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In this paper, aiming at the detection of fatigue driving scene of drivers, a diagnostic model based on machine learning is proposed under the scene of long-time driving. The validity of the model is verified by simulation experiments. The simulation result shows that the model can effectively fit the fatigue condition of drivers under long-time driving, and accurately judge and warn the fatigue state of drivers. At the same time, the model also extends the application of fatigue classification detection.

About 40% of the US construction workforce experiences high-level fatigue, which leads to poor judgment, increased risk of injuries, a decrease in productivity, and a lower quality of work. Therefore, it is essential to monitor fatigue to reduce its adverse effects and prevent long-term health problems. However, since fatigue demonstrates itself in several complex processes, there is no single standard measurement method for fatigue detection. This study aims to develop a system for continuous workers’ fatigue monitoring by predicting the aerobic fatigue threshold (AFT) using forearm muscle activity and motion data. The proposed system consists of five modules: Data acquisition, activity recognition, oxygen uptake prediction, maximum aerobic capacity (MAC) estimation, and continuous AFT monitoring. The proposed system was evaluated on the participants performing fourteen scaffold-building activities. The results show that the AFT features have achieved a higher accuracy of 92.31% in assessing the workers’ fatigue level compared to heart rate (51.28%) and percentage heart rate reserve (50.43%) features. Moreover, the overall performance of the proposed system on unseen data using average two-min AFT features was 76.74%. The study validates the feasibility of using forearm muscle activity and motion data to workers’ fatigue levels continuously.

Fiber Bragg grating (FBG) sensors provide excellent capability for the structural health monitoring (SHM) of load-bearing structures by allowing for local internal strain measurements within structures. However, the integration of these sensors to composite materials is associated with several challenges that have to be addressed to have the correct strain measurement and in turn to perform reliable SHM. One of the most important issues is the presence of uneven strain fields around FBGs, which significantly affect the response of the sensors and hence the reliability of the acquired data. The uniformity of the strain fields around sensors is important for dependable data acquisition; however, to generate such a condition, tow width-to-FBG length relationship, optical fiber configuration with respect to reinforcement fiber orientation, and crack density resulting from fatigue loading are very important factors that have to be considered. In this paper, these issues are addressed by investigating the signal properties of FBG sensors with 1 and 10 mm lengths embedded within the composite specimens during the manufacturing process. After fatigue testing of the specimens, it is shown that 1-mm-long FBGs embedded in-line with adjacent reinforcement fibers with tow widths of ∼2 mm provide much more reliable signals than 10-mm-long FBGs embedded perpendicular to adjacent tows.

Malone, S, Mendes, B, Hughes, B, Roe, M, Devenney, S, Collins, K, and Owen, A. Decrements in neuromuscular performance and increases in creatine kinase impact training outputs in elite soccer players. J Strength Cond Res 32(5): 1342-1351, 2018-The aim of the current investigation was to understand the impact of pretraining neuromuscular performance and creatine kinase (CK) status on subsequent training performance in elite soccer players. Thirty soccer players (age: 25.3 ± 3.1 years; height: 183 ± 7 cm; mass: 72 ± 7 kg) were involved in this observational study. Each morning before training, players completed assessments for neuromuscular performance (countermovement jump; CMJ) and CK levels. Global positioning technology provided external load: total distance, high-speed distance, sprint distance, accelerations, decelerations, average metabolic power, explosive distance, and high metabolic power distance (25.5 W·kg). Mixed-effect linear models revealed significant effects for CK and CMJ Z-score on total high-speed distance, very high-speed distance, accelerations, decelerations, explosive distance, and maximal velocity. Effects are reported with 90% confidence limits. A CK Z-score of +1 corresponded to a -5.5 ± 1.1, -3.9 ± 0.5, -4.3 ± 2.9%, -4.1 ± 2.9%, -3.1 ± 2.9%, and -4.6 ± 1.9%, reduction in total high-speed distance, very high-speed distance, accelerations, decelerations, explosive distance, and maximal velocity, respectively. Countermovement jump Z-score of -1 corresponded to a -3.5 ± 1.1, -2.9 ± 0.5, -2.1 ± 1.4, -5.3 ± 2.9%, -3.8 ± 2.9%, -1.1 ± 2.9%, and -5.6 ± 1.2% reduction in these external load measures. Magnitude-based analysis revealed that the practical size of the effect of a pretraining CMJ Z-score of -1 and CK Z-score of +1 would have on total high-speed distance, very high-speed distance, high metabolic power distance (25.5 W·kg), accelerations, decelerations, explosive distance, and maximal velocity was likely negative. The results of this study suggest that systematic pretraining monitoring of neuromuscular and muscle stress within soccer cohorts can provide coaches with information about the training output that can be expected from individual players during a training session.

