Neuromuscular fatigue and cognitive constraints independently modify lower extremity landing biomechanics in healthy and chronic ankle instability individuals.

The purpose was to determine the impact of both cognitive constraint and neuromuscular fatigue on landing biomechanics in healthy and chronic ankle instability (CAI) participants. Twenty-three male volunteers (13 Control and 10 CAI) performed a single-leg landing task before and immediately after a fatiguing exercise with and without cognitive constraints. Ground Reaction Force (GRF) and Time to Stabilization (TTS) were determined at landing in vertical, anteroposterior (ap) and mediolateral (ml) axes using a force plate. Three-dimensional movements of the hip, knee and ankle were recorded during landing using a motion capture system. Exercise-induced fatigue decreased ankle plantar flexion and inversion and increased knee flexion. Neuromuscular fatigue decreased vertical GRF and increased ml GRF and ap TTS. Cognitive constraint decreased ankle internal rotation and increased knee and hip flexion during the flight phase of landing. Cognitive constraint increased ml GRF and TTS in all three axes. No interaction between factors (group, fatigue, cognitive) were observed. Fatigue and cognitive constraint induced greater knee and hip flexion, revealing higher proximal control during landing. Ankle kinematic suggests a protective strategy in response to fatigue and cognitive constraints. Finally, these two constraints impair dynamic stability that could increase the risk of ankle sprain.

Anodal tDCS improves the effect of neuromuscular training on the feedforward activity of lower extremity muscles in female taekwondo athletes with dynamic knee valgus.

Transcranial direct current stimulation (tDCS) can increase cortical excitability of a targeted brain area. This study aimed to investigate the effect of adding anodal-tDCS (a-tDCS) to neuromuscular training (NMT) on the dynamic knee valgus (DKV) and feedforward activity (FFA) of knee muscles. Thirty-four Taekwondo athletes with DKV, were randomly assigned to either NMT + a-tDCS (N = 17) or NMT + sham tDCS (N = 17). DKV and the knee muscles' FFA at the moment of single and double-leg landing and lateral hopping tasks were evaluated before and after the interventions. DKV and FFA of the knee muscles was improved in all tasks (P < 0.05), however, between-group differences were not significant (P > 0.05). The FFA of the semitendinosus, vastus medialis, gluteus medius, and gastrocnemius muscles in the single-leg landing (P < 0.05), the gluteus medius, gluteus maximus, semitendinosus, biceps femoris, and gastrocnemius muscles in the double-leg landing (P < 0.05), and the gluteus medius, gluteus maximus, and gastrocnemius muscles in the lateral hopping (P < 0.05) tasks were significantly different between the groups. A-tDCS achieved significantly larger improvements in the feedforward activity of lower extremity muscles compared with sham-tDCS. However, between-group comparisons did not show a significant difference in DKV.

Effect of fatigue on knee biomechanics during the sidestep cutting manoeuvre: A modelling approach.

Loading both lateral and medial compartments is crucial to understanding the effect of muscle fatigue during sidestep cutting. The present study investigated the changes in tibiofemoral contact forces in the medial and lateral compartments and the muscle force contributions during the sidestep-cutting manoeuvre after a handball-specific fatigue protocol. Twenty female handball athletes performed three trials of the sidestep-cutting manoeuvre before (baseline) and after the fatigue protocol. Motion capture and ground reaction forces were measured, and the data were processed in OpenSim. The variables were compared using statistical parametric mapping (SPM), with a significance level of p < 0.05. The results showed a decreased knee flexion angle during fatigue in the early stance phase. In addition, the post-fatigue analysis demonstrated significantly reduced forces in vasti muscles. Similarly, during fatigue, the SPM analysis showed decreased tibiofemoral contact forces in the vertical and anterior directions. Vertical force applied to both medial and lateral condyles demonstrated a significant reduction after the fatigue protocol. These results indicated that forces applied to the tibiofemoral joint were reduced following the fatigue protocol compared to the baseline values. However, no consistent evidence exists that fatigue increases the risk of knee injuries.

Can a Novel Light Weight Minimal Support Lifting Exoskeleton Modify Lifting Movement in People without Low Back Pain?

