present study aims to investigate how mental and muscle fatigue affects spatial working memory. Method: The research method was quasi-experimental and was performed using the pretestposttest design. The participants in this study were 20 to 30 year old male students of Shahid Beheshti University of Tehran in 2021, of whom, 14 subjects were selected by convincing method as the sample using the G-Power approach and previous investigations. The Mental Fatigue Self-Assessment Scale, Corsi Block software, Stroop software, and the Monark Bike Ergometer were utilized. In addition, the repeated measurement analysis of variance test in SPSS-23 was used to analyze the data. Results: The results indicated that mental fatigue condition had a significant effect on working memory (P=0.002); and has reduced the efficiency of working memory. But muscle fatigue conditions had no significant effect on assessing working memory, and in these conditions there was a better performance in working memory (P=0.065). Conclusion: The findings of this study emphasize the importance of mental fatigue in reducing working memory performance, even though this type of fatigue is related to cognitive and cerebral functioning. Accordingly, the findings are in line with a top-down approach, as well as cognitive perspectives such as generalized motor program theory.

Health has effects on children's academic performance. Qi deficiency is generally used to assess an individual's health in the Chinese traditional medicine theory. This study explores the effects of qi deficiency on children's academic performance and examines whether mental fatigue mediates these effects. A total of 550 students aged 10-13 in fifth-grade were surveyed in a big primary school in Sichuan Province in November 2023 using paper-pencil-based questionnaires. Qi deficiency and mental fatigue were assessed, and exam scores in Chinese and Mathematics were recorded. Pearson's correlation and linear regression analyses were used to test the mediation model and hypotheses. The fifth-grade students had mild qi deficiency (M = 2.09) and a mild state of mental fatigue (M = 2.38) on a five-point Likert scale. The average exam scores in Mathematics and Chinese were 70.07 and 74.44 points out of 100, respectively. Qi deficiency was associated with Mathematics scores (r = -0.37, p < 0.01) and Chinese scores (r = -0.30, p < 0.01), and mental fatigue (r = 0.47, p < 0.01). Furthermore, mental fatigue was associated with Mathematics scores (r = -0.46, p < 0.01) and Chinese scores (r = -0.34, p < 0.01). Linear regression analyses showed that qi deficiency significantly predicted Mathematics scores (β = -0.26, p < 0.01), Chinese scores (β = -0.19, p < 0.01), and mental fatigue (β = 0.41, p < 0.01). When qi deficiency was controlled for, mental fatigue significantly predicted Mathematics scores (β = -0.28, p < 0.01) and Chinese scores (β = -0.17, p < 0.01). The mediation model and hypotheses were well supported, indicating that mental fatigue mediated the influence of qi deficiency on academic performance of fifth-grade students. Furthermore, the mediation effect of mental fatigue on Mathematics scores was a little stronger than that on Chinese scores.

After long time cognitive work, most of people confronted with the mental fatigue, which can decrease the classification accuracy of cognitive, or even cause the traffic accidents for drivers. Therefore, the detection of the fatigue state is very essential. The study aims to explore an effective and novel approach based on electroencephalogram. All participants were instructed to implement the spelling experiments. Data were recorded on the awake condition, on sleep deprivation condition and after two hour spelling experiment. To comprehensively quantify the state of mental fatigue, spectral non-negative matrix factorization and a quantification fatigue index were proposed in the data analysis. The results indicated that the quantification fatigue index significantly increased with the greater level of fatigue (p <; 0.05), and this method we proposed can discriminate the different state of fatigue. Thus this method is promising in detecting the state of mental fatigue with electroencephalogram.

