Fatigue Conditions Research Articles

Human Operator Mental Fatigue Assessment Based on Video: ML-Driven Approach and Its Application to HFAVD Dataset

The detection of the human mental fatigue state holds immense significance due to its direct impact on work efficiency, specifically in system operation control. Numerous approaches have been proposed to address the challenge of fatigue detection, aiming to identify signs of fatigue and alert the individual. This paper introduces an approach to human mental fatigue assessment based on the application of machine learning techniques to the video of a working operator. For validation purposes, the approach was applied to a dataset, “Human Fatigue Assessment Based on Video Data” (HFAVD) integrating video data with features computed by using our computer vision deep learning models. The incorporated features encompass head movements represented by Euler angles (roll, pitch, and yaw), vital signs (blood pressure, heart rate, oxygen saturation, and respiratory rate), and eye and mouth states (blinking and yawning). The integration of these features eliminates the need for the manual calculation or detection of these parameters, and it obviates the requirement for sensors and external devices, which are commonly employed in existing datasets. The main objective of our work is to advance research in fatigue detection, particularly in work and academic settings. For this reason, we conducted a series of experiments by utilizing machine learning techniques to analyze the dataset and assess the fatigue state based on the features predicted by our models. The results reveal that the random forest technique consistently achieved the highest accuracy and F1-score across all experiments, predominantly exceeding 90%. These findings suggest that random forest is a highly promising technique for this task and prove the strong connection and association among the predicted features used to annotate the videos and the state of fatigue.

A New Multi-Axial Functional Stress Analysis Assessing the Longevity of a Ti-6Al-4V Dental Implant Abutment Screw

This study investigates the impact of tightening torque (preload) and the friction coefficient on stress generation and fatigue resistance of a Ti-6Al-4V abutment screw with an internal hexagonal connection under dynamic multi-axial masticatory loads in high-cycle fatigue (HCF) conditions. A three-dimensional model of the implant–abutment assembly was simulated using ANSYS Workbench 16.2 computer aided engineering software with chewing forces ranging from 300 N to 1000 N, evaluated over 1.35 × 107 cycles, simulating 15 years of service. Results indicate that the healthy range of normal to maximal mastication forces (300–550 N) preserved the screw’s structural integrity, while higher loads (≥800 N) exceeded the Ti-6Al-4V alloy’s yield strength, indicating a risk of plastic deformation under extreme conditions. Stress peaked near the end of the occluding phase (206.5 ms), marking a critical temporal point for fatigue accumulation. Optimizing the friction coefficient (0.5 µ) and preload management improved stress distribution, minimized fatigue damage, and ensured joint stability. Masticatory forces up to 550 N were well within the abutment screw’s capacity to sustain extended service life and maintain its elastic behavior.

Real-world data in lupus nephritis: results from a European survey on renal function testing and burden of disease progression

Objective Patients with lupus nephritis (LN), a severe renal manifestation of systemic lupus erythematosus, should be monitored for progression of chronic kidney disease to end-stage renal disease but data on renal function testing in LN patients are limited. This real-world analysis aimed to evaluate nephrologists’ use of renal function tests to support LN diagnosis and monitoring and to examine the impact of disease progression in LN patients in Europe. Methods Data were drawn from the Adelphi Lupus Disease Specific Programme, a cross-sectional survey of nephrologists and their next five consulting patients with LN in France, Germany, Italy, Spain, and the United Kingdom in 2021. Nephrologists provided demographic and clinical information for each patient and the same patients completed a self-reported questionnaire. Using a checkbox, patients provided informed consent to take part in the survey. Results Nephrologists (n = 72) provided data on 376 patients with LN. Estimated glomerular filtration rate (eGFR) or proteinuria testing was not undertaken in around 10% and 50% of these patients, respectively. Regression analysis predicted reduction in renal function (disease progression) following LN diagnosis whilst bivariate analyses showed significantly worse outcomes for patients with progressed disease: worse pain, fatigue, treatment satisfaction, and patient-reported health state and activity impairment. Conclusion Our study revealed lower-than-expected nephrologist-reported use of renal function testing to support diagnosis/monitoring of patients with LN in real-world clinical settings in Europe. Lower quality of life (QoL) was observed in patients with more progressed disease. Increased use of renal function testing is needed so that all LN patients are monitored closely to manage disease progression and avoid the associated QoL impact.