Low back pain (LBP) is a major contributor to lifting-related disabilities. To minimize the risk of back pain, emerging technologies known as lifting exoskeletons were designed to optimize lifting movements. However, it is currently unknown whether a minimally supportive exoskeleton can alter the lifting movement in people without LBP. This study aims to investigate if wearing a novel lightweight exoskeleton that minimally supports the back, hip, and knee can alter the lifting range of motion and movement variations in people without LBP. This study also aims to investigate if wearing this novel exoskeleton can result in a reliable between-day lifting movement. In two separate sessions (each one week apart), fourteen participants lifted a box (that weighed 10% of their body weight) ten times, once while wearing an exoskeleton and once while not wearing an exoskeleton. Wearing the novel exoskeleton during lifting produced moderate-high, test-retest reliability (Trunk: ICC3,1 = 0.89, 95% CI [0.67, 0.96], SEM = 9.34°; Hip: ICC3,1 = 0.63, 95% CI [0.22, 0.88], SEM = 2.57°; Knee: ICC3,1 = 0.61, 95% CI [0.23, 0.87], SEM = 2.50°). Wearing an exoskeleton significantly decreased the range of motion of the knee (F1,4 = 4.83, p = 0.031, ηp2 = 0.06). Additionally, wearing an exoskeleton significantly decreased hip (diff = 8.38, p = 0.045) and knee (diff = -8.57, p = 0.038) movement variability; however, wearing an exoskeleton did not decrease the movement variability of the body's trunk (diff = 0.60, p = 1.00). Therefore, minimally supported lifting through the use of exoskeletons can modify movement in people without LBP and produce reliable lifting movements. Wearing the novel exoskeleton is also desirable for monitoring lifting movements. Future studies should investigate the use of sensors and IMU to monitor lifting movement at work with the least amount of intrusion on an individual's movement.

Effects of 16 weeks of plyometric training on knee biomechanics during the landing phase in athletes.

This study investigated the effects of plyometric training on lower-limb muscle strength and knee biomechanical characteristics during the landing phase. Twenty-four male subjects were recruited for this study with a randomised controlled design. They were randomly divided into a plyometric training group and a traditional training group and underwent training for 16 weeks. Each subject was evaluated every 8 weeks for knee and hip isokinetic muscle strength as well as knee kinematics and kinetics during landing. The results indicated significant group and time interaction effects for knee extension strength (F = 74.942 and p = 0.001), hip extension strength (F = 99.763 and p = 0.000) and hip flexion strength (F = 182.922 and p = 0.000). For landing kinematics, there were significant group main effects for knee flexion angle range (F = 4.429 and p = 0.047), significant time main effects for valgus angle (F = 6.502 and p = 0.011) and significant group and time interaction effects for internal rotation angle range (F = 5.475 and p = 0.008). The group main effect for maximum knee flexion angle was significant (F = 7.534 and p = 0.012), and the group and time interaction effect for maximum internal rotation angle was significant (F = 15.737 and p = 0.001). For landing kinetics, the group main effect of the loading rate was significant (F = 4.576 and p = 0.044). Significant group and time interaction effects were observed for knee extension moment at the moment of maximum vertical ground reaction force (F = 5.095 and p = 0.010) and for abduction moment (F = 8.250 and p = 0.001). These findings suggest that plyometric training leads to greater improvements in hip and knee muscle strength and beneficial changes in knee biomechanics during landing compared to traditional training.

Hip-Knee Motion-Lagged Coordination Mapping Enables Speed Adaptive Walking for Powered Knee Prosthesis.

The commonly used finite-state-machine (FSM) impedance control for powered prostheses deploys diverse control parameters according to different gait phases, resulting in dozens of parameter adjustments and possible gait phase misrecognition. In contrast, this study presents a straightforward, continuous, and speed-adaptive control approach based on hip-knee motion-lagged coordination mapping (MLCM). The mapping, featured by the motion lag, can effectively generate the prosthetic knee's goal gait within a second-order polynomial. It is also verified from extensive gait analysis that the motion lag and polynomial coefficients evolve linearly with respect to walking speed and gait period, promising a simple real-time deployment for prosthesis control. Experimental validation with two non-disabled subjects and two transfemoral amputees wearing a prosthesis demonstrates the MLCM controller's ability to reduce the hip compensatory behavior, generate biomimetic knee kinematics, stance phase time, stride length, and hip-knee motion coordination across various speeds. Furthermore, compared to the benchmark FSM impedance controller, the MLCM controller reduces the number of control parameters from 17 to 7 and avoids misrecognition during gait phase transitions.

