Methodological aspects of SEMG recordings for force estimation--a tutorial and review

One-Channel Surface Electromyography Decomposition for Muscle Force Estimation

Estimating muscle force by surface electromyography (sEMG) is a non-invasive and flexible way to diagnose biomechanical diseases and control assistive devices such as prosthetic hands. To estimate muscle force using sEMG, a supervised method is commonly adopted. This requires simultaneous recording of sEMG signals and muscle force measured by additional devices to tune the variables involved. However, recording the muscle force of the lost limb of an amputee is challenging, and the supervised method has limitations in this regard. Although the unsupervised method does not require muscle force recording, it suffers from low accuracy due to a lack of reference data. To achieve accurate and easy estimation of muscle force by the unsupervised method, we propose a decomposition of one-channel sEMG signals into constituent motor unit action potentials (MUAPs) in two steps: (1) learning an orthogonal basis of sEMG signals through reconstruction independent component analysis; (2) extracting spike-like MUAPs from the basis vectors. Nine healthy subjects were recruited to evaluate the accuracy of the proposed approach in estimating muscle force of the biceps brachii. The results demonstrated that the proposed approach based on decomposed MUAPs explains more than 80% of the muscle force variability recorded at an arbitrary force level, while the conventional amplitude-based approach explains only 62.3% of this variability. With the proposed approach, we were also able to achieve grip force control of a prosthetic hand, which is one of the most important clinical applications of the unsupervised method. Experiments on two trans-radial amputees indicated that the proposed approach improves the performance of the prosthetic hand in grasping everyday objects.

Estimation of Handgrip Force from SEMG Based on Wavelet Scale Selection

This paper proposes a nonlinear correlation-based wavelet scale selection technology to select the effective wavelet scales for the estimation of handgrip force from surface electromyograms (SEMG). The SEMG signal corresponding to gripping force was collected from extensor and flexor forearm muscles during the force-varying analysis task. We performed a computational sensitivity analysis on the initial nonlinear SEMG-handgrip force model. To explore the nonlinear correlation between ten wavelet scales and handgrip force, a large-scale iteration based on the Monte Carlo simulation was conducted. To choose a suitable combination of scales, we proposed a rule to combine wavelet scales based on the sensitivity of each scale and selected the appropriate combination of wavelet scales based on sequence combination analysis (SCA). The results of SCA indicated that the scale combination VI is suitable for estimating force from the extensors and the combination V is suitable for the flexors. The proposed method was compared to two former methods through prolonged static and force-varying contraction tasks. The experiment results showed that the root mean square errors derived by the proposed method for both static and force-varying contraction tasks were less than 20%. The accuracy and robustness of the handgrip force derived by the proposed method is better than that obtained by the former methods.

Interpreting Signal Amplitudes in Surface Electromyography Studies in Sport and Rehabilitation Sciences

Surface electromyography (sEMG) is a popular research tool in sport and rehabilitation sciences. Common study designs include the comparison of sEMG amplitudes collected from different muscles as participants perform various exercises and techniques under different loads. Based on such comparisons, researchers attempt to draw conclusions concerning the neuro- and electrophysiological underpinning of force production and hypothesize about possible longitudinal adaptations, such as strength and hypertrophy. However, such conclusions are frequently unsubstantiated and unwarranted. Hence, the goal of this review is to discuss what can and cannot be inferred from comparative research designs as it pertains to both the acute and longitudinal outcomes. General methodological recommendations are made, gaps in the literature are identified, and lines for future research to help improve the applicability of sEMG are suggested.

Weight bearing exercise can elicit similar peak muscle activation as medium-high intensity resistance exercise in elderly women

PURPOSE

To assess whether stepping-based weight bearing exercise (WBE) can elicit peak activation of upper leg muscles similar to resistance exercise (RE) at an intensity required to induce strength gains in elderly women.

METHODS

Muscular activation of several upper leg muscles was measured during RE and WBE in a cohort of 19 healthy elderly women (69.3 ± 3.4 years). WBE consisted of forward and lateral stepping with step heights of 10, 20 and 30 cm. Muscular activation was compared to 60% of one-repetition maximum (1-RM) of congruent RE.

