Modeling and Validation of Fatigue and Recovery of Muscles for Manual Demolition Tasks

Manual demolition tasks are heavy, physically demanding tasks that could cause muscle fatigue accumulation and lead to work-related musculoskeletal disorders (WMSDs). Fatigue and recovery models of muscles are essential in understanding the accumulation and the reduction in muscle fatigue for forceful exertion tasks. This study aims to explore the onset of muscle fatigue under different work/rest arrangements during manual demolition tasks and the offset of fatigue over time after the tasks were performed. An experiment, including a muscle fatigue test and a muscle fatigue recovery test, was performed. Seventeen male adults without experience in demolition hammer operation were recruited as human participants. Two demolition hammers (large and small) were adopted. The push force was either 20 or 40 N. The posture mimicked that of a demolition task on a wall. In the muscle fatigue test, the muscle strength (MS) before and after the demolition task, maximum endurance time (MET), and the Borg category-ratio-10 (CR-10) ratings of perceived exertion after the demolition task were measured. In the muscle fatigue recovery test, MS and CR-10 at times 1, 2, 3, 4, 5, and 6 min were recorded. Statistical analyses were performed to explore the influence of push force and the weight of the tool on MS, MET, and CR-10. Both muscle fatigue models and muscle fatigue recovery models were established and validated. The results showed that push force affected MET significantly (p < 0.05). The weight of the tool was significant (p < 0.05) only on the CR-10 rating after the first pull. During the muscle fatigue recovery test, the MS increase and the CR-10 decrease were both significant (p < 0.05) after one or more breaks. Models of MET and MS prediction were established to assess muscle fatigue recovery, respectively. The absolute (AD) and relative (RD) deviations of the MET model were 1.83 (±1.94) min and 34.80 (±31.48)%, respectively. The AD and RD of the MS model were 1.39 (±0.81) N and 1.9 (±1.2)%, respectively. These models are capable of predicting the progress and recovery of muscle fatigue, respectively, and may be adopted in work/rest arrangements for novice workers performing demolition tasks.

Pre-exercise Carbohydrate Drink Adding Protein Improves Post-exercise Fatigue Recovery

Purpose: This study aimed to assess the requirement of protein in pre-exercise carbohydrate drinks for optimal endurance performance at high intensity and post-exercise fatigue recovery.Methods: Endurance performance at 85% V.⁢O2peak of young men (age 20 ± 0.9 years, V.⁢2peak 49.3 ± 0.3 L/min) was measured for two consecutive days using cycling time to exhaustion and total work exerted 2 h after three isocaloric supplementations: RICE (50 g, protein: 1.8 g), n = 7; SOY + RICE (50 g, protein: 4.8 g), n = 7; and WHEY + RICE (50 g, protein: 9.2 g), n = 7.Results: Endurance performance was similar for the three supplemented conditions. Nevertheless, maximal cycling time and total exerted work from Day 1 to Day 2 were improved in the WHEY + RICE (+21%, p = 0.05) and SOY-RICE (+16%, p = 0.10) supplemented conditions, not the RICE supplemented condition. Increases in plasma interleukin-6 (IL-6) were observed 1 h after exercise regardless of supplemented conditions. Plasma creatine kinase remained unchanged after exercise for all three supplemented conditions. Increases in ferric reducing antioxidant power (FRAP) after exercise were small and similar for the three supplemented conditions.Conclusion: Adding protein into carbohydrate drinks provides no immediate benefit in endurance performance and antioxidant capacity yet enhances fatigue recovery for the next day. Soy-containing carbohydrate drink, despite 50% less protein content, shows similar fatigue recovery efficacy to the whey protein-containing carbohydrate drink. These results suggest the importance of dietary nitrogen sources in fatigue recovery after exercise.

Difference of cooling use during sleep between elderly and young people

In Japan, nearly 80% of heatstroke occurrences in recent years have involved people older than 65 years old. This study surveyed the actual use of cooling by elderly people at sleep time compared to those found for younger people. Results revealed the followings. 1) Ratios of cooling use at sleep time were 30.8% for elderly people and 57.4% for younger people. The respective ratios of natural ventilation use at sleep time were 39.9% and 32.4%. 2) Average wet bulb globe temperatures (WBGTs) of bed rooms during sleep were 26.9°C for elderly people and 26.4°C for younger people. 3) Elderly people feel warmer than younger people but they feel more thermally comfortable. 4) Sleep scores were 49.7 for elderly people and 48.5 for younger people. No difference was found for the frequency of night waking or the Sleep maintenance score, but the Fatigue recovery score showed the greatest difference between elderly and younger people.

