Lower Limb Electromyography Research Articles

A novel balance index for preliminary assessment of proprioception based on a balance-cognitive study

Finding a quick and accurate method for evaluating proprioception is useful for improving performance which is the main objective of the current research. This paper presents a novel index, called the Synergy Balance Index (SBI), that leverages lower limb electromyography signals for the evaluation of proprioception. The concept has been tested on a set of balance tasks performed by 23 healthy subjects on a ∞-shape path. The capability of the SBI has been investigated using two ways, classification and monitoring. Also, the relationship between the features extracted from the recorded signals was investigated by calculating the correlation coefficient. The findings suggest that in the absence of sufficient and accurate information on individuals, this index can only differentiate groups if there is a significant difference in their proprioception. All of the evaluated criteria were obtained above 95 percent. This index was effective when used with equal conditions and comparisons of each individual with himself over multiple stages of proprioception training that included two tasks (balance, and cognitive). The index showed increased proprioception performance after just one training session, showing its possible sensitivity and speed. The SBI is a quick, low-cost, and easy-to-use index for assessing a person’s proprioception. It has potential applications in rehabilitation, neurology, and sports biology. Enhanced research in this area could result in better patient care. The small sample size and the lack of a diverse population group limit the study. This can be fixed by gathering more data from a larger and more diverse set of participants.

Estimation of electrical muscle activity during gait using inertial measurement units with convolution attention neural network and small-scale dataset

In general, muscle activity can be directly measured using Electromyography (EMG) or calculated with musculoskeletal models. However, both methods are not suitable for non-technical users and unstructured environments. It is desired to establish more portable and easy-to-use muscle activity estimation methods. Deep learning (DL) models combined with inertial measurement units (IMUs) have shown great potential to estimate muscle activity. However, it frequently occurs in clinical scenarios that a very small amount of data is available and leads to limited performance of the DL models, while the augmentation techniques to efficiently expand a small sample size for DL model training are rarely used. The primary aim of the present study was to develop a novel DL model to estimate the EMG envelope during gait using IMUs with high accuracy. A secondary aim was to develop a novel model-based data augmentation method to improve the performance of the estimation model with small-scale dataset. Therefore, in the present study, a time convolutional network-based generative adversarial network, namely MuscleGAN, was proposed for data augmentation. Moreover, a subject-independent regression DL model was developed to estimate EMG envelope. Results suggested that the proposed two-stage method has better generalization and estimation performance than the commonly used existing methods. Pearson correlation coefficient and normalized root-mean-square errors derived from the proposed method reached up to 0.72 and 0.13, respectively. It was indicated that the MuscleGAN indeed improved the estimation accuracy of lower limb EMG envelope from 70% to 72%. Thus, even using only two IMUs and a very small-scale dataset, the proposed model is still capable of accurately estimating lower limb EMG envelope, demonstrating considerable potential for its application in clinical and daily life scenarios.

Neuromuscular mechanisms of motor adaptation to repeated treadmill-slip perturbations during stance in healthy young adults.

Treadmill-based repeated perturbation training (PBT) induces motor adaptation in reactive balance responses, thus lowering the risk of slip-induced falls. However, little evidence exists regarding intervention-induced changes in neuromuscular control underlying motor adaptation. Examining neuromuscular changes could be an important step in identifying key elements of adaptation and evaluating treadmill training protocols for fall prevention. Moreover, identifying the muscle synergies contributing to motor adaptation in young adults could lay the groundwork for comparison with high fall-risk populations. Thus, we aimed to investigate neuromuscular changes in reactive balance responses during stance slip-PBT. Lower limb electromyography (EMG) signals (4/leg) were recorded during ten repeated forward stance (slip-like) perturbations in twenty-six young adults. Muscle synergies were compared between early-training (slips 1-2) and late-training (slips 9-10) stages. Results showed that 5 different modes of synergies (named on dominant muscles: WTA, WS_VLAT, WR_GAS, WR_VLAT, and WS_GAS) were recruited in both stages. 3 out of 5 synergies (WTA, WR_VLAT, and WS_GAS) showed a high similarity (r>0.97) in structure and activation between stages, whereas WR_GAS and WS_VLAT showed a lower similarity (r<0.83) between the two stages, and the area of activation in WTA, the peak value of activation in WR_VLAT and the activation onset in WR_GAS showed a reduction from early-to late-training stage (p<0.05). These results suggest that a block of stance slip-PBT resulted in modest changes in muscle synergies in young adults, which might explain the smaller changes seen in biomechanical variables. Future studies should examine neuromuscular changes in people at high risk of falls.