RESULTS

Peak activation during WBE was higher than RE at 60% 1-RM during forward and lateral stepping in vastus lateralis starting at 20 cm (p = 0.049 and p = 0.001), and biceps femoris at 30 cm step height (p = 0.024 and p = 0.030). Gluteus maximus peak activation matched RE at 60% 1-RM at 20 and 30 cm step height regardless of step direction (p ≥ 0.077). Peak activation of the rectus femoris and gluteus medius matched RE activation at 60% 1-RM during lateral stepping at 30 cm (p = 0.355 and p = 0.243, respectively) but not during forward stepping. WBE did not induce similar activation as RE in the semitendinosus.

CONCLUSION

In WBE, most upper leg muscles were recruited at an equal or higher intensity than in RE at 60% 1-RM. Lateral stepping at 30 cm step height showed the highest training potential of all WBE's applied.

A model-based approach for estimation of changes in lumbar segmental kinematics associated with alterations in trunk muscle forces

The kinematics information from imaging, if combined with optimization-based biomechanical models, may provide a unique platform for personalized assessment of trunk muscle forces (TMFs). Such a method, however, is feasible only if differences in lumbar spine kinematics due to differences in TMFs can be captured by the current imaging techniques. A finite element model of the spine within an optimization procedure was used to estimate segmental kinematics of lumbar spine associated with five different sets of TMFs. Each set of TMFs was associated with a hypothetical trunk neuromuscular strategy that optimized one aspect of lower back biomechanics. For each set of TMFs, the segmental kinematics of lumbar spine was estimated for a single static trunk flexed posture involving, respectively, 40° and 10° of thoracic and pelvic rotations. Minimum changes in the angular and translational deformations of a motion segment with alterations in TMFs ranged from 0° to 0.7° and 0 mm to 0.04 mm, respectively. Maximum changes in the angular and translational deformations of a motion segment with alterations in TMFs ranged from 2.4° to 7.6° and 0.11 mm to 0.39 mm, respectively. The differences in kinematics of lumbar segments between each combination of two sets of TMFs in 97% of cases for angular deformation and 55% of cases for translational deformation were within the reported accuracy of current imaging techniques. Therefore, it might be possible to use image-based kinematics of lumbar segments along with computational modeling for personalized assessment of TMFs.

Investigation of the HD-sEMG probability density function shapes with varying muscle force using data fusion and shape descriptors

This work presents an evaluation of the High Density surface Electromyogram (HD-sEMG) Probability Density Function (PDF) shape variation according to contraction level. On that account, using PDF shape descriptors: High Order Statistics (HOS) and Shape Distances (SD), we try to address the absence of a consensus for the sEMG non-Gaussianity evolution with force variation. This is motivated by the fact that PDF shape information are relevant in physiological assessment of the muscle architecture and function, such as contraction level classification, in complement to classical amplitude parameters. Accordingly, both experimental and simulation studies are presented in this work. For data fusion, the watershed image processing technique was used. This technique allowed us to find the dominant PDF shape variation profiles from the 64 signals. The experimental protocol consisted of three isometric isotonic contractions of 30, 50 and 70% of the Maximum Voluntary Contraction (MVC). This protocol was performed by six subjects and recorded using an 8 × 8 HD-sEMG grid. For the simulation study, the muscle modeling was done using a fast computing cylindrical HD-sEMG generation model. This model was personalized by morphological parameters obtained by sonography. Moreover, a set of the model parameter configurations were compared as a focused sensitivity analysis of the PDF shape variation. Further, monopolar, bipolar and Laplacian electrode configurations were investigated in both experimental and simulation studies. Results indicated that sEMG PDF shape variations according to force increase are mainly dependent on the Motor Unit (MU) spatial recruitment strategy, the MU type distribution within the muscle, and the used electrode arrangement. Consequently, these statistics can give us an insight into non measurable parameters and specifications of the studied muscle primarily the MU type distribution.