Circadian Rhythm and Physical Fatigue Separately Influence Cognitive and Physical Performance in Amateur Athletes

Background/Objectives: Circadian rhythm (CR) influences various physiological functions, including physical and cognitive performance, which fluctuate throughout the day. The present study aimed to investigate the combined and separate effects of CR and physical fatigue on cognitive and physical performance. Methods: A sample of 18 amateur athletes was subjected to a series of tests at three different times of the day: morning, afternoon, and evening. Fatigue was induced following an isokinetic concentric exercise combined with a 20 min treadmill run, followed by assessments of selected physical and cognitive tasks. Results: A repeated measure ANOVA did not reveal an interaction between CR and fatigue in cognitive performance (p > 0.05). However, a significant main effect of fatigue was observed in visual reaction time (VisRT) across all three timepoints. Moreover, peak torque (PT) and the peak torque fatigue index (PTFI) showed significant differences between the three times of the day, peaking in the evening. Conclusions: Although we found no interaction between CR and the physical fatigue state on selected cognitive parameters at the three times of the day, a separate effect of fatigue on cognitive performance was identified. Additionally, physical parameters exhibited peak values occurring in the evening hours. Future research should further explore underlying mechanisms that potentially influence cognitive performance at different times of the day.

Complementary Machining – Machining Strategy for Surface Modification: A Review

All fabrication techniques utilized to manufacture metallic parts modify the surface integrity of the part. Complementary machining is a relatively recent machining strategy characterized by combining metal cutting and mechanical surface treatment. Typically, it implies that after conventional machining, the cutting insert is used reversely to modify the surface by local plastic deformation. To improve product performance, mechanical surface treatment is an additional phase in the manufacturing process chain that usually results in longer production times and higher costs. As a result, a variety of hybrid techniques have been created, such as complementary machining, which has the benefit of using conventional machine tools and their associated cutting tools. The study on complementary machining is reviewed in the article. The main focus is to assess the viability of complementary machining to modify surface integrity for enhanced properties by specifically establishing its effect on tool wear, surface roughness, microhardness, fatigue, microstructure, and residual stress state.

Multilevel attention mechanism for motion fatigue recognition based on sEMG and ACC signal fusion.

This study aims to develop a cost-effective and reliable motion monitoring device capable of comprehensive fatigue analysis. It achieves this objective by integrating surface electromyography (sEMG) and accelerometer (ACC) signals through a feature fusion strategy. The study introduces a multi-level attention mechanism for classification, leveraging convolutional neural networks (CNNs). The preprocessing phase involves a local feature attention mechanism that enhances local waveform features using the amplitude envelope. A dual-scale attention mechanism, operating at both channel and neuron levels, is employed to enhance the model's learning from high-dimensional fused data, improving feature extraction and generalization. The local feature attention mechanism significantly improves the model's classification accuracy and convergence, as demonstrated in ablation experiments. The model, optimized with multi-level attention mechanisms, excels in accuracy and generalization, particularly in handling data with pseudo-artifacts. Computational analysis indicates that the proposed optimization algorithm has minimal impact on CNN's training and testing times. The study achieves recognition accuracies of 92.52%, 92.38%, and 92.30%, as well as F1-scores of 91.92%, 92.13%, and 92.29% for the three fatigue states, affirming its reliability. This research provides technical support for the development of affordable and dependable wearable motion monitoring devices.

Beyond acute infection: mechanisms underlying post-acute sequelae of COVID-19 (PASC).