Cross-domain prediction approach of human lower limb voluntary movement intention for exoskeleton robot based on EEG signals.

Exoskeleton robot control should ideally be based on human voluntary movement intention. The readiness potential (RP) component of the motion-related cortical potential is observed before movement in the electroencephalogram and can be used for intention prediction. However, its single-trial features are weak and highly variable, and existing methods cannot achieve high cross-temporal and cross-subject accuracies in practical online applications. Therefore, this work aimed to combine a deep convolutional neural network (CNN) framework with a transfer learning (TL) strategy to predict the lower limb voluntary movement intention, thereby improving the accuracy while enhancing the model generalization capability; this would also provide sufficient processing time for the response of the exoskeleton robotic system and help realize robot control based on the intention of the human body. The signal characteristics of the RP for lower limb movement were analyzed, and a parameter TL strategy based on CNN was proposed to predict the intention of voluntary lower limb movements. We recruited 10 subjects for offline and online experiments. Multivariate empirical-mode decomposition was used to remove the artifacts, and the moment of onset of voluntary movement was labeled using lower limb electromyography signals during network training. The RP features can be observed from multiple data overlays before the onset of voluntary lower limb movements, and these features have long latency periods. The offline experimental results showed that the average movement intention prediction accuracy was 95.23% ± 1.25% for the right leg and 91.21% ± 1.48% for the left leg, which showed good cross-temporal and cross-subject generalization while greatly reducing the training time. Online movement intention prediction can predict results about 483.9 ± 11.9ms before movement onset with an average accuracy of 82.75%. The proposed method has a higher prediction accuracy with a lower training time, has good generalization performance for cross-temporal and cross-subject aspects, and is well-prioritized in terms of the temporal responses; these features are expected to lay the foundation for further investigations on exoskeleton robot control.

Hamstring harvest results in significantly reduced knee muscular protection during side-step cutting two years after anterior cruciate ligament reconstruction.

The purpose of this study was to determine the effect of donor muscle morphology following tendon harvest in anterior cruciate ligament (ACL) reconstruction on muscular support of the tibiofemoral joint during sidestep cutting. Magnetic resonance imaging (MRI) was used to measure peak cross-sectional area (CSA) and volume of the semitendinosus (ST) and gracilis (GR) muscles and tendons (bilaterally) in 18 individuals following ACL reconstruction. Participants performed sidestep cutting tasks in a biomechanics laboratory during which lower-limb electromyography, ground reaction loads, whole-body motions were recorded. An EMG driven neuro-musculoskeletal model was subsequently used to determine force from 34 musculotendinous units of the lower limb and the contribution of the ST and GR to muscular support of the tibiofemoral joint based on a normal muscle-tendon model (Standard model). Then, differences in peak CSA and volume between the ipsilateral/contralateral ST and GR were used to adjust their muscle-tendon parameters in the model followed by a recalibration to determine muscle force for 34 musculotendinous units (Adjusted model). The combined contribution of the donor muscles to muscular support about the medial and lateral compartments were reduced by 52% and 42%, respectively, in the adjusted compared to standard model. While the semimembranosus (SM) increased its contribution to muscular stabilisation about the medial and lateral compartment by 23% and 30%, respectively. This computer simulation study demonstrated the muscles harvested for ACL reconstruction reduced their support of the tibiofemoral joint during sidestep cutting, while the SM may have the potential to partially offset these reductions. This suggests donor muscle impairment could be a factor that contributes to ipsilateral re-injury rates to the ACL following return to sport.