Coordination of deep hip muscle activity is altered in symptomatic femoroacetabular impingement

Diagnosis of femoroacetabular impingement (FAI) is increasing, yet the associated physical impairments remain poorly defined. This morphological hip condition can cause joint pain, stiffness, impaired function, and eventually hip osteoarthritis. This exploratory study compared coordination of deep hip muscles between people with and without symptomatic FAI using analysis of muscle synergies (i.e., patterns of activity of groups of muscles activated in synchrony) during gait. Fifteen individuals (11 males) with symptomatic FAI (clinical examination and imaging) and 14 age- and sex-comparable controls without morphological FAI underwent testing. Intramuscular fine-wire and surface electrodes recorded electromyographic activity of selected deep and superficial hip muscles. A non-negative matrix factorization algorithm extracted three synergies which were compared between groups. Information regarding which muscles were activated together in the FAI group (FAI group synergy vector) was used to reconstruct individual electromyography patterns and compare groups. Variance accounted for (VAF) by three synergies was less for the control (94.8 [1.4]%) than FAI (96.0 [1.0]%) group (p = 0.03). VAF of obturator internus was significantly higher in the FAI group (p = 0.02). VAF of the reconstructed individual electromyography patterns with the FAI or control group vector were significantly higher for the FAI group (p < 0.01). Following reconstruction, VAF of quadratus femoris was significantly more reduced in controls (p = 0.04), indicating greater between-subject variability. Coordination of deep hip muscles in the synergy related to hip joint control during early swing differed between groups. This phase involves movement towards the impingement position, which has relevance for the interpretation of synergy differences and potential clinical importance. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:1494-1504, 2017.

A Novel Approach to Measuring Muscle Mechanics in Vehicle Collision Conditions

The aim of the study was to evaluate a novel approach to measuring neck muscle load and activity in vehicle collision conditions. A series of sled tests were performed on 10 healthy volunteers at three severity levels to simulate low-severity frontal impacts. Electrical activity-electromyography (EMG)-and muscle mechanical tension was measured bilaterally on the upper trapezius. A novel mechanical contraction (MC) sensor was used to measure the tension on the muscle surface. The neck extensor loads were estimated based on the inverse dynamics approach. The results showed strong linear correlation (Pearson's coefficient = 0.821) between the estimated neck muscle load and the muscle tension measured with the MC sensor. The peak of the estimated neck muscle force delayed 0.2 ± 30.6 ms on average vs. the peak MC sensor signal compared to the average delay of 61.8 ± 37.4 ms vs. the peak EMG signal. The observed differences in EMG and MC sensor collected signals indicate that the MC sensor offers an additional insight into the analysis of the neck muscle load and activity in impact conditions. This approach enables a more detailed assessment of the muscle-tendon complex load of a vehicle occupant in pre-impact and impact conditions.

Simultaneous and Continuous Estimation of Shoulder and Elbow Kinematics from Surface EMG Signals

In this paper, we present a simultaneous and continuous kinematics estimation method for multiple DoFs across shoulder and elbow joint. Although simultaneous and continuous kinematics estimation from surface electromyography (EMG) is a feasible way to achieve natural and intuitive human-machine interaction, few works investigated multi-DoF estimation across the significant joints of upper limb, shoulder and elbow joints. This paper evaluates the feasibility to estimate 4-DoF kinematics at shoulder and elbow during coordinated arm movements. Considering the potential applications of this method in exoskeleton, prosthetics and other arm rehabilitation techniques, the estimation performance is presented with different muscle activity decomposition and learning strategies. Principle component analysis (PCA) and independent component analysis (ICA) are respectively employed for EMG mode decomposition with artificial neural network (ANN) for learning the electromechanical association. Four joint angles across shoulder and elbow are simultaneously and continuously estimated from EMG in four coordinated arm movements. By using ICA (PCA) and single ANN, the average estimation accuracy 91.12% (90.23%) is obtained in 70-s intra-cross validation and 87.00% (86.30%) is obtained in 2-min inter-cross validation. This result suggests it is feasible and effective to use ICA (PCA) with single ANN for multi-joint kinematics estimation in variant application conditions.