Immune dysregulation is a key aspect of post-acute sequelae of coronavirus disease 2019 (PASC), also known as long COVID, with sustained activation of immune cells, T cell exhaustion, skewed B cell profiles, and disrupted immune communication thereby resulting in autoimmune-related complications. The gut is emerging as a critical link between microbiota, metabolism and overall dysfunction, potentially sharing similarities with other chronic fatigue conditions and PASC. Immunothrombosis and neurological signalling dysfunction emphasise the complex interplay between the immune system, blood clotting, and the central nervous system in the context of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Clear research gaps in the design of PASC studies, especially in the context of longitudinal research, stand out as significant areas of concern.

A deformation-diffusion interactive model to study crack-tip behaviour and predict crack growth rate under fatigue and hydrogen-embrittlement conditions

Hydrogen is accepted as a cleaner and more sustainable energy source, since it carries abundant energy and does not produce any effluent gas from burning when compared to fossil fuels. However, long-term degradation in mechanical properties, attributed to hydrogen embrittlement, is reported for metallic materials exposed to gaseous hydrogen, leading to accelerated crack growth behaviour under fatigue. In this paper, a visco-plastic deformation-diffusion interactive model is developed to study fatigue crack growth behaviour in a nickel-based superalloy under hydrogen-embrittlement condition. In the model, cyclic deformation is described by visco-plasticity constitutive model, while hydrogen diffusion is simulated by a modified form of Fick’s first law of diffusion which can address hydrogen diffusion driven by the hydrostatic stress gradient. In particular, trapped hydrogen, expressed as dependent on both diffusible hydrogen concentration and inelastic strain, is considered in the modelling of hydrogen diffusion. The model also describes the effects of hydrogen concentration on mechanical deformation by considering its influence on the evolution of isotropic hardening as well as on the strain state. Interaction between cyclic deformation and hydrogen diffusion is therefore studied for a crack tip in a compact tension specimen subjected to fatigue and hydrogen attack, showing a strong dependency on both loading frequency and stress intensity factor range. Subsequently, a two-parameter criterion is proposed for fatigue crack growth prediction, which accounts for the contributions of both cyclic deformation and hydrogen diffusion. The predictions show a good agreement with experimental data in terms of crack growth rate under fatigue and hydrogen-embrittlement conditions.

Kinetic analysis of change of direction simulating a defensive action in soccer players with and without acute fatigue.

The objective of this study is to analyse the kinetic effects of acute fatigue during a 45° change of direction executed with the non-dominant limb, emulating a typical defensive action during pressing in soccer. Seventeen male professional soccer players (age: 21.7 ± 5.4 years) performed a 45° change of direction before and after a fatigue protocol. Participants were instructed to execute an approach run as quickly as possible, to change direction with their non-dominant foot on a force platform, and then continue running with the aim of stopping against an opponent. Times, forces, impulses, and force rates for different subphases during support were compared. Speeds remained consistent across pre-fatigue (4.53 ± 0.55 m s-1) and post-fatigue (4.58 ± 0.70 m s-1) trials. The results indicated a decrease in braking time (p = 0.01), impulse associated with the braking phase (p < 0.01), and impulse during body weight lifting (p = 0.01) under acute fatigue conditions. These changes suggest that, under acute fatigue, soccer players may not decelerate sufficiently in the initial direction of the run and may raise their body less in the first step after the change of direction. Maximum force values and force rates did not show significant changes; however, they were sufficiently high to suggest a potential injury risk in both conditions.

Effect of loading frequency on tensile fatigue behavior of ultra-high-strength engineered cementitious composites

The ultra-high-strength engineering cementitious composites demonstrates pseudo strain hardening behavior when subjected to uniaxial tension, making it a promising material for enduring repeated or fatigue loads. Extensive research has been conducted on the quasi-static, dynamic, and fatigue behavior of this composites. However, due to the challenges of conducting direct tensile testing on concrete, investigations into the tensile fatigue behavior of ECC, particularly for ultra-high-strength ECC, remain limited. The fatigue behavior of concrete can be influenced by various factors. This study focuses on the impact of loading frequency. Several series of tensile fatigue tests were conducted under different loading frequencies and stress levels. The test results revealed that fatigue life increases with higher applied loading frequencies and decreases with increasing stress levels. The analysis of the test results includes the examination of failure modes, fatigue life, deformation, and secondary strain rates. A probabilistic model of fatigue failure, considering the discreteness of the initial static strength, was proposed based on the fatigue life. This model aligned well with the experimental results, providing valuable insights into the behavior of ultra-high-strength ECC under tensile fatigue conditions