Knee Extensor Muscle Strength Associated with the Onset of Depression in Older Japanese Women: The Otassha Study.

We examined whether knee extensor muscle strength can predict the onset of depressive symptoms in older Japanese women living in Tokyo. A baseline comprehensive geriatric examination was conducted to evaluate isometric knee extensor muscle strength and depressive symptoms (using Geriatric Depression Scale [GDS]) in 2017-2019. A free of neurological disease participants received a series of follow-up examinations following an initial evaluation. A GDS score of ≥5 during follow-up marked the onset of depressive symptoms. A logistic regression model was established after adjustment of baseline GDS score for variables including age, body mass index, smoking, alcohol consumption, comorbidities, working status, hobbies, volunteering, years of education, and dietary variety. Of the 1845 recruited individuals, 1409 were eligible to be targeted for follow-up. Among them, 768 women provided two-year follow-up data and contributed the final analysis. After covariate adjustments, the odds ratios (95% confidence interval) for depressive symptoms were 0.68 (0.39, 1.20) and 0.48 (0.26, 0.91) for the middle and highest tertiles of muscle strength, respectively, using the lowest tertile as reference. A dose-response association between muscle strength and depression (p = 0.022) was identified. This study suggests an inverse dose-response relationship between knee extensor muscle strength and the onset of depressive symptoms in older Japanese women.

Explainable Deep-Learning-Based Gait Analysis of Hip-Knee Cyclogram for the Prediction of Adolescent Idiopathic Scoliosis Progression.

Accurate prediction of scoliotic curve progression is crucial for guiding treatment decisions in adolescent idiopathic scoliosis (AIS). Traditional methods of assessing the likelihood of AIS progression are limited by variability and rely on static measurements. This study developed and validated machine learning models for classifying progressive and non-progressive scoliotic curves based on gait analysis using wearable inertial sensors. Gait data from 38 AIS patients were collected using seven inertial measurement unit (IMU) sensors, and hip-knee (HK) cyclograms representing inter-joint coordination were generated. Various machine learning algorithms, including support vector machine (SVM), random forest (RF), and novel deep convolutional neural network (DCNN) models utilizing multi-plane HK cyclograms, were developed and evaluated using 10-fold cross-validation. The DCNN model incorporating multi-plane HK cyclograms and clinical factors achieved an accuracy of 92% in predicting curve progression, outperforming SVM (55% accuracy) and RF (52% accuracy) models using handcrafted gait features. Gradient-based class activation mapping revealed that the DCNN model focused on the swing phase of the gait cycle to make predictions. This study demonstrates the potential of deep learning techniques, and DCNNs in particular, in accurately classifying scoliotic curve progression using gait data from wearable IMU sensors.

Enhancing Walking Performance With a Bilateral Hip Exoskeleton Assistance in Individuals With Above-Knee Amputation.

Transfemoral amputation is a debilitating condition that leads to long-term mobility restriction and secondary disorders that negatively affect the quality of life of millions of individuals worldwide. Currently available prostheses are not able to restore energetically efficient and functional gait, thus, recently, the alternative strategy to inject energy at the residual hip has been proposed to compensate for the lack of energy of the missing leg. Here, we show that a portable and powered hip exoskeleton assisting both the residual and intact limb induced a reduction of walking energy expenditure in four individuals with above-knee amputation. The reduction of the energy expenditure, quantified using the Physiological Cost Index, was in the range [-10, -17]% for all study participants compared to walking without assistance, and between [-2, -24]% in three out of four study participants compared to walking without the device. Additionally, all study participants were able to walk comfortably and confidently with the hip exoskeleton overground at both their self-selected comfortable and fast speed without any observable alterations in gait stability. The study findings confirm that injecting energy at the hip level is a promising approach for individuals with above-knee amputation. By reducing the energy expenditure of walking and facilitating gait, a hip exoskeleton may extend mobility and improve locomotor training of individuals with above-knee amputation, with several positive implications for their quality of life.

Knee Angle Estimation from Surface EMG during Walking Using Attention-Based Deep Recurrent Neural Networks: Feasibility and Initial Demonstration in Cerebral Palsy.