Modifying motor unit territory placement in the Fuglevand model

The Fuglevand model is often used to address challenging questions in neurophysiology; however, there are elements of the neuromuscular system unaccounted for in the model. For instance, in some muscles, slow and fast motor units (MUs) tend to reside deep and superficially in the muscle, respectively, necessarily altering the development of surface electromyogram (EMG) power during activation. Thus, the objective of this study was to replace the randomized MU territory (MUT) placement algorithm in the Fuglevand model with an optimized method capable of reflecting these observations. To accomplish this, a weighting term was added to a previously developed optimization algorithm to encourage regionalized MUT placement. The weighting term consequently produced significantly different muscle fibre type content in the deep and superficial portions of the muscle. The relation between simulated EMG and muscle force was found to be significantly affected by regionalization. These changes were specifically a function of EMG power, as force was unaffected by regionalization. These findings suggest that parameterizing MUT regionalization will allow the model to produce a larger variety of EMG-force relations, as is observed physiologically, and could potentially simulate the loss of specific MU types as observed in ageing and clinical populations.

Dynamic Elbow Flexion Force Estimation Through a Muscle Twitch Model and sEMG in a Fatigue Condition

We propose a joint force estimation method to compute elbow flexion force using surface electromyogram (sEMG) considering time-varying effects in a fatigue condition. Muscle fatigue is a major cause inducing sEMG changes with respect to time over long periods and repetitive contractions. The proposed method composed the muscle-twitch model representing the force generated by a single spike and the spikes extracted from sEMG. In this study, isometric contractions at six different joint angles (10 subjects) and dynamic contractions with constant velocity (six subjects) were performed under non-fatigue and fatigue conditions. Performance of the proposed method was evaluated and compared with that of previous methods using mean absolute value (MAV). The proposed method achieved average 6.7 ± 2.8 %RMSE for isometric contraction and 15.6 ± 24.7%RMSE for isokinetic contraction under fatigue condition with more accurate results than the previous methods.

Comparison of Constant-Posture Force-Varying EMG-Force Dynamic Models About the Elbow

Numerous techniques have been used to minimize error in relating the surface electromyogram (EMG) to elbow joint torque. We compare the use of three techniques to further reduce error. First, most EMG-torque models only use estimates of EMG standard deviation as inputs. We studied the additional features of average waveform length, slope sign change rate and zero crossing rate. Second, multiple channels of EMG from the biceps, and separately from the triceps, have been combined to produce two low-variance model inputs. We contrasted this channel combination with using each EMG separately. Third, we previously modeled nonlinearity in the EMG-torque relationship via a polynomial. We contrasted our model versus that of the classic exponential power law of Vredenbregt and Rau (1973). Results from 65 subjects performing constant-posture, force-varying contraction gave a "baseline" comparison error (i.e., error with none of the new techniques) of 5.5 ± 2.3% maximum flexion voluntary contraction (%MVC_F). Combining the techniques of multiple features with individual channels reduced error to 4.8 ± 2.2 %MVC_F, while combining individual channels with the power-law model reduced error to 4.7 ± 2.0 %MVC_F. The new techniques further reduced error from that of the baseline by ≈ 15 %.

Towards Real-Time Estimation of Muscle-Fiber Conduction Velocity Using Delay-Locked Loop

Decrease in muscle-fiber conduction velocity (MFCV) during sustained contraction has been widely accepted as myoelectric manifestation of muscle fatigue. Several methods have been proposed in the literature for MFCV estimation by analysing surface electromyography (EMG), e.g., cross-correlation (CC) function and maximum likelihood (ML). However, for all the availablemethods, windowing of the EMG signal and computationally demanding calculations are required, limiting the possibility to continuously monitor muscle fatigue in real time. In the present study, an adaptive scheme is proposed that permits real-time estimation of MFCV. The proposed scheme is based on a delay-lockedloop (DLL). Asecond-orderloop is adopted to track the delay variationover time. An error filter is employed to approximate a ML estimation in case of colored noise. Furthermore, the DLL system is extended for multichannel CV estimation. The performance of the proposed method is evaluated by both dedicated simulations and real EMG signals. Our results show the accuracy of the proposed method to be comparable to that of theML method formuch lower (1/40) computational complexity, especially suited for real-time MFCV measurements. Use of this method can enable new studies onmyoelectric fatigue, possibly leading to new insight on the underlying physiological processes.