Sex Difference in Lower-limb Electromyography and Kinematics when Using Resistance Bands during a Barbell Back Squat.

The aim of this study was to compare the muscle activity of the gluteus medius (GMe), gluteus maximus (GMa), biceps femoris (BF), vastus lateralis (VL), vastus medialis (VM) and erector spinae (ES) as well as medial knee displacement (MKD) while using varying stiffness resistance bands (red: 1.68 kg; black: 3.31 kg; gold: 6.44 kg) during a barbell back squat (BBS) among males and females. A total of 23 (females: 11) resistance trained people were recruited for this study. Muscle activity was measured using electromyography, and motion capture cameras tracked lower-limb kinematics and MKD. Three resistance bands were placed at the distal end of the femur while performing a BBS at their 85% repetition maximum (RM). Parametric and non-parametric statistical analyses were conducted with the alpha level of 0.05. The gold resistance band resulted in a smaller knee-width-index value (i.e., greater MKD) compared to other bands (p < 0.01). Males exhibited less MKD compared to females during the BBS for each resistance band (p = 0.04). Males produced greater VL activity when using the black and gold resistance bands during the BBS (p = 0.03). When using a gold resistance band, the GMe muscle activation was higher compared to other resistance bands (p < 0.01). VM muscle activity was reduced when using a gold resistance band compared to no band condition (p < 0.01). BF (p = 0.39) and ES (p = 0.88) muscle activity did not change when using different resistance bands. As a result, females may be at a biomechanical disadvantage when using resistance bands compared to males while performing the BBS hindering them from optimal performance.

Snowboard Landings from Different Heights: Electroencephalography Activity in Motor Preparation and Lower Limb Electromyography Changes.

The neural strategies for movements of the lower extremities for landings from different landing heights in trained half-pipe snowboarders are not well known. We observed changes in brain activity as measured by electroencephalography (EEG) and lower limb muscle activity as measured by electromyography (EMG) in trained and untrained half-pipe snowboarders landing from different heights (30 and 60cm). There were 12 trained male half-pipe snowboarders (HS) and 12 untrained participants (UP). We recorded EEG signals during motor preparation prior to dropping and EMG signals from right lateral rectus femoris (RF), tibialis anterior (TA), and gastrocnemius lateralis (GL) muscles during landings. Generally, theta power in the frontal cortex significantly increased in the preparation period compared to the resting state, while the alpha 1 and alpha 2 power values in central and parietal cortical areas decreased as dropping heights increased. Additionally, the HS group displayed greater magnitudes of change in power values in three frequency bands compared to the UP group. The HS group (relative to UP group) also showed higher normalized EMG amplitudes for RF and GL during contact, especially at 60cm. The HS group (relative to the UP group) presented lower antagonist EMG activity and a higher GL/TA ratio at the 60cm dropping height. Long-term specialized training might lead to greater neural modulation of predictive sensorimotor control and specific neuromuscular activation patterns during landing.

Balance Perturbations in Simulated Low-Gravity Modulate Human Premotor and Frontoparietal Electrocortical Theta, Alpha, and Beta Band Spectral Power

We aimed to identify the influence of bodyweight unloading on healthy human electrical brain and muscle dynamics during standing balance. Using an underwater environment to simulate reduced gravity, we recorded high-density electroencephalography and lower limb electromyography from 10 individuals (5 female). During five standing balance conditions, we adjusted the water depth (1: on-land, 2: chest-level, 3: waist-level) and applied external fluid forces to the front of the body in the posterior direction (4: low and 5: high external fluid forces). Reduced bodyweight decreased ankle plantar flexor muscle activity and increased alpha band (8-13 Hz) spectral power from right premotor cortex. Underwater balance perturbations increased muscle activations surrounding the ankle and knee joints and increased theta band (4-8 Hz) spectral power from right premotor cortex. Concurrently, alpha and beta band (13-30 Hz) spectral power decreased from left prefrontal and right premotor cortices, along with reduced alpha band spectral power from left parietal cortex.