Effects of Theracurmin® consumption on liver function, fatigue, and sleep: a randomized, double-blind, placebo- controlled, parallel-comparison study

Objective: To evaluate the effects of the eight-week consumption of Theracurmin® on liver function, fatigue, and sleep.Methods: This was a randomized, double-blind, placebo-controlled, parallel-comparison study involving 68 healthy Japanese adults. Subjects were allocated into either the active (Theracurmin®) or placebo group (n = 34 each) using a random number generator. Subjects consumed two capsules per day of either the active or placebo food for eight weeks. The primary outcome was the serum alanine aminotransferase (ALT) levels at eight weeks, whereas the secondary outcomes were the biomarkers of liver function, comparison of the percentages of improvement in liver function based on the decision criteria, OSA sleep inventory MA version (OSA-MA), and visual analog scale of fatigue.Results: Each group included 33 subjects in the full analysis set. ALT levels in the per protocol set analysis, except for subjects drinking quantities of alcohol that increase the risk of lifestyle-related disease onset, showed a significant decrease in ALT compared to the placebo group (P < 0.05). The subjective symptom in the fatigue recovery factor of OSA-MA was significantly improved through the intervention (P < 0.05). The fatigue recovery effect of Theracurmin® was prominent in the subjects aged ≤ 45 years, the age group defined by the Ministry of Health, Labour and Welfare as middle-aged and older persons in the Act on Stabilization of Employment of Elderly. No adverse event was observed.Conclusions: These results suggest that the consumption of Theracurmin® or eight weeks improved liver function and fatigue recovery at awakening in healthy Japanese adults.Trial registration: UMIN-CTR: UMIN000039319.Foundation: Theravalues CorporationKeywords: highly bioavailable curcumin, liver function, alanine aminotransferase (ALT), OSA sleep inventory MA version, fatigue recovery

The effect of learning, forgetting, fatigue, and recovery on the performance of dual-resource constrained (DRC) systems

Dual-Resource Constrained (DRC) systems consist of two resources: workers and machines (stations). DRCs have become common in manufacturing and service firms that emphasise flexibility, where workers perform different tasks. Although having a flexible workforce is beneficial, it comes at a cost. When workers alternate between different jobs the productivity of the system is affected. On one hand the system becomes more responsive to changes (internal/external), and on the other hand worker productivity and system throughput deteriorate because of the loss of knowledge and workers’ fatigue. This subjects workers to conflicting phenomena. When workers are performing a task they are learning but also accumulating fatigue, which may result in error or injury. When transferred to another task, or on a break, workers may forget what they have learnt but at the same time recover from fatigue, either fully or partially. In particular, forgetting and fatigue are interesting to be considered as they directly affect the quality of products. This research investigates the effects of workers’ learning-forgetting and fatigue-recovery on DRC systems. First, it modifies a known learning-forgetting model by accounting for fatigue and recovery. Second, it assumes that the quality of a production process may deteriorate and generate defective items that require rework. Third, a human error model is developed that considers human learning-forgetting and fatigue-recovery in producing defective items. Fourth, a comprehensive model is developed that integrates learning, forgetting, fatigue, and recovery into a DRC system with quality consideration. This model is investigated for different transfer and flexibility policies. Numerical results provide insights and guidelines that may help operations managers with decisions on how to improve a system’s performance and throughput, while considering worker welfare. Results indicate that it is important to consider workers capabilities and limitations when designing manufacturing systems. They also suggest that ignoring human restrictions and abilities results in unrealistic production planning and erroneous cost estimation.

The effect of learning, forgetting, fatigue, and recovery on the performance of dual-resource constrained (DRC) systems

Dual-Resource Constrained (DRC) systems consist of two resources: workers and machines (stations). DRCs have become common in manufacturing and service firms that emphasise flexibility, where workers perform different tasks. Although having a flexible workforce is beneficial, it comes at a cost. When workers alternate between different jobs the productivity of the system is affected. On one hand the system becomes more responsive to changes (internal/external), and on the other hand worker productivity and system throughput deteriorate because of the loss of knowledge and workers’ fatigue. This subjects workers to conflicting phenomena. When workers are performing a task they are learning but also accumulating fatigue, which may result in error or injury. When transferred to another task, or on a break, workers may forget what they have learnt but at the same time recover from fatigue, either fully or partially. In particular, forgetting and fatigue are interesting to be considered as they directly affect the quality of products. This research investigates the effects of workers’ learning-forgetting and fatigue-recovery on DRC systems. First, it modifies a known learning-forgetting model by accounting for fatigue and recovery. Second, it assumes that the quality of a production process may deteriorate and generate defective items that require rework. Third, a human error model is developed that considers human learning-forgetting and fatigue-recovery in producing defective items. Fourth, a comprehensive model is developed that integrates learning, forgetting, fatigue, and recovery into a DRC system with quality consideration. This model is investigated for different transfer and flexibility policies. Numerical results provide insights and guidelines that may help operations managers with decisions on how to improve a system’s performance and throughput, while considering worker welfare. Results indicate that it is important to consider workers capabilities and limitations when designing manufacturing systems. They also suggest that ignoring human restrictions and abilities results in unrealistic production planning and erroneous cost estimation.