Knee Moment-Angle Characteristics and Semitendinosus Muscle Morphology in Children with Spastic Paresis Selected for Medial Hamstring Lengthening

To increase knee range of motion and improve gait in children with spastic paresis (SP), the semitendinosus muscle (ST) amongst other hamstring muscles is frequently lengthened by surgery, but with variable success. Little is known about how the pre-surgical mechanical and morphological characteristics of ST muscle differ between children with SP and typically developing children (TD). The aims of this study were to assess (1) how knee moment-angle characteristics and ST morphology in children with SP selected for medial hamstring lengthening differ from TD children, as well as (2) how knee moment-angle characteristics and ST morphology are related. In nine SP and nine TD children, passive knee moment-angle characteristics and morphology of ST (i.e. fascicle length, muscle belly length, tendon length, physiological cross-sectional area, and volume) were assessed by hand-held dynamometry and freehand 3D ultrasound, respectively. At net knee flexion moments above 0.5 Nm, more flexed knee angles were found for SP compared to TD children. The measured knee angle range between 0 and 4 Nm was 30% smaller in children with SP. Muscle volume, physiological cross-sectional area, and fascicle length normalized to femur length were smaller in SP compared to TD children (62%, 48%, and 18%, respectively). Sixty percent of the variation in knee angles at 4 Nm net knee moment was explained by ST fascicle length. Altered knee moment-angle characteristics indicate an increased ST stiffness in SP children. Morphological observations indicate that in SP children planned for medial hamstring lengthening, the longitudinal and cross-sectional growth of ST muscle fibers is reduced. The reduced fascicle length can partly explain the increased ST stiffness and, hence, a more flexed knee joint in these SP children.

Filtered Virtual Reference: A New Method for the Reduction of Power Line Interference With Minimal Distortion of Monopolar Surface EMG

GOAL

This study tests and validates a new method to remove power line interference from monopolar EMGs detected by multichannel systems: the filtered virtual reference (FVR). FVR is an adaptation of the virtual reference (VR) method, which consists in referencing signals detected by each electrode in a grid to their spatial average. Signals may however be distorted with the VR approach, in particular when the skin region where the detection system is positioned does not cover the entire muscle.

METHODS

Simulated and experimental EMGs were used to compare the performance of FVR and VR in terms of interference reduction and distortion of monopolar signals referred to a remote reference.

RESULTS

Simulated data revealed the monopolar EMG signals processed with FVR were significantly less distorted than those filtered by VR. These results were similarly observed for experimental signals. Moreover, FVR method outperformed VR in removing power line interference when it was distributed unevenly across the signals of the grid.

CONCLUSION

Key results demonstrated that FVR improves the VR method as it reduces interference while preserving the information content of monopolar signals.

SIGNIFICANCE

Although the actual distribution of motor unit action potential is represented in monopolar EMGs, collecting high quality monopolar signals is challenging. This study presents a possible solution to this issue; FVR provides undistorted monopolar signals with negligible interference and is insensitive to muscle architecture. It is therefore relevant for EMG applications benefiting from a clean monopolar detection (e.g., decomposition, control of prosthetic devices, motor unit number estimation).

Extracorporeal Shock Wave Stimulation as Alternative Treatment Modality for Wrist and Fingers Spasticity in Poststroke Patients: A Prospective, Open-Label, Preliminary Clinical Trial

Objective. To evaluate the effectiveness of radial shock waves (rESW) for wrist and fingers flexors spasticity in stroke patients. Methods. Twenty patients with upper limb muscle spasticity were enrolled in the study and treated with a single session of rESW. The spasticity level of the radio carpal (RC) and finger (FF) joints was assessed using Modified Ashworth Scale (MAS). The resting bioelectrical activity of the flexor carpi radialis (FCR) and flexor carpi ulnaris (FCU) was examined using surface electromyography (sEMG). Trophic conditions were measured using infrared thermal (IRT) imaging. All measurements were conducted at baseline (t₀), immediately after rESW (t₁), and 1 (t₂) and 24 (t₃) hours following rESW. Results. Significant reduction in MAS was observed for the RC joint in t₁, as well as for the FF joints in t₁, t₂, and t₃. A significant decrease in sEMG was shown for the FCR muscle in t₁ and t₂, as well as for the FCU muscle in t₁ and t₃. Also, a significant increase in IRT value was observed in t₃ only. Conclusions. A single session of rESW could be an effective alternative treatment for reduction of limb spasticity and could lead to improvement of trophic conditions of the spastic muscles.