It has been shown that the mental fatigue induced by prolonged self-regulation increases perception of effort and reduces performance during subsequent endurance exercise. However, the physiological mechanisms underlying these negative effects of mental fatigue are unclear. The primary aim of this study was to test the hypothesis that mental fatigue exacerbates central fatigue induced by whole-body endurance exercise. Twelve subjects performed 30 min of either an incongruent Stroop task to induce a condition of mental fatigue or a congruent Stroop task (control condition) in a random and counterbalanced order. Both cognitive tasks (CTs) were followed by a whole-body endurance task (ET) consisting of 6 min of cycling exercise at 80% of peak power output measured during a preliminary incremental test. Neuromuscular function of the knee extensors was assessed before and after CT, and after ET. Rating of perceived exertion (RPE) was measured during ET. Both CTs did not induce any decrease in maximal voluntary contraction (MVC) torque (p = 0.194). During ET, mentally fatigued subjects reported higher RPE (mental fatigue 13.9 ± 3.0, control 13.3 ± 3.2, p = 0.044). ET induced a similar decrease in MVC torque (mental fatigue –17 ± 15%, control –15 ± 11%, p = 0.001), maximal voluntary activation level (mental fatigue –6 ± 9%, control –6 ± 7%, p = 0.013) and resting twitch (mental fatigue –30 ± 14%, control –32 ± 10%, p < 0.001) in both conditions. These findings reject our hypothesis and confirm previous findings that mental fatigue does not reduce the capacity of the central nervous system to recruit the working muscles. The negative effect of mental fatigue on perception of effort does not reflect a greater development of either central or peripheral fatigue. Consequently, mentally fatigued subjects are still able to perform maximal exercise, but they are experiencing an altered performance during submaximal exercise due to higher-than-normal perception of effort.

Impact of depression on mental fatigue and attention in patients with multiple sclerosis

This study aims to determine Full Day School Management in SMA As Syafi’iyah Medan, Jl. Karya Wisata Ii No.1,Medan Johor, Medan, North Sumatra Province. This research is a qualitative popoulasi study of the Full Day School teacher and management and students of SMA As Syafi’iyah Medan. In an effort to improve student character education in MAN 2, the terrain model includes stages, namely: planning Full Day School learning, implementing Full Day School learning and evaluating Full Day School learning. Learning planning is adapted to the curriculum adopted by SMA As Syafi’iyah Medan, namely the government curriculum, local curriculum and school curriculum and the formulation of syllabus and plan for implementing learning. The implementation of Full Day School learning consists of habituation activities, exemplary activities, nationalism and patriotism activities and student creativity activities. Evaluation Full Day School learning in general in Medan Model 2 MAN 2 in determining minimal completeness provides an assessment of three domains, namely cognitive, affective and domain psychomotor.

This study aims to obtain a description of the visionary leadership of the principal in the implementation of the full day school program at MI Modern Al Azhary Ajibarang. This research is a type of field research that uses a qualitative approach. The data were collected by interviewing, observing and documenting then being analyzed through the stages of data reduction, data presentation, and data verification. The results showed that there were five strategies applied in visionary leadership at MI Modern Al Azhary Ajibarang. First, to focus leadership practices on the goals of the full day school program. Second, make short-term and long-term plans for the full day school program. Third, focus on achieving the vision for a successful full day school program. Fourth, responding to various changes made by the full day school program. Fifth, respond to the needs of teachers and student guardians in the implementation of full day school.

This study investigated the impact of mental fatigue and self-controlled versus yoked feedback on learning a force production task. We randomly assigned 44 non-athlete male students (Mage = 21.4, SD = 1.4 years) to four groups; (a) MF&SCF = mental fatigue & self-controlled feedback, (b) MF&Y = mental fatigue & yoked, (c) NMF&SCF = no mental fatigue & self-controlled feedback, and (d) NMF&Y = no mental fatigue & yoked). SCF group participants were provided feedback whenever they requested it, while YK group participants received feedback according to a schedule created by their SCF counterparts. To induce mental fatigue, participants performed a Stroop color-word task for one hour. During the acquisition (practice) phase, participants were asked to produce a given percentage of their maximum force (20%) in 12 blocks of six trials. We recorded the participants' absolute error at the end of the acquisition phase, the immediate retention test, the first transfer test, and the second transfer test (after 24 hours and without any further mental fatigue). The acquisition phase data were analyzed in a 2 (feedback) × 2 (mental fatigue) × 12 (block) ANOVA with repeated measures on the last factor, while the retention and transfer data were analyzed in 2 (feedback) × 2 (mental fatigue) ANOVAs. We found that all four groups made significant progress during practice (p < .001), but there were no significant group differences during this phase (p>.05). There was a significant interaction effect of self-controlled feedback and mental fatigue at retention (p = .018) and transfer testing (p < .001). In the mental fatigue condition, participants in the self-controlled group had poorer learning compared to participants in the yoked group; but when not mentally fatigued, participants in the self-controlled group had better learning than those in the yoked group. These findings suggest that mental fatigue reduces typical advantages of self-controlled feedback in motor learning.