Influence of the number of muscles and strides on selective motor control during gait in individuals with cerebral palsy

ObjectiveTo evaluate the influence of the number of muscles and strides on estimating motor control accuracy during treadmill-gait, in individuals with cerebral palsy (CP). MethodsBilateral lower limb electromyography data were extracted for 44 children/adolescents with CP. The number of synergy solutions required to explain 90 % of the variance (tVAF-threshold) and the total variance accounted for by one synergy (tVAF1) were calculated for a different number of strides (between 5 and 50) and muscles both unilaterally (four to seven) and bilaterally (eight to 14). The kappa and intraclass correlation coefficients were used to assess similarities in tVAF-threshold and tVAF1 between the different number of strides and muscle sets. ResultsIn both analyses, the number of muscles influenced the tVAF-threshold. Additionally, using <30 strides led to only substantial-moderate agreement with 50 strides (k < 0.80). In both analyses, the mean tVAF1 values demonstrated high-agreement between the different number of muscles (intraclass-correlations = 0.88–0.93) and strides (intraclass-correlations = 0.96–0.99); In the group level, it may result in an error of ≤2.3 %. However, in the individual level, using different number of muscles or <40 strides may result in an error of ≥6 %. ConclusionDiffering numbers of muscles and strides did not influence the group mean tVAF1 value, but it influenced the tVAF-threshold value. In addition, using different number of muscles or strides can lead to a large measurement error in the individual tVAF1 value.

Lower Limb Biomechanics During Drop-Jump Landings on Challenging Surfaces in Individuals With Chronic Ankle Instability.

Individuals with chronic ankle instability (CAI) exhibit impaired lower limb biomechanics during unilateral drop-jump landings on a flat surface. However, lower limb biomechanical adaptations during unilateral drop-jump landings on more challenging surfaces, such as those that are unstable or inclined, have not been described. To determine how unilateral drop-jump landing surfaces (flat, unstable, and inclined) influence lower limb electromyography, kinematics, and kinetics in individuals with CAI. Descriptive laboratory study. Biomechanics laboratory. A total of 22 young adults (age = 24.9 ± 4.9 years, height = 1.68 ± 0.08 m, mass = 70.6 ± 11.4 kg) with CAI. Participants completed 5 trials each of unilateral drop-jump landings on a flat surface (DROP), an unstable surface (FOAM), and a laterally inclined surface (WEDGE). Electromyography of the gluteus medius, vastus lateralis, gastrocnemius medialis, peroneus longus, and tibialis anterior muscles was recorded. Ankle and knee angles and moments were calculated using a 3-dimensional motion-analysis system and a force plate. Biomechanical variables were compared among tasks using 1-dimensional statistical nonparametric mapping. During DROP, greater ankle-dorsiflexion and knee-extension moments were observed than during FOAM and WEDGE and greater vastus lateralis muscle activity was observed than during FOAM. Greater ankle-inversion and plantar-flexion angles were noted during FOAM and WEDGE than during DROP. Peroneus longus muscle activity was greater during DROP than during FOAM. During FOAM, greater ankle-inversion and knee-extension angles and ankle-inversion and internal-rotation moments, as well as less peroneus longus muscle activity, were present than during WEDGE. The greater ankle-inversion and plantar-flexion angles as well as the lack of increased peroneus longus muscle activation during the FOAM and WEDGE conditions could increase the risk of recurrent lateral ankle sprain in individuals with CAI. These findings improve our understanding of the changes in lower limb biomechanics when landing on more challenging surfaces and will help clinicians better target deficits associated with CAI during rehabilitation.