Purpose: Being able to identify how an athlete is responding to training would be useful to optimise adaptation and performance. The maximal rate of heart rate increase (rHRI), a marker of heart rate acceleration has been shown to correlate with performance changes in response to changes in training load in male athletes; however, it has not been established if it also correlates with performance changes in female athletes. Methods: rHRI and cycling performance were assessed in six female cyclists following 7 days of light training (LT), 14 days of heavy training (HT) and a 10 day taper period. rHRI was the first derivative maximum of a sigmoidal curve fit to R-R data recorded during 5 min of cycling at 100 W. Cycling performance was assessed as work done (kJ) during time-trials of 5 (5TT) and 60 (60TT) min duration. Results: 5TT was possibly decreased at HT (ES ± 90% confidence interval = − 0.16 ± 0.25; p = 0.60), while, 5TT and 60TT very likely to almost certainly increased from HT to taper (ES = 0.71 ± 0.24; p = 0.007 and ES = 0.42 ± 0.19; p = 0.02, respectively). Large within-subject correlations were found between rHRI, and 5TT (r = 0.65 ± 0.37; p = 0.02) and 60TT (r = 0.70 ± 0.31; p = 0.008). Conclusions: rHRI during the transition from rest to light exercise correlates with training induced-changes in exercise performance in females, suggesting that rHRI may be a useful monitoring tool for female athletes. Refereed/Peer-reviewed

Aircraft structure fatigue monitoring has been developed over decades presently reaching the stage where it became mandatory for all combat aircraft to be equipped with an airborne fatigue monitoring system. These systems usually collect operational data for calculating the safe fatigue life or inspection interval for the aircraft structure. This paper presents an analysis of the current state of fatigue monitoring systems on the IAR-99 SOIM based on the experience of international fatigue monitoring programs and analysis of structure resource improvement. Aspects related to strain gauge and calibration, flight parameter data gathering, data integrity, comparison with fatigue test results and fatigue damage models are also investigated by means of flight tests.

The purpose of this study was to assess the concurrent validity and test-retest reliability of a linear position transducer (LPT) for the squat jump (SJ) and counter-movement jump (CMJ) height. Twenty-eight subjects (25.18 &plusmn, 7.1 years) performed three SJs followed by three CMJs using a force plate concurrently with the LPT to test validity. Subjects returned on a separate day, at least 48 h apart, to measure test-retest reliability. A t-test showed a significant difference between the two devices for both SJ (p &lt, 0.001) and CMJ (p &lt, 0.001) while Bland&ndash, Altman analysis for validity revealed that the LPT overestimated jump height for both SJ (mean difference (MD) = 8.01 &plusmn, 2.93 cm) and CMJ (MD = 8.68 &plusmn, 2.99 cm). With regards to reliability of the LPT, mean intraclass correlation (ICC) for both SJ (ICC = 0.84) and CMJ (ICC = 0.95) were high, and Bland&ndash, Altman analysis showed mean differences lower than minimal detectable change (MDC) between the days for both SJ (MD = 1.89 &plusmn, 4.16 cm vs. MDC = 2.72 cm) and CMJ (MD = 0.47 &plusmn, 3.23 cm vs. MDC = 2.11 cm). Additionally, there was a low coefficient of variation (CV) between days for both SJ (CV = 3.25%) and CMJ (CV = 0.74%). Therefore, while the LPT overestimates jump height, it is a reliable tool for tracking changes in jump height to measure performance improvement and monitor fatigue.

The application of a telemetry system for train axle fatigue monitoring is analyzed in this paper. Monitoring of the axle bending deformation at critical points is of great importance for both high speed and freight trains. The fatigue life of the axle may be significantly reduced due to accidental peak loads. Commonly used telemetry systems require special pick-ups for transmitting electrical power to the electronics placed on the rotating axle and for transferring back sensor signals. Inductive power transfer is performed through a high frequency magnetic field linking a rotating winding. Sensor signals are modulated on top of the power signal and transferred at an even higher frequency to be immune to the inductive magnetic field. In this paper a new approach for an inductive power transfer system, completely decoupled from the transfer of sensor signals, is analyzed. The layout of the energy transmission system has been simplified with respect to traditional telemetry systems and its efficiency is increased. Also the immunity of the measurements against the power magnetic field, the distance of the power head and all the electrical noise induced results have been improved. The combination of a simple power induction system, a fast data processing unit and a low power RF data transmission system lead to an easy and reliable telemetry system for train axle monitoring.