Modern mental fatigue detection methods include many parameters for evaluation. For example, many researchers use human subjective evaluation or driving parameters to assess this human condition. Development of a method for detecting the functional state of mental fatigue is an extremely important task. Despite the fact that human operator support systems are becoming more and more widespread, at the moment there is no open-source solution that can monitor this human state based on eye movement monitoring in real time and with high accuracy. Such a method allows the prevention of a large number of potential hazardous situations and accidents in critical industries (nuclear stations, transport systems, and air traffic control). This paper describes the developed method for mental fatigue detection based on human eye movements. We based our research on a developed earlier dataset that included captured eye-tracking data of human operators that implemented different tasks during the day. In the scope of the developed method, we propose a technique for the determination of the most relevant gaze characteristics for mental fatigue state detection. The developed method includes the following machine learning techniques for human state classification: random forest, decision tree, and multilayered perceptron. The experimental results showed that the most relevant characteristics are as follows: average velocity within the fixation area; average curvature of the gaze trajectory; minimum curvature of the gaze trajectory; minimum saccade length; percentage of fixations shorter than 150 ms; and proportion of time spent in fixations shorter than 150 milliseconds. The processing of eye movement data using the proposed method is performed in real time, with the maximum accuracy (0.85) and F1-score (0.80) reached using the random forest method.

<h3>Background</h3> A lot of controversy exists about how fatigue affects injury risk. Within the fatigue spectrum, mental fatigue impairs visuomotor skills, reaction time and decision-making. Recently, adaptability has been put forward as an important driver in understanding injury occurrence and injury prevention. It is hypothesised that mental fatigue decreases an athlete’s adaptability by means of an increased visuomotor reaction time and diminished ability for decision-making and visuomotor skill execution. <h3>Objective</h3> To assess the impact of mental fatigue on functional tests used in injury risk profiling and if mental fatigue decreases an athlete adaptability. <h3>Design</h3> Randomized counterbalanced cross-over design. <h3>Setting</h3> Primary prevention. <h3>Participants</h3> Fourteen healthy participants (age = 22 ± 1 years; height = 176.9 ± 8.4 cm; weight = 69.7 ± 10.4 kg). <h3>Interventions</h3> Mental fatigue was induced by a 90-minute 100% incongruent Stroop color word test, while the control task included watching a 90-minute documentary. <h3>Main Outcome Measurements</h3> Y-balance test (YBT), Reactive balance test (RBT), Single leg hop test (SLH) and countermovement jump (CMJ) performance was evaluated pre-post mental fatigue. Mental fatigue was evaluated using the M-VAS, Stroop and Eriksen-Flanker task performance outcomes. <h3>Results</h3> Mental fatigue was successfully induced at the subjective level with a significant increase in M-VAS (p&lt;0.001), with no decrease in performance on the Stroop and Eriksen-Flanker task. Mental fatigue did not affect YBT, SLH and the CMJ performance. However, RBT accuracy significantly decreased in mental fatigue condition (p=0.024), while the visuomotor reaction time of the RBT remained unaffected. <h3>Conclusions</h3> This is the first experiment to illustrate that mental fatigue affects functional adaptability, as accuracy in response to environmental stimuli decreases. However, traditional functional test perfmance remains unaffected. Therefore, both neurocognitive functional tests and mental fatigue responses should be considered within injury risk profiling strategies. Prospective study designs within the injury prevention domain should include neurocognitive functional tests to investigate the possible relationship of these tests with sports injuries.

Purpose. The purpose of the article is the formation of theoretical, methodological and practical foundations for the implementation of marketing tools to assess the impact of consumer fatigue from making everyday decisions on brand loyalty and purchasing behaviour in stores. Methodology of research. The theoretical and methodological basis of the article was formed by the provisions of behavioural economics, neuro-marketing, and branding. The study is based on the dialectical method of learning the influence of consumer fatigue from decision-making on brand loyalty. General scientific and special methods are used within the limits of the mentioned approach, in particular: comparison – to determine the advantages and disadvantages of different groups of marketing tools; questionnaire survey – for a pilot study of the criteria for making a decision on the purchase of goods by consumers in stores; mathematical modelling – for evaluating the data obtained during the experiment and determining the tendencies of choosing the company's product or brand by consumers during fatigue; analysis and synthesis – to form a mechanism for the implementation of neuro-marketing tools by companies; induction and deduction – to interpret conclusions based on research results. Findings. The phenomenon of consumer decision fatigue resulting from repeated choice-making is explored, leading to mental exhaustion and impaired behaviour control, affecting brand loyalty. A concept is formulated for the application of neuro-marketing tools to understand consumer behaviour in retail stores, which engages all human sensory organs, including audio influence, visualization, tactile stimulation, scent influence, and taste stimulation. Pilot study of the purchasing behaviour of consumers in a state of physical or mental fatigue and without it was conducted. It has been established that closer to the evening, consumer fatigue from decision-making is observed, as during the day people may be under the influence of stressful factors, depleting emotional and cognitive resources. The factors that are important in making a decision regarding the choice of a product of a certain brand are singled out. The hypothesis regarding the influence of consumer fatigue from decision-making on the formation of brand loyalty was confirmed. Originality. The concept is formulated of using neuromarketing tools for a better understanding of consumer behavior in stores, a more detailed analysis of the decision-making process and their purchasing behavior, the formation of habits and loyalty to company brands, consumer reactions to product packaging and labeling in a state of fatigue. Practical value. The results of the pilot study will help create more effective marketing campaigns using a personalized approach to consumers and simplified communication. Key words: consumer behaviour, decision fatigue, marketing, shopping in stores, brand loyalty, neuro-marketing.