Muscle force estimation from lower limb EMG signals using novel optimised machine learning techniques

The main objective of this work is to establish a framework for processing and evaluating the lower limb electromyography (EMG) signals ready to be fed to a rehabilitation robot. We design and build a knee rehabilitation robot that works with surface EMG (sEMG) signals. In our device, the muscle forces are estimated from sEMG signals using several machine learning techniques, i.e. support vector machine (SVM), support vector regression (SVR) and random forest (RF). In order to improve the estimation accuracy, we devise genetic algorithm (GA) for parameter optimisation and feature extraction within the proposed methods. At the same time, a load cell and a wearable inertial measurement unit (IMU) are mounted on the robot to measure the muscle force and knee joint angle, respectively. Various performance measures have been employed to assess the performance of the proposed system. Our extensive experiments and comparison with related works revealed a high estimation accuracy of 98.67% for lower limb muscles. The main advantage of the proposed techniques is high estimation accuracy leading to improved performance of the therapy while muscle models become especially sensitive to the tendon stiffness and the slack length.Graphical

Research on Joint-Angle Prediction Based on Artificial Neural Network for Above-Knee Amputees.

In the current study, our research group proposed an asymmetric lower extremity exoskeleton to enable above-knee amputees to walk with a load. Due to the absence of shank and foot, the knee and ankle joint at the amputation side of the exoskeleton lack tracking targets, so it is difficult to realize the function of assisted walking when going up and downstairs. Currently, the use of lower-limb electromyography to predict the angles of lower limb joints has achieved remarkable results. However, the prediction effect was poor when only using electromyography from the thigh. Therefore, this paper introduces hip-angle and plantar pressure signals for improving prediction effect and puts forward a joint prediction method of knee- and ankle-joint angles by electromyography of the thigh, hip-joint angle, and plantar pressure signals. The generalized regression neural network optimized by the golden section method is used to predict the joint angles. Finally, the parameters (the maximum error, the Root-Mean-Square error (RMSE), and correlation coefficient ()) were calculated to verify the feasibility of the prediction method.

Analysis and Recognition of Human Lower Limb Motions Based on Electromyography (EMG) Signals

Background: This paper focuses on the characteristics of lower limb EMG signals for common movements. Methods: We obtained length data for lower limb muscles during gait motion using software named OpenSim; statistical product and service solutions (SPSS) were utilized to study the correlation between each muscle, based on gait data. Low-correlation muscles in different regions were selected; inertial measurement unit (IMU) and EMG sensors were used to measure the lower limb angles and EMG signals when on seven kinds of slope, in five kinds of gait (walking on flat ground, uphill, downhill, up-step and down-step) and four kinds of movement (squat, lunge, raised leg and standing up). Results: After data denoising and feature extraction, we designed a double hidden-layer BP neural network to recognize the above motions according to EMG signals. Results show that EMG signals of selected muscles have a certain periodicity in the process of movement that can be used to identify lower limb movements. Conclusions: It can be seen, after the recognition of different proportions of training and testing sets that the average recognition rate of the BP neural network is 86.49% for seven gradients, 93.76% for five kinds of gait and 86.07% for four kinds of movements.

Lower-Limb Electromyography Signal Analysis for the Bottom Group of Muscles Fitness Norm before and after Intensive Exercise

Muscular fitness is not only the ability of the body to adapt to work and the environment but also the operational ability of physical behavior. We speculated whether research could be conducted on the theory of muscular fitness and its qualitative/quantitative relationship based on muscular fitness and exercise physiology from the perspective of muscular endurance and muscular exploration. This study used standing long jumps as a standard metric for physical fitness to identify the bottom 20% groups. The experiment involved eight freshmen from the bottom 20% groups, and the pre-tests of the participants’ electromyography (EMG) signals under different exercise intensities were measured and after performing a set of intensive exercises for post-tests. The signal’ characteristics measured in time and frequency domains were analyzed to find the correlation between them and the participants’ muscular fitness. Weighted squats were chosen as the strength movements, which were separated into an exercise experiment and a force plate experiment. Both experiments included three different exercise intensities: 8 repetition maximum (RM), 18RM, and 28RM. The EMG signals were captured and analyzed in both time and the frequency domains. Finally, paired sample tests were performed to determine the difference of features under different exercise intensities. The comparison of readings before and after intensive exercises shows that, for the exercised experiment, a significant difference in the mean absolute (MAV), the variance of EMG (VAR), the root mean square value (RMS), and the average amplitude of change (AAC) was observed under 8RM. Under 18RM, MAV, VAR, and AAC showed a significant difference. In the force plate experiment, RMS, AAC, mean frequency (MNF), and median frequency (MDF) showed a statistically significant difference under the intensity of 18RM. As for intensity under 28RM, MAV, VAR, RMS, and AAC also showed significant difference.