Muscle Activity during Walking Measured Using 3D MRI Segmentations and [18F]-Fluorodeoxyglucose in Combination with Positron Emission Tomography

PURPOSE

This study aimed to determine the contribution of each muscle of the lower limb to walking using positron emission tomography (PET) with [F]-fluorodeoxyglucose (FDG). Furthermore, we compared our results obtained using volumetric analysis of entire muscles with those obtained using a more traditional approach considering the uptake in only one slice in each segment.

METHODS

Ten healthy subjects walked on a treadmill at self-selected comfortable walking speed for 90 min, 60 min before and 30 min after intravenous injection of 50-MBq FDG. A PET/computerized tomography scan of the lower limb was made subsequently. The three-dimensional contours of 39 muscles in the left lower limb were semiautomatically determined from magnetic resonance imaging scans. After nonrigidly registering the magnetic resonance imaging to the computerized tomography scans, we superimposed the muscle contours on the PET scans.

RESULTS

The muscles with the highest median FDG uptake among all subjects were the soleus, gluteus maximus, vastus lateralis, gastrocnemius medialis, and adductor magnus. We found a wide range of FDG uptake values among subjects, including in some of the most important muscles involved in walking (e.g., soleus, gluteus medius, gastrocnemius medialis). Compared with the volumetric analysis, the single slice analysis did not yield an accurate estimate of the FDG uptake in many of the most active muscles, including the gluteus medius and minimus (overestimated) as well as all the thigh muscles (underestimated).

CONCLUSIONS

The distribution of FDG among the muscles varied between subjects, suggesting that each subject had a unique activation pattern. The FDG uptake as estimated from single slices did not correspond well to the uptake obtained from volumetric analysis, which illustrates the added value of our novel three-dimensional image analysis techniques.

Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury

Background

Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.

Method

HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification.

Results

Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard). Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).

Conclusion

In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.

Force Modelling of Upper Limb Biomechanics Using Ensemble Fast Orthogonal Search on High-Density Electromyography

An important quality of upper limb force estimation is the repeatability and worst-case performance of the estimator. The following paper proposes a methodology using an ensemble learning technique coupled with the fast orthogonal search (FOS) algorithm to reliably predict varying isometric contractions of the right arm. This method leverages the rapid and precise modelling offered by FOS combined with a univariate outlier detection algorithm to dynamically combine the output of numerous FOS models. This is performed using high-density surface electromyography (HD-SEMG) obtained from three upper-arm muscles, the biceps brachii, triceps brachii and brachioradialis. This method offers improved performance over other HD-SEMG and SEMG based force estimators, with a substantial reduction in the number of channels required.

A Study on Estimation of Joint Force Through Isometric Index Finger Abduction With the Help of SEMG Peaks for Biomedical Applications

We propose a new method to estimate joint force using a biomechanical muscle model and peaks of surface electromyography (SEMG). The SEMG measurement was carried out from the first dorsal interosseous muscle during isometric index finger abduction. The SEMG peaks were used as the input of the biomechanical muscle model which is a transfer function to generate the force. The force estimation performance ( R(2) ) was evaluated using the proposed method with nine healthy subjects, and a former method using a mean absolute value (MAV), which is the full-wave rectified and averaged (or low-pass filtered) signal of SEMG in a time window, was compared with the proposed method; the performance of the proposed method (0.94 ± 0.03) was better than that of MAV (0.90 ± 0.02). The proposed method could be widely applied to quantitative analysis of muscle activities based on SEMG.