Mental fatigue (MF) is a common phenomenon in our daily lives. In the workplace, mental fatigue can increase the risk of human errors. Moreover, if it is not detected and handled correctly, it can cause various problems. Electroencephalogram (EEG) is one of many modalities that is widely used by researchers for detecting mental fatigue. However, due to the difficulty in provoking fatigue condition during the EEG measurement, this study proposed two experimental designs for detecting mental fatigue, the first design is by using physical induction (PI) and the 2nd design is by using mental induction (MI). We obtained the EEG signals from 20 healthy participants, from 14 channels of wireless EEG headset. Each participant was given four types of cognitive tests in the form of a computer game including Trail, Span, Stroop, and Arithmetic. The subjective measurement of fatigue condition was measured by using the Swedish Occupational Fatigue Inventory (SOFI) questionnaires. The EEG signal was extracted by using power percentage (PP) features of alpha ( $\alpha$ ), beta ( $\beta$ ), and theta ( $\theta$ ) bands of frequency from all channels. As for classification, we introduced the use Relevance Vector Machine (RVM) approach which is claimed to have better performance than SVM as the precedence method. According to the results, all of the cognitive tests has increased average value of response time (RT) and decreased correction score (CS) on post-induction compared to pre-induction. Another result showed that the best mental fatigue detection is obtained from mental induction rather than physical induction. The classification results demonstrate an accuracy of 93.7% (MI) and 92.6% (PI) are achieved by RVM approach. Furthermore, RVM has also less execution time compared to SVM.

This study aims to understand perceptions of teachers, education personnel, students and parents about full day school education program; basic concepts of full day school education; factors driving or impeding the implementation of full day school education at research site; and follow-up of full day school program in the future. This research used quantitative and qualitative approach with descriptive method and rely on data collection technique from spreading questionnaire, observation, interview, documentation, and literature study. Data analysis techniques used description analysis techniques. The population in this study were teachers who were given additional task as vice principal at State Madrasah Tsanawiyah (MTs) 1 Serang, student and parents in class VIII as representative respondents. Processing and data analysis was done gradually, along with the emergence and development of information input from research subjects. The conclusion of this study is teachers and education personnel of State MTs 1 Serang agreed to implement full day school education program, in order to: prepare themselves to face the era of competition in economic society of ASEAN environment; strengthen the motivation and competition of student learning process; improve work motivation and performance of teachers and administrative staff; also maintaining the establishment of happy and prosperous families by using "Saturday" as a family holiday.

Mental fatigue is, for many, a very distressing and long-term problem after a traumatic brain injury (TBI) or stroke. This will make it more difficult for the individual to return to work and resume social activities, and it can take several years to find the right balance between rest and activity in daily life, to find strategies and to accept the new situation. The aim of this study was to evaluate the effect of an advanced mindfulness program following a MBSR program, designed for subjects suffering from long-term mental fatigue after a brain injury. The advanced program was based on The Brahma Viharas, meditative practices known for cultivating four mental states: compassion, metta, appreciative joy, and equanimity. Fourteen participants followed the 8-month advanced mindfulness program, with group visits once a month and a final all-day retreat. All the participants were suffering from mental fatigue at least 1 year after a brain injury following a stroke or a TBI. The assessments after the advanced program showed a significant and sustained positive effect on mental fatigue and on tests measuring information processing speed and attention. With mindfulness practice it was possible to improve wakefulness during meditation and, above all, improve the mental fatigue levels. We propose that mindfulness is a promising treatment for mental fatigue after a stroke or TBI.