The Impact of a Congested Match Schedule (Due to the COVID-19 Lockdown) on Creatine Kinase (CK) in Elite Football Players Using GPS Tracking Technology

The aim was to analyse the consequences of a congested schedule (due to the COVID-19 lockdown) on creatine kinase (CK) in elite football players using GPS tracking technology. A total of 17 elite football players were monitored in training and competition with a global positioning system. Variables including total distance, high-intensity distance, and distance acceleration and deceleration were analysed. Different measurements of serum creatine kinase (CK) concentration were performed on match day (MD) and at 24 h (MD+1), 48 h (MD+2), and 72 h (MD+3) after each match to study the muscle damage of each individual player caused during the match. The results showed a significant increase in physical demands in training (in relative terms regarding the match) at MD+3 compared to MD+1 and MD+2. Furthermore, at +72 h, CK decreases to a value almost the same as that before MD. On the other hand, the players with lower demands for high-intensity actions in the match showed a higher reduction in the concentration of CK at MD+3 compared to MD+1 and MD+2 (p &lt; 0.05). It became evident that players with high-intensity demand and a high number of accelerations and decelerations need more time to assimilate the match load and can remain in a state of muscle fatigue for up to 3 days. In addition, a congested schedule can lead to a state of chronic fatigue in elite football players, limiting physical performance and possibly increasing the potential risk of injury for football players.

Study of Vibration‐Ultrasonic Combined Fatigue on 7075‐T6 Aluminum Alloy

ABSTRACTComponents in aero‐engine are likely excited in multiple resonance models in dynamic loads. This paper proposes an accelerated fatigue testing method that combines the vibration test with ultrasonic loading to develop a feasible experimental system for combined cycle fatigue (CCF) and explore the CCF characteristics in the high cycle fatigue (HCF) associated with very high cycle fatigue (VHCF) conditions. A thin plate specimen of 7075‐T6 aluminum alloy with two natural frequencies of 2 and 20 kHz is designed for the experiment. The stress waveform and distribution during real‐time monitoring provide validation for the method. Finally, the influences of composite loads are demonstrated by exploring the characteristics of the S–N curves and fracture morphology. The results suggest that the increase in both axial and bending stress markedly diminishes fatigue life, while the difference in stress levels under combined loading is revealed through variations in fatigue striation morphology.

Clustering for mitigating subject variability in driving fatigue classification using electroencephalography source-space functional connectivity features.

While Electroencephalography (EEG)-based driver fatigue state classification models have demonstrated effectiveness, their real-world application remains uncertain. The substantial variability in EEG signals among individuals poses a challenge in developing a universal model, often necessitating retraining with the introduction of new subjects. However, obtaining sufficient data for retraining, especially fatigue data for new subjects, is impractical in real-world settings. In response to these challenges, this paper introduces a hybrid solution for fatigue detection that combines clustering with classification. Unsupervised clustering groups subjects based on their EEG functional connectivity in an alert state, and classification models are subsequently applied to each cluster for predicting alert and fatigue states. Results indicate that classification on clusters achieves higher accuracy than scenarios without clustering, suggesting successful grouping of subjects with similar functional connectivity characteristics through clustering, thereby enhancing the classification process. Furthermore, the proposed hybrid method ensures a practical and realistic retraining process, improving the adaptability and effectiveness of the fatigue detection system in real-world applications.&#xD.