Reduced joint motion supersedes asymmetry in explaining increased metabolic demand during walking with mechanical restriction

Recent research has highlighted the complex interactions among chronic injury- or disease-induced joint limitations, walking asymmetry, and increased metabolic cost. Determining the specific metabolic impacts of asymmetry or joint impairment in clinical populations is difficult because of concurrent neurological and physiological changes. This work investigates the metabolic impact of gait asymmetry and joint restriction by unilaterally (asymmetric) and bilaterally (symmetric) restricting ankle, knee, and combined ankle and knee ranges of motion in unimpaired individuals. We calculated propulsive asymmetry, temporal asymmetry, and step-length asymmetry for an average gait cycle; metabolic rate; average positive center of mass power using the individual limbs method; and muscle effort using lower limb electromyography measurements weighted by corresponding physiological cross-sectional areas. Unilateral restriction caused propulsive and temporal asymmetry but less metabolically expensive gait than bilateral restriction. Changes in asymmetry did not correlate with changes in metabolic cost. Interestingly, bilateral restriction increased average positive center of mass power compared to unilateral restriction. Further, increased average positive center of mass power correlated with increased energy costs, suggesting asymmetric step-to-step transitions did not drive metabolic changes. The number of restricted joints reduces available degrees of freedom and may have a larger metabolic impact than gait asymmetry, as this correlated significantly with increases in metabolic rate for 7/9 participants. These results emphasize symmetry is not by definition metabolically optimal, indicate that the mechanics underlying symmetry are meaningful, and suggest that available degrees of freedom should be considered in designing future interventions.

Effect of jaw clenching on postural adjustments to a predictable external perturbation

This study investigated the effect of jaw clenching on anticipatory postural adjustments (APAs) and reactive postural adjustments (RPAs). Eight healthy adults were exposed to predictable external perturbations with and without submaximal jaw clenching. We recorded the three-dimensional body kinematics, ground reaction forces, and electromyography (EMG) of 12 muscles. EMG onset, integrated EMG, and positions of the center-of-mass (COM) and center-of-pressure (COP) during the anticipatory and reactive phases of postural adjustments were computed and compared for the jaw clenching and control conditions. Jaw clenching resulted in an earlier onset of APAs and a greater amplitude of trunk and lower limb EMG activities in the APAs and RPAs. There were no differences in the COM and COP displacements after the perturbation. Jaw clenching is effective for enhancing APAs and RPAs, although it may not increase postural stability following predictable external perturbation in healthy adults.

Effects of Electromyographic Biofeedback Therapy Combined with Comprehensive Rehabilitation Training on Lower Limb Motor Function in Patients with Stroke Recovery

This article explores the effects of myoelectric biofeedback therapy association with rehabilitation training on LLMF in patients with stroke and hemiplegia. Sixty patients with stroke and hemiplegia were separated into the control group and the treatment group. The two groups were disposed neuromedicine drugs and rehabilitation training, while the treatment group also increased the training of the affected side's lower limb electromyography. The same therapist evaluated Fugl-Meyer score (FMA), M-B index (MBI), Berg Balance Scale (BBS), score before and 4 weeks after treatment, and performed statistical analysis. The results showed that the FMA scores, balance ability scores, daily living ability scores, and active range scores of the wrist and stepping joints of the upper and lower limbs after several weeks of treatment in the two groups were better than those in the group before treatment. The scores of the EMG biofeedback treatment group at several weeks were better than the control group of the same period, the difference was statistically significant. EMG Biofeedback Therapy Combined with Comprehensive Rehabilitation Training can effectively improve upper and lower extremity movement, balance function, daily life ability, dorsiflexion of the wrist and dorsiflexion of the step joints after stroke, and the effect is better than that of conventional rehabilitation therapy.

