Few studies have focused on the effect of fatigue severity on landing strategy. This study aimed to investigate the effect of fatigue progression on ground reaction force during landing. Eighteen participants performed a fatigue exercise protocol. Then participants performed drop landings at three levels of fatigue: no fatigue, medium fatigue, and severe fatigue. Multiple linear regression was conducted to identify the predictors of the peak vertical ground reaction force at each level of fatigue. Two-way ANOVAs were conducted to test the effect of fatigue on the vertical ground reaction force and the predictors. For the vertical ground reaction force, the knee joint stiffness and the knee angle at initial contact were the main predictors at no fatigue. The peak knee flexion angle and knee power were the main predictors at medium fatigue. However, the peak ankle plantarflexion moments became the main predictor at severe fatigue. The vertical ground reaction force decreased from no to medium fatigue (p = 0.001), and then increased from medium to severe fatigue (p = 0.034). The knee joint stiffness decreased from no to medium fatigue (p = 0.049), and then remained unchanged from medium to severe fatigue. The peak knee flexion angle increased from no to medium fatigue (p = 0.001), and then slightly decreased from medium to severe fatigue (p = 0.051). The results indicate that fatigue progression causes a transition from stiff to soft landing, and then to stiff landing. Participants used ankle joints more to control the landing intensity at severe fatigue.

Ruan, M, Li, L, Chen, C, and Wu, X. Stretch could reduce hamstring injury risk during sprinting by right shifting the length-torque curve. J Strength Cond Res 32(8): 2190–2198, 2018—It was hypothesized that static stretch would shift the length-torque curve to the right, which may reduce the risk of muscle strain injuries. The purpose of this study was to evaluate the acute effects of static stretching of hamstring (SSH) on the risk of hamstring injury during sprinting indicated by the shift of the length–torque relationship. Twelve female college athletes (age: 20.8 ± 0.7 years; height: 1.61 ± 0.05 m; body mass: 54.25 ± 4.22 kg) participated in this study. Subjects performed overground sprinting under 2 conditions: after warm-up with 4 × 30 seconds SSH or after warm-up without SSH. Three-dimensional kinematic and kinetic data and electromyography of biceps femoris long head (BFlh), rectus femoris, and vastus medialis were collected during testing. The maximum length of BFlh during late swing phase increased after SSH with large effect size and close to statistically significant (p = 0.05, d = 1.22), but the knee flexion torque at the peak length did not change significantly. Static stretching of hamstring significantly reduced peak values of both horizontal (d = 1.46) and vertical (d = 1.79) ground reaction forces, and BFlh's activation level during the preactivation (late swing) phase (p = 0.05, d = 2.16). The results indicated that the length of BFlh–knee torque relationship and the length of BFlh–hip torque relationships during the late swing phase and initial stance phase were shifted to the right after SSH, which may reduce risk of hamstring strain injuries. We suggest that preactivity static stretching should not be simply removed and participators should give priority to stretch muscles that are vulnerable to strain injuries.

Ruan, M, Zhang, Q, and Wu, X. Acute effects of static stretching of hamstring on performance and anterior cruciate ligament injury risk during stop-jump and cutting tasks in female athletes. J Strength Cond Res 31(5): 1241–1250, 2017—There is limited research investigating antagonist stretch. The purpose of this study was to evaluate the influence of static stretching of hamstrings (SSH) on performance and anterior cruciate ligament (ACL) injury risk during stop-jump and 180° cutting tasks. Twelve female college athletes (age 20.8 ± 0.7 years; height 1.61 ± 0.05 m; mass 54.25 ± 4.22 kg) participated in this study. Subjects performed stop-jump and 180° cutting tasks under 2 conditions: after warm-up with 4 × 30 seconds SSH or after warm-up without SSH. Three-dimensional kinematic and kinetic data as well as electromyography of biceps femoris, rectus femoris, vastus medialis, and gastrocnemius medialis were collected during testing. Static stretching of hamstrings significantly enhanced jump height by 5.1% (p = 0.009) but did not change the takeoff speed of cutting. No significant changes in peak knee adduction moment or peak anterior tibia shear force were observed with SSH regardless of the task. The peak lateral tibia shear force during cutting was significantly (p = 0.036) reduced with SSH. The co-contraction of hamstring and quadriceps during the preactivation (stop-jump: p = 0.04; cutting: p = 0.05) and downward phases (stop-jump: p = 0.04; cutting: p = 0.05) was significantly reduced after SSH regardless of the task. The results suggest that SSH enhanced the performance of stop-jump because of decreased co-contraction of hamstring and quadriceps but did not change the performance of cutting. In addition, SSH did not increase ACL injury risk during stop-jump and cutting tasks and even reduced medial-lateral knee loading during cutting.