Accurately estimating knee joint angle during walking from surface electromyography (sEMG) signals can enable more natural control of wearable robotics like exoskeletons. However, challenges exist due to variability across individuals and sessions. This study evaluates an attention-based deep recurrent neural network combining gated recurrent units (GRUs) and an attention mechanism (AM) for knee angle estimation. Three experiments were conducted. First, the GRU-AM model was tested on four healthy adolescents, demonstrating improved estimation compared to GRU alone. A sensitivity analysis revealed that the key contributing muscles were the knee flexor and extensors, highlighting the ability of the AM to focus on the most salient inputs. Second, transfer learning was shown by pretraining the model on an open source dataset before additional training and testing on the four adolescents. Third, the model was progressively adapted over three sessions for one child with cerebral palsy (CP). The GRU-AM model demonstrated robust knee angle estimation across participants with healthy participants (mean RMSE 7 degrees) and participants with CP (RMSE 37 degrees). Further, estimation accuracy improved by 14 degrees on average across successive sessions of walking in the child with CP. These results demonstrate the feasibility of using attention-based deep networks for joint angle estimation in adolescents and clinical populations and support their further development for deployment in wearable robotics.

The Accuracy of Height Prediction Equations in Greek Patients: A Cross-Sectional Study.

In clinical settings, standing height measurement is often difficult to perform due to patients' inability to stand upright. Height prediction equations derived from measurements of the length of other body segments have been published; however, they are not readily applicable to all populations since ethnic differences affect the relationship between standing height and body segment length. This cross-sectional study aimed to examine the accuracy of height prediction using the Malnutrition Universal Screening Tool (MUST) height predictive equations among Greek patients and to develop new, nationally representative equations. The study population consisted of 1198 Greek adult outpatients able to stand upright without assistance and without medical conditions that affected their height. Standing height, ulna length, knee height and demi-span measurements were obtained from 599 males and 599 females. Patients were stratified into age groups of <55 and ≥55 years, <60 and ≥60 years and <65 and ≥65 years according to the categories indicated by the MUST for height prediction from alternative measurements. There were positive correlations between standing height and ulna length and knee height and demi-span length (p < 0.001) in both sexes and all age categories. A strong correlation was observed between the measured and predicted standing height using ulna length (rho = 0.870, p < 0.001), knee height (rho = 0.923, p < 0.001) and demi-span length (rho = 0.906, p < 0.001). The average difference between the MUST indicative equations' height predictions from alternative measurements and actual height was -3.04 (-3.32, -2.76), -1.21 (-1.43, -0.988) and 2.16 (1.92, 2.41), respectively. New height prediction equations for Greek patients were identified, with the predicted values closer to the measured standing heights than those predicted with the MUST indicative equations for height prediction from alternative measurements.

The Effect of Duration on Performance and Perceived Fatigability During Acute High-Intensity Interval Exercise in Young, Healthy Males and Females.

Few studies have explored the kinetics of performance and perceived fatigability during high-intensity interval training, despite its popularity. We aimed to characterize the kinetics of fatigability and recovery during an 8 × 4-min HIIT protocol, hypothesizing that most muscle function impairment would occur during the initial four intervals. Fifteen healthy males and females (mean ± standard deviation; age = 26 ± 5 years, V̇O2max = 46.8 ± 6.1 mL·kg-1·min-1) completed eight, 4-min intervals at 105% of critical power with 3 min of rest. Maximal voluntary knee extension contractions (MVCs) coupled with electrical nerve stimulation were performed at baseline and after the first, fourth, and eighth intervals. MVC, potentiated twitch force (Pt), and Db10:100 ratio all declined throughout HIIT (p < 0.05). MVC sharply declined after interval 1 (-15 ± 9% relative to baseline; p < 0.05) and had only further declined after interval 8 (-26 ± 11%; p < 0.05), but not interval 4 (-19 ± 13%; p > 0.05). Pt and Db10:100 also sharply declined after interval 1 (Pt: -18 ± 13%, Db10:100: -14 ± 20%; p < 0.05) and further declined after interval 4 (Pt: -35 ± 19%, Db10:100: -30 ± 20%; p < 0.05) but not interval 8 (Pt: -41 ± 19%; Db10:100: -32 ± 18%; p > 0.05). Voluntary activation did not significantly change across the HIIT protocol (p > 0.05). Evoked force recovery was significantly blunted as more intervals were completed: after interval 1, Pt recovered by 7 ± 11% compared to -6 ± 7% recovery after interval 8 (p < 0.05). Ratings of perceived effort, fatigue, and leg pain rose throughout the session (p < 0.05 for each) and were greater (effort and fatigue) for females (p < 0.05). Otherwise, males and females exhibited similar performance fatigability kinetics, with contractile function declines blunted in response to additional intervals.