The Role of Biomarkers in Monitoring Chronic Fatigue Among Male Professional Team Athletes: A Systematic Review

This systematic review synthesizes evidence on biomarker responses to physiological loads in professional male team sport athletes, providing insights into induced fatigue states. Structured searches across major databases yielded 28 studies examining various biomarkers in elite team sport players. Studies evaluated muscle damage markers, anabolic/catabolic hormones reflecting metabolic strain, inflammatory markers indicating immune activity and tissue damage, immunological markers tied to infection risk, and oxidative stress markers showing redox imbalances from excessive physiological load. Responses were examined in official matches and training across competitive seasons. The evidence shows that professional team sports induce significant alterations in all studied biomarkers, reflecting measurable physiological strain, muscle damage, oxidative stress, inflammation, and immunosuppression during intensive exercise. These effects tend to be larger and more prolonged after official matches compared to training. Reported recovery time courses range from 24-h to several days post-exercise. Monitoring biomarkers enables quantifying cumulative fatigue and physiological adaptations to training/competition loads, helping to optimize performance while mitigating injury and overtraining. Key biomarkers include creatine kinase, testosterone, cortisol, testosterone/cortisol ratio, salivary immunoglobulin-A, and markers of inflammation and oxidative stress. Further research should extend biomarker monitoring to cover psychological stress and affective states alongside physiological metrics for deeper insight into athlete wellness and readiness.

Effects of Mild Fatigue on Biomechanics of Single Leg Landing in Young Male Volleyball Players

Objective: To investigate the effects of mild fatigue on the biomechanics of the lower limbs of young male volleyball players while performing single leg landing tasks. Methods: A total of ten young male volleyball players were recruited as participants in this study. After the single leg landing was performed, we compared the performance between those with and without fatigue (post- and non-fatigue, respectively). Kinematics and kinetics were collected using instruments, and related captured data were imported into OpenSim to analyze the hip, knee, and ankle joints. Results: We found that the ankle dorsiflexion angle at initial contact was significantly decreased in the post-fatigue group compared to the non-fatigue one. Meanwhile, the peak gluteus maximus force, peak gluteus medius force, peak tibialis posterior force, and peak gastrocnemius force significantly increased. There were no significant differences in the hip and knee joint flexion angles as well as the quadriceps and biceps femoris long head forces between the two groups. Conclusions: Mild fatigue can affect the performance of single leg landing, and players need to control the lower limbs by generating a higher muscle force to cope with the instability induced by fatigue. In a fatigued state, following initial contact with the ground, a decreased ankle dorsiflexion angle necessitates an increase in gastrocnemius and tibialis posterior muscle force to maintain stance during landing.

Intelligent Human Operator Mental Fatigue Assessment Method Based on Gaze Movement Monitoring

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.

Changes in hamstrings’ active stiffness during fatigue tasks are modulated by contraction duration rather than intensity

Despite the increase in research of hamstring stiffness through the use of ultrasound-based shear wave elastography, the active stiffness of biceps femoris long head (BFlh) and semitendinosus (ST) muscles under fatigue conditions at various contraction intensities has not been sufficiently explored. This study aimed to compare the effects of knee flexor’s isometric contraction until exhaustion performed at 20% vs. 40% of maximal voluntary isometric contraction (MVIC), on the active stiffness responses of BFlh and ST. Eighteen recreationally active males performed two experimental sessions. The knee flexors’ MVIC was assessed before the fatiguing task, which involved a submaximal isometric contraction until failure at 20% or 40% of MVIC. Active muscle stiffness of the BFlh and ST was assessed using shear wave elastography. BFlh active stiffness remained relatively unaltered at 20% of MVIC, while ST active stiffness decreased from ≅ 91% contraction time (55.79 to 44.52 kPa; p < 0.001). No intramuscular stiffness changes were noted in BFlh (36.02 to 41.36 kPa; p > 0.05) or ST (63.62 to 53.54 kPa; p > 0.05) at 40% of MVIC session. Intermuscular active stiffness at 20% of MVIC differed until 64% contraction time (p < 0.05) whereas, at 40% of MVIC, differences were observed until 33% contraction time (p < 0.05). BFlh/ST ratios were not different between intensities (20%=0.75 ± 0.24 ratio vs. 40%=0.72 ± 0.32 ratio; p > 0.05), but a steeper increase in BFlh/ST ratio was found for 20% (0.004 ± 0.003 ratio/%) compared to 40% (0.001 ± 0.003 ratio/%) of MVIC (p = 0.003). These results suggest that contraction duration could play a major role in inducing changes in hamstrings’ mechanical properties during fatigue tasks compared to contraction intensity.