Research on the characteristics of lower limb electromyography and fatigue of 400m Sprinters

The main muscle groups in the non-terminal straight line were gastrocnemius muscle, biceps femoris muscle, lateral femoris muscle and medial femoris muscle; The range of the main muscle groups during the entire cushioning and thrusting and extension phases is very stable. The cushioning phase is the gastrocnemius, biceps femoris, tibial anterior muscle, and lateral femoris; the thrusting and extension phases are the medial femoris, lateral femoris, and biceps femoris, Gastrocnemius; Rhythm has no significant difference in the MPF of each muscle group in the non-end-point straight and the end-point straight (P>0.05), and the MPF of each muscle group in the end-point straight has a downward trend.

Lower-Limb Electromyography Signal Analysis of Distinct Muscle Fitness Norms under Graded Exercise Intensity

Physical fitness is the overall ability of the body to adapt to the working environment and perform sporting and daily activities. The aim of this study was to analyze the correlation between muscle fitness and the electromyography (EMG) signals of lower limbs under varying exercise intensity. The standing long jump was used as a test task for assessing the power of the lower limb muscles. Participants were university freshmen who belonged to the top 20%, middle 20%, and bottom 20% groups in terms of physical fitness norms. The EMG signals of the participants’ lower limbs while they performed squats were collected under four exercise intensities of repetitions maximum (RM): no load, 8RM, 18RM, and 28RM; the features of the signals were extracted using time-domain and frequency-domain analysis. Statistical analysis was also performed. The top and bottom groups exhibited significant differences time-domain indicators mean absolute value (MAV) and average amplitude change (AAC) in the low-intensity exercise (28RM). The MAV, variance of EMG (VAR), root mean square (RMS), and AAC were significantly different between the top and bottom groups in the three graded intensities (8RM, 18RM, and 28RM). The mean frequency (MNF) and median frequency (MDF), which are frequency-domain indicators, were significantly different between the top and bottom groups in the low-intensity (28RM) and moderate-intensity (18RM) exercises.

Neuromuscular function in anterior cruciate ligament reconstructed patients at long-term follow-up

BackgroundThe permanence of neuromuscular adaptations following anterior cruciate ligament reconstruction is not known. The aim of this study was to compare bilateral muscle co-contraction indices, time to peak ground reaction force, and timing of muscle onset between anterior cruciate ligament reconstruction subjects 10–15 years post reconstruction with those of matched uninjured controls during a one-leg hop landing. MethodsNine healthy controls and 9 reconstruction subjects were recruited. Clinical and functional knee exams were administered. Lower limb co-contraction indices, time to peak ground reaction force, and muscle onset times were measured bilaterally. Differences in clinical and functional outcomes were assessed with unpaired t-tests, and mixed model repeated measures were used to examine effects of group, limb and interaction terms in electromyography measures. Findings89% of control knees were clinically “normal”, whereas only 33% of reconstructed knees were “normal”. Anterior cruciate ligament-reconstructed subjects tended to achieve shorter functional hop distances but demonstrated symmetrical lower limb electromyography measures that were no different from those of controls' with the exception that biceps femoris activation was delayed bilaterally prior to ground contact but was greater during the injury risk phase of landing. InterpretationWith the exception of hamstring activation, lower limb electromyography measures were largely similar between ligament-reconstructed and matched control subjects, which was in contrast to the clinical findings. This result brings into question the significance of neuromuscular function at this long-term follow-up but raises new questions regarding the role of symmetry and pre-injury risk.