Effect of the Material Properties and Knee Position to the Bone Bruise Pattern in Skeletally Mature and Immature Subjects.

A bone bruise is generated by a bony collision that could occur when the anterior cruciate ligament (ACL) is injured, and its pattern reflects the injury mechanism and skeletal maturity. Thus, the bone bruise pattern is useful to predict a subject-specific injury mechanism, although the sensitivity and/or effect of the material property and the knee position at injury is still unclear. The objective of the present study was to determine the effect of the material property and knee position on the bone bruise pattern in skeletally mature and immature subjects using finite element analysis. Finite element models were created from a magnetic resonance (MR) image in the sagittal plane of a skeletally mature (25 y. o.) and immature (9 y. o.) male subject. The femur and tibia were collided at 2 m/s to simulate the impact trauma and determine the maximum principal stress. The analysis was performed at 15, 30, and 45 deg of knee flexion, and neutral, 10 mm anterior and posterior translated position at each knee flexion angle. Although high stress was distributed toward the metaphysis area in the mature model, the stress did not cross the growth plate in the immature model. The size of the stress area was larger in the mature model than those in the immature model. The location of the stress area changed depending on the joint position. Young's modulus of cartilage and trabecular bone also affected the location of the stress area. The Young's modulus for the cartilage affected peak stress during impact, while the size of the stress area had almost no change. These results indicate that the bone bruise pattern is strongly associated with subject-specific parameters. In addition, the bone bruise pattern was affected not only by knee position but also by tissue qualities. In conclusion, although the bone bruise distribution was generally called footprint of the injury, the combined evaluation of the quality of the structure and the bone bruise distribution is necessary for properly diagnosing tissue injury based on the MR imaging.

Using a statistical shape model to estimate the knee landmarks for aligning femurs for femoral finite element models.

BACKGROUND AND OBJECTIVE: The BOne Strength (BOS) score is a CT-based tool to assess fracture risk for patients with femoral bone metastases using finite element (FE) models. Until now, the knee joint center (KJC) and centers of the condyles (CoCs) were needed to create the FE model, hence BOS scores of incompletely scanned femurs could not be calculated. In this study, a statistical shape model (SSM) was used to align FE models of femurs with a removed knee anatomy. The aim was to determine the effect of using an SSM with different proximal femur fractions on KJC and CoC locations, and on the BOS score. METHODS: QCT scans of 117 femurs were used to generate patient-specific FE models of the proximal femur. These models were aligned using the knee joint center (KJC), center of condyles (CoC) and femoral head center. The femurs were artificially shortened by removing 30 %, 50 % or 70 % of the femur. A recently developed SSM was used to reconstruct the distal femur. For each of the femur fractions, the difference between the original and SSM-reconstructed KJC and CoC were determined and the BOS scores were calculated. RESULTS: Although the individual differences between the original and SSM-reconstructed KJC and CoC location could be large, the effect on the individual BOS scores was limited. The SSM-reconstructed BOS scores were highly correlated to the original BOS scores. CONCLUSION: Using SSM to align femurs with a removed knee anatomy resulted in varying estimation of knee anatomy between patients but relatively accurate BOS scores.

Fair AI-powered orthopedic image segmentation: addressing bias and promoting equitable healthcare.

AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment. Despite the remarkable advancements in AI algorithms for medical imaging, the potential for biases inherent within these models remains largely unexplored. This study tackles these concerns by thoroughly re-examining AI-driven segmentation for hip and knee bony anatomy. While advanced imaging modalities like CT and MRI offer comprehensive views, plain radiographs (X-rays) predominate the standard initial clinical assessment due to their widespread availability, low cost, and rapid acquisition. Hence, we focused on plain radiographs to ensure the utilization of our contribution in diverse healthcare settings, including those with limited access to advanced imaging technologies. This work provides insights into the underlying causes of biases in AI-based knee and hip image segmentation through an extensive evaluation, presenting targeted mitigation strategies to alleviate biases related to sex, race, and age, using an automatic segmentation that is fair, impartial, and safe in the context of AI. Our contribution can enhance inclusivity, ethical practices, equity, and an unbiased healthcare environment with advanced clinical outcomes, aiding decision-making and osteoarthritis research. Furthermore, we have made all the codes and datasets publicly and freely accessible to promote open scientific research.