Influence of Fatigue and Defensive Pressure on Three-Point Jump-Shot Kinematics in Basketball

This study examines the influence of fatigue and defensive pressure on the kinematic parameters of the three-point jump shot in basketball. Fourteen male collegiate basketball players (age: 21 ± 3 years old, body height: 186.35 ± 7.02 cm, body mass: 82.20 ± 10.99) participated in the study. Each participant performed three-point jump shots under four conditions: without defense, with defense, without defense after a fatigue protocol, and with defense after a fatigue protocol. Kinematic data were collected using the Xsens MVN inertial suit system and the OptoJump Next system. The analysis focused on various parameters including jump height, center of mass, release height, shoulder angle, and segment velocities. The repeated-measures ANOVA was used to observe the differences between each shot condition (fatigue, defense). Results indicated significant changes in the kinematic parameters due to both fatigue and defensive pressure. Fatigue notably changed shooting performance, affecting jump height and release mechanics. The defensive pressure altered shooting technique, leading to quicker ball release and higher release points. These findings highlight the importance of incorporating fatigue and defensive scenarios in training, suggesting that coaches develop more targeted training plans to improve performance under conditions of fatigue and defensive pressure.

Examining the Independent and Interactive Carryover Effects of Cognitive and Physical Exertions on Physical Performance.

This study compared the effects of prior cognitive, physical, and concurrent exertion on physical performance. Fatiguing cognitive and physical exertions have been shown to negatively affect subsequent task performance. However, it is not clearly understood if concurrent physical and cognitive effort may exaggerate the negative carryover effects on physical task performance when compared to cognitive or physical exertion alone. Twenty-five participants completed four isometric handgrip endurance trials on different days. The endurance trials were preceded by four, 15-minute experimental manipulations (cognitive, physical, concurrent, control). Electromyography (EMG) and force tracing performance were monitored, with handgrip strength measured pre and post. Subjective ratings of mental and physical fatigue, as well as affect, motivation, and task self-efficacy, were also assessed. Handgrip strength decreased following both physical (-14.4% MVC) and concurrent (-12.3% MVC) exertion manipulations, with no changes being observed for the cognitive and control conditions. No differences were observed across conditions for endurance time, EMG, nor tracing performance. When compared to the control conditions, perceptions of mental and physical fatigue were higher following the experimental manipulation. Endurance trial self-efficacy was lower for the mental, physical and concurrent conditions compared to control. The concurrent condition resulted in similar decreases in strength as the physical fatigue condition, but otherwise resulted in similar carryover effects on endurance performance across all conditions. Further study is required at higher exposure levels, or for longer exposure durations, to further probe the influence of concurrent physical and cognitive effort on task performance. Concurrent cognitive and physical effort resulted in similar physical performance decrements to physical effort alone.

Impact of Quadriceps Muscle Fatigue on Ankle Joint Compensation Strategies During Single-Leg Vertical Jump Landing.

This study investigates the impact of quadriceps fatigue on lower limb biomechanics during the landing phase of a single-leg vertical jump (SLJ) in 25 amateur male basketball players from Ningbo University. Fatigue was induced through single-leg knee flexion and extension exercises until task failure. Kinematic and dynamic data were collected pre-fatigue (PRF) and post-fatigue (POF) using the Vicon motion capture system and the AMTI force platform and analyzed using an OpenSim musculoskeletal model. Paired sample t-tests revealed significant changes in knee and hip biomechanics under different fatigue conditions, with knee joint angle (p < 0.001), velocity (p = 0.006), moment (p = 0.006), and power (p = 0.036) showing significant alterations. Hip joint angle (p = 0.002), moment (p = 0.033), and power (p < 0.001) also exhibited significant changes. Muscle activation and joint power were significantly higher in the POF condition, while joint stiffness was lower. These findings suggest that quadriceps fatigue leads to biomechanical adjustments in the knee and hip joints, which may increase the risk of injury despite aiding in landing stability.