Sex-specific Effects of Localized Muscle Fatigue on Upper Body Kinematics During a Repetitive Pointing Task

BackgroundFemales are reported to have a higher risk of musculoskeletal disorders than males. Among risk factors for musculoskeletal disorders, the mechanism of muscle fatigue remains unclear. Especially how females and males adapt to localized fatigue is poorly understood. The purpose of the study was to examine the sex-specific effects of fatigue location on shoulder, elbow and spinal joint angles, and angular variabilities during a repetitive pointing task.MethodsSeven males and ten females performed a standing repetitive pointing task when they were non-fatigued (NF), elbow-fatigued (EF), shoulder-fatigued (SF) and trunk-fatigued (TF), while trunk and upper body tridimensional kinematic data was recorded. Joint angles and angular variabilities of shoulder, elbow, upper thorax, lower thorax, and lumbar were calculated. ResultsResults showed that shoulder angles changed the most after EF in males, but after SF in females. The similarities between sexes were that SF increased the variabilities at upper (lateral flexion: 0.15° greater than NF, rotation: 0.26° greater than all other conditions) and lower thorax (lateral flexion: 0.13° greater than NF, rotation: averagely 0.1° greater than all other condition) in both sexes. TF altered upper thorax variability (0.36° smaller than SF), lower thorax angle (lateral flexion: 3.00° greater than NF, rotation: 1.68° greater than SF), and lumbar angle (averagely 1.8° smaller than all other conditions) in both sexes. However, females had greater lower thorax angle (lateral flexion: 8.3° greater, p=0.005) as well as greater upper (rotation: 0.53° greater, p=0.006) and lower thorax (rotation: 0.5° greater, p=0.007; flexion: 0.6° greater, p=0.014) angular variabilities.ConclusionsThe overall greater lower and upper thorax angular variabilities suggested a more unstable spinal movement pattern in females. The kinematic differences between sexes highlighted a few sex differences in adapting the localized muscle fatigue.

Exploring Localized Muscle Fatigue Responses at Current Upper-Extremity Ergonomics Threshold Limit Values

Objective The purpose of this study was to evaluate localized muscle fatigue responses at three upper-extremity ergonomics threshold limit value (TLV) duty cycles. Background Recently, a TLV equation was published to help mitigate excessive development of localized muscle fatigue in repetitive upper limb tasks. This equation predicts acceptable levels of maximal voluntary contraction (% MVC) for a given duty cycle (DC). Experimental validation of this TLV curve has not yet been reported, which can help guide utilization by practitioners. Method Eighteen participants performed intermittent isometric elbow flexion efforts, in three separate counter-balanced sessions, at workloads defined by the American Conference of Governmental Industrial Hygenists’ (ACGIH) TLV equation: low DC (20% DC, 29.6% MVC), medium DC (40% DC, 19.7% MVC), and high DC (60% DC, 13.9% MVC). Targeted localized muscle fatigue (LMF) of the biceps brachii was tracked across numerous response variables, including decline in strength (MVC), electromyography (EMG) amplitude and mean power frequency (MnPF), and several psychophysical ratings. Results At task completion, biceps MnPF and MVC (strength) were significantly different between each TLV workload, with the high DC condition eliciting the largest declines in MnPF and MVC. Conclusion Findings demonstrate that working at different DCs along the ACGIH TLV curve may not be equivalent in preventing excessive LMF. Higher DC workloads elicited a greater LMF response across several response variables. Application High DC work of the upper extremity should be avoided to mitigate excess LMF development. Current TLVs for repetitive upper-extremity work may overestimate acceptable relative contraction thresholds, particularly at higher duty cycles.

Association between electromyographic localized muscle fatigue of the rectus femoris and static postural balance in physically active adult men

Although the determinant impact of exercise-induced muscle fatigue prior to postural balance assessment has been widely described, recent evidence suggests that hyperventilation and sensorimotor losses, rather than muscle fatigue, are responsible for the changes observed in postural balance. However, the association between localized muscle fatigue (LMF), induced by isokinetic dynamometer protocol test and assessed through surface electromyography, and postural balance in adults is poorly understood. We aimed to evaluate the association between the LMF of the rectus femoris and static postural balance in 51 adult men (43±14.8 years; 26.9±5 kg/m2). We obtained physical activity level and postural balance, respectively, through a triaxial accelerometry and a force platform. The quadriceps femoris strength and endurance were obtained using an isokinetic dynamometer and surface electromyography simultaneously. The association between the isokinetic and electromyographic LMF and static postural balance was investigated using linear regression models adjusted for age, body mass index, and isokinetic quadriceps strength and LMF. The correlations between postural balance variables and isokinetic muscle strength and LMF were weak-to-moderate. After multivariate analyses, we observed that electromyographic LMF were a predictor of postural balance, mainly of the mean amplitude and COP area and velocity in the mediolateral direction, regardless of isokinetic variables. Therefore, LMF plays a determinant role in the postural balance of physically active adult men. Fatigue indices are significant predictors of postural balance, regardless of previous fatigue induction.

History Dependency of Muscle Strength Recovery from a Fatiguing Intermittent Task

Muscle fatigue and recovery are complex processes influencing muscle force generation capacity. While fatigue reduces this capacity, muscle recovery acts to restore the unfatigued muscle state. Many factors can potentially affect muscle recovery, among these may be a task dependency of recovery following an exercise. However, little has been reported regarding the history dependency of recovery after fatiguing contractions. Recently, we investigated the dependency of the fatigue process on cycle time during low to moderate exertion levels of intermittent muscle contraction (Rashedi & Nussbaum, 2016). A dependency of localized muscle fatigue on cycle time was shown, even though there was a consistent level of overall physical demand. It was concluded that the difference in fatigue development might be related to recovery processes occurring during execution of the intermittent task. In the present study, we focused on the potential effect of contraction history on post-fatigue recovery. Based on the expected dependency of recovery to task demands during exercise, it was hypothesized that post-fatigue recovery will also be affected by the history of exercise-induced muscle fatigue. We examined the dependency of muscle recovery subsequent to four different histories of fatiguing muscle contractions, imposed using two cycle times (30 and 60 sec) during low to moderate levels (15% and 25% of maximum voluntary contraction (MVC)) of intermittent static exertions involving index finger abduction. All participants completed the intermittent contractions, in all four conditions, for 1 hour, and MVCs were obtained at fixed intervals during 1 hour of post-exercise recovery (i.e., at 0.2, 5, 10, 30, and 60 minutes). There was a clear and statistically-significant dependency of muscle recovery rate on the muscle capacity state existing immediately after fatiguing exercise. This dependency did not appear to be modified by either the cycle time or exertion level leading to that state. Similar results were found in the study of Iguchi et al. (2008), wherein the authors compared recovery between two different exertion histories while fatiguing muscles to the same level, though recovery was only monitored for 5 minutes. These results imply that the post-exercise rate of recovery is primarily influenced by the post-exercise muscle state. Such evidence may help improve existing models of muscle recovery (Rashedi & Nussbaum, 2015b), facilitating more accurate predictions of localized muscle fatigue development (Rashedi & Nussbaum, 2015a), and thereby helping to enhance muscle performance and reduce the risk of injury