Hypertension adversely affects glycolipid metabolism and vascular function in aging populations. This network meta-analysis evaluated 36 randomized trials (n = 2875) comparing traditional mind-body exercises (Tai Chi, Baduanjin, Daoyinyangshengshu) for metabolic and vascular improvements. Analyses revealed Tai Chi most effectively raised high-density lipoprotein (HDL) (standardized mean differences [SMD] = 0.88), while Daoyinyangshengshu optimally reduced fasting glucose (SMD = −1.21) and endothelin-1 (SMD = −1.82) while increasing nitric oxide (SMD = 1.41). Baduanjin best lowered low-density lipoprotein (LDL) (SMD = −0.95), with other exercises improving cholesterol and triglycerides. The findings demonstrate that specific mind-body practices differentially enhance cardiometabolic health, with Tai Chi and Daoyinyangshengshu showing particular promise for comprehensive benefits. These evidence-based results support incorporating traditional exercises into hypertension management protocols to address both metabolic and vascular dysfunction.

(1) Background: The aim of this study was to assess lower limb muscle strength in older adults during the transfer from sitting to standing (STS) using an inertial measurement unit (IMU). Muscle weakness in this population can severely impact function and independence in daily living and increase the risk of falls. By using an IMU, we quantified lower limb joint moments in the STS test to support health management and individualized rehabilitation program development for older adults. (2) Methods: This study involved 28 healthy older adults (13 males and 15 females) aged 60–70 years. The lower limb joint angles and moments estimated using the IMU were compared with a motion capture system (Mocap) (pair t-test, ICC, Spearman correlations, Bland–Altman plots) to verify the accuracy of the IMU in estimating lower limb muscle strength in the elderly. (3) Results: There was no significant difference in the lower limb joint angles and moments calculated by the two systems. Joint angles and moments were not significantly different (p > 0.05), and the accuracy and consistency of the IMU system was comparable to that of the Mocap system. For the hip, knee, and ankle joints, the ICCs for joint angles were 0.990, 0.989, and 0.885, and the ICCs for joint moments were 0.94, 0.92, and 0.89, respectively. In addition, the results of the two systems were highly correlated with each other: the r-values for hip, knee, and ankle joint angles were 0.99, 0.99, and 0.96, and the r-values for joint moments were 0.92, 0.96, and 0.85. In the present study, there was no significant difference (p > 0.05) between the IMU system and the Mocap system in calculating lower limb joint angles and moments. (4) Conclusions: This study confirms the accuracy of the IMU in assessing lower limb muscle strength in the elderly. It provides a portable and accurate alternative for the assessment of lower limb muscle strength in the elderly.

While music is known to influence exercise performance through auditory-motor coupling, the biomechanical mechanisms by which musical groove—characterized by rhythmic drive and movement-inducing qualities—modulates cycling coordination remain poorly understood. This study investigates how groove levels systematically alter lower extremity kinematics and neuromuscular control during high-torque cycling. Twenty-four well-trained, right-handed cyclists completed high-torque cycling trials under three counterbalanced conditions: metronome (control), low-groove (LG), and high-groove (HG) music, with groove levels objectively classified by a validated deep learning model (R2 = 0.85). Three-dimensional motion capture (200Hz) quantified hip-ankle and pelvis-torso coordination using vector coding techniques, while surface electromyography (EMG) of 12 lower limb muscles was analyzed via non-negative matrix factorization (NMF) to extract muscle synergy patterns. The NMF approach decomposes multi-muscle activation patterns into fundamental synergistic components, providing insight into neuromuscular control strategies. Compared to LG and control conditions, HG music significantly: (1) increased hip-ankle in-phase coordination by 28.7% (HG:29.8% vs. LG:23.2%, p = 0.020), (2) enhanced pelvis-torso synchronization by 27.1% (HG:38.0% vs. LG:29.9%, p = 0.048), and (3) promoted greater muscle synergy complexity (median synergies: HG = 7 vs LG = 6, p = 0.039). Notably, the soleus (SOL) muscle—crucial for ankle stabilization—showed significantly higher activation weights in HG condition (0.11 ± 0.03 vs 0.04 ± 0.02, p = 0.030), suggesting improved distal control. The emergence of a unique erector spinae-gastrocnemius lateralis (ES-GL) synergy pattern (present in 54% of HG trials) indicates enhanced trunk-limb coupling under high-groove conditions. High-groove music promotes more coordinated movement patterns during cycling through two key mechanisms: (1) optimized joint coordination, particularly in proximal–distal (hip-ankle) and axial (pelvis-torso) linkages, and (2) reorganization of neuromuscular control strategies evidenced by increased synergy complexity and selective activation of postural stabilizers (SOL). These findings provide biomechanical evidence supporting groove-based auditory-motor interventions, though direct performance benefits require verification through additional kinetic and metabolic measures. The successful application of deep learning for groove quantification establishes a framework for personalized music selection in sports and rehabilitation contexts.