Torque and power of knee extensor muscles at individualized isokinetic angular velocities.

OBJECTIVE: Existing isokinetic contractions are characterized using standardized angular velocities, which can induce differing adaptations. Here, we characterized the variation in the isokinetic parameters of knee extensors according to individualized angular velocity (IAV). METHODS: We performed a cross-sectional study of 19 young, healthy men. We measured the maximum angular velocity (MAV) of concentric knee extension using the isotonic mode of an isokinetic dynamometer. Isometric and isokinetic (at angular velocities corresponding to 100%, 70%, 40%, and 10% of each individual's MAV) knee extensor contractions were performed, and the peak torque and mean power were recorded. RESULTS: Peak torque significantly decreased with increasing IAV (129.42 ± 25.04, 84.37 ± 20.97, and 56.42 ± 16.18 Nm at 40%, 70%, and 100%, respectively), except for isometric contraction (233.36 ± 47.85) and at 10% of MAV (208 ± 48.55). At the mean power, 10% of MAV (74.52 ± 20.84 W) was significantly lower than the faster IAV (176.32 ± 49.64, 161.53 ± 56.55, and 145.95 ± 50.64 W at 40%, 70%, and 100%, respectively), and 100% was significantly lower than 40%. CONCLUSION: The optimized IAV for isokinetic contraction to improve power output while maintaining torque is 10% to 40% of MAV. IAV may reflect both the velocity and force components of power because individuals do not have the same angular velocity.

Human-in-the-Loop Optimization of Knee Exoskeleton Assistance for Minimizing User's Metabolic and Muscular Effort.

Lower limb exoskeletons have the potential to mitigate work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls adapt an exoskeleton's assistance in real time, to optimize the user-exoskeleton interaction. This study presents a HITL control for a knee exoskeleton using a CMA-ES algorithm to minimize the users' physical effort, a parameter innovatively evaluated using the interaction torque with the exoskeleton (a muscular effort indicator) and metabolic cost. This work innovates by estimating the user's metabolic cost within the HITL control through a machine-learning model. The regression model estimated the metabolic cost, in real time, with a root mean squared error of 0.66 W/kg and mean absolute percentage error of 26% (n = 5), making faster (10 s) and less noisy estimations than a respirometer (K5, Cosmed). The HITL reduced the user's metabolic cost by 7.3% and 5.9% compared to the zero-torque and no-device conditions, respectively, and reduced the interaction torque by 32.3% compared to a zero-torque control (n = 1). The developed HITL control surpassed a non-exoskeleton and zero-torque condition regarding the user's physical effort, even for a task such as slow walking. Furthermore, the user-specific control had a lower metabolic cost than the non-user-specific assistance. This proof-of-concept demonstrated the potential of HITL controls in assisted walking.

Validation of Inertial-Measurement-Unit-Based Ex Vivo Knee Kinematics during a Loaded Squat before and after Reference-Frame-Orientation Optimisation.

Recently, inertial measurement units have been gaining popularity as a potential alternative to optical motion capture systems in the analysis of joint kinematics. In a previous study, the accuracy of knee joint angles calculated from inertial data and an extended Kalman filter and smoother algorithm was tested using ground truth data originating from a joint simulator guided by fluoroscopy-based signals. Although high levels of accuracy were achieved, the experimental setup leveraged multiple iterations of the same movement pattern and an absence of soft tissue artefacts. Here, the algorithm is tested against an optical marker-based system in a more challenging setting, with single iterations of a loaded squat cycle simulated on seven cadaveric specimens on a force-controlled knee rig. Prior to the optimisation of local coordinate systems using the REference FRame Alignment MEthod (REFRAME) to account for the effect of differences in local reference frame orientation, root-mean-square errors between the kinematic signals of the inertial and optical systems were as high as 3.8° ± 3.5° for flexion/extension, 20.4° ± 10.0° for abduction/adduction and 8.6° ± 5.7° for external/internal rotation. After REFRAME implementation, however, average root-mean-square errors decreased to 0.9° ± 0.4° and to 1.5° ± 0.7° for abduction/adduction and for external/internal rotation, respectively, with a slight increase to 4.2° ± 3.6° for flexion/extension. While these results demonstrate promising potential in the approach's ability to estimate knee joint angles during a single loaded squat cycle, they highlight the limiting effects that a reduced number of iterations and the lack of a reliable consistent reference pose inflicts on the sensor fusion algorithm's performance. They similarly stress the importance of adapting underlying assumptions and correctly tuning filter parameters to ensure satisfactory performance. More importantly, our findings emphasise the notable impact that properly aligning reference-frame orientations before comparing joint kinematics can have on results and the conclusions derived from them.

Neuromuscular Adaptations in Endurance-Trained Male Adolescents Versus Untrained Peers: A 9-Month Longitudinal Study.

BACKGROUND: Neuromuscular function is considered as a determinant factor of endurance performance during adulthood. However, whether endurance training triggers further neuromuscular adaptations exceeding those of growth and maturation alone over the rapid adolescent growth period is yet to be determined. OBJECTIVE: The present study investigated the concurrent role of growth, maturation, and endurance training on neuromuscular function through a 9-month training period in adolescent triathletes. METHODS: Thirty-eight 13- to 15-year-old males (23 triathletes [~6 h/week endurance training] and 15 untrained [<2 h/week endurance activity]) were evaluated before and after a 9-month triathlon training season. Maximal oxygen uptake (V̇O2max) and power at V̇O2max were assessed during incremental cycling. Knee extensor maximal voluntary isometric contraction torque (MVCISO) was measured and the voluntary activation level (VAL) was determined using the twitch interpolation technique. Knee extensor doublet peak torque (T100Hz) and normalized vastus lateralis (VL) electromyographic activity (EMG/M-wave) were also determined. VL and rectus femoris (RF) muscle architecture was assessed using ultrasonography. RESULTS: Absolute V̇O2max increased similarly in both groups but power at V̇O2max only significantly increased in triathletes (+13.8%). MVCISO (+14.4%), VL (+4.4%), and RF (+15.8%) muscle thicknesses and RF pennation angle (+22.1%) increased over the 9-month period in both groups similarly (p < 0.01), although no changes were observed in T100Hz, VAL, or VL EMG/M-wave. No changes were detected in any neuromuscular variables, except for coactivation. CONCLUSION: Endurance training did not induce detectible, additional neuromuscular adaptations. However, the training-specific cycling power improvement in triathletes may reflect continued skill enhancement over the training period.

Effects of plyometric training techniques on vertical jump performance of basketball players.

The aim of our study was to compare the effects of two different plyometric training programs (targeting knee extensors or plantar flexors) on jump height and strength of leg muscles. Twenty-nine male basketball players were assigned to the knee-flexed (KF), knee-extended (KE), or control groups. In addition to regular training, the KF group performed plyometric jumps (10 sets of 10 jumps, 3 sessions/week, 4 weeks) from 50 cm boxes with the knee flexed (90°-120°), whereas the KE group performed the jumps from 30 cm boxes with the knee much more extended (130°-170°). Jumping ability was evaluated with squat jumps (SJs), countermovement jumps (CMJs), and drop jumps from 20 cm (DJ20) and 40 cm (DJ40). Knee and ankle muscles were assessed during maximal isokinetic and isometric tests, and EMG activity was recorded from vastus lateralis and medial gastrocnemius. The KF group increased SJ (+10%, d = 0.86) and CMJ (+11%, d = 0.70) but decreased DJ40 height (-7%, d = -0.40). Conversely, the KE group increased DJ20 (+10%, d = 0.74) and DJ40 (+12%, d = 0.77) but decreased SJ height (-4%, d = -0.23). The reactivity index during DJs increased (+10% for DJ20, d = 0.47; +20% for DJ40, d = 0.91) for the KE group but decreased (-10%, d = -0.48) for the KF group during DJ40. Plantar flexor strength increased for the KE group (d = 0.72-1.00) but not for the KF group. Negative transfer across jumps is consistent with the principle of training specificity. Basketball players interested to perform fast rebounds in their training should avoid plyometric jumps with large knee flexions and long contact times.