Musculoskeletal Simulation for Assessment of Effect of Movement-Based Structure-Modifying Treatment Strategies

The better understanding of the complex mechanism between neural motor control and its resulting joint kinematics and muscle forces allows a better elucidation of the mechanisms behind body growth, aging progression, and disease development. This study aimed at investigating the impact of movement-based structure-modifying treatment strategies on joint kinematics, muscle forces, and muscle synergies of the gait with instrumented implant. A patient-specific musculoskeletal model was used to quantitatively assess the deviations of joint and muscle behaviors between the normal gait and 4 gait modifications (bouncy, medial thrust, midcrouch, and mtp (i.e., gait with forefoot strike)). Moreover, muscle synergy analysis was performed using EMG-based nonnegative matrix factorization. Large variation of 19 degrees and 190 N was found for knee flexion/extension and lower limb muscle forces, respectively. EMG-based muscle synergy analysis revealed that the activation levels of the vastus lateralis and tibialis anterior are dominant for the midcrouch gait. In addition, an important contribution of semimembranosus to the medial thrust and midcrouch gaits was also observed. In fact, such useful information could allow a better understanding of the joint function and muscle synergy strategies leading to deeper knowledge of joint and muscle mechanisms related to neural voluntary motor commands.

Tibialis anterior analysis from functional and architectural perspective during isometric foot dorsiflexion: a cross-sectional study of repeated measures

Background

The purpose of the present study is to establish the relationship and degree of contribution between torque and sonomiography variables (pennation angle – muscle thickness), and electromyography variables (EMG_{AreaUnderCurve} – EMG_MaximalPeak) of the tibialis anterior muscle during (TA) maximal and relative isometric foot dorsiflexion (IFD). Secondary aim: To determine the measurement’s reliability.

Methods

Cross-sectional study. 31 participants (15 men; 16 women) performed IFD at different intensities (100, 75, 50, and 25 %) of the maximal voluntary contraction (MVC) (three times for each intensity). Outcome variables: To determine the torque, pennation angle, muscle thickness, EMG_MaximalPeak, and EMG_{AreaUnderCurve}. Statistical analysis: In order to test the measurement’s reliability, Cronbach’s alpha and standard error of the measurement were determined. An inferential analysis was carried out using Pearson correlations(r). For each contraction intensity, a multiple regression analysis was performed, where the dependent variable was torque and the independent variables were EMG_{AreaUnderCurve}, EMG_MaximalPeak, muscle thickness and pennation angle.

Results

All outcome variables show excellent reliability. The highest correlation value was 0.955 (thickness 100 % – thickness 25 %). R² values ranged from 0.713 (100 % MVC) to 0.588 (25 % MVC).

Conclusion

The outcome variables demonstrated excellent reliability in terms of measuring IFD at different intensities. The correlations between all outcome variables were moderate-to-strong. TA functional and architectural variables have a significant impact on the torque variance during IFD at different intensities.

A Hertzian Integrated Contact Model of the Total Knee Replacement Implant for the Estimation of Joint Contact Forces

The prediction of lower limb muscle and contact forces may provide useful knowledge to assist the clinicians in the diagnosis as well as in the development of appropriate treatment for musculoskeletal disorders. Research studies have commonly estimated joint contact forces using model-based muscle force estimation due to the lack of a reliable contact model and material properties. The objective of this present study was to develop a Hertzian integrated contact model. Then, in vivo elastic properties of the Total Knee Replacement (TKR) implant were identified using in vivo contact forces leading to providing reliable material properties for modeling purposes. First, a patient specific rigid musculoskeletal model was built. Second, a STL-based implant model was designed to compute the contact area evolutions during gait motions. Finally, a Hertzian integrated contact model was defined for the in vivo identification of elastic properties (Young’s modulus and Poisson coefficient) of the instrumented TKR implant. Our study showed a potential use of a new approach to predict the contact forces without knowledge of muscle forces. Thus, the outcomes may lead to accurate and reliable prediction of human joint contact forces for new case study.

The auditory space in the motor system

Sensory events in the space around us trigger specific motor patterns directed toward or away from the spatial location of the sensory source. Spatially-defined sensorimotor associations are well-known in the visual domain but less so for the auditory modality. In particular no spatially-directed audio-motor association has been described for the upper limb. We tested the instantaneous directional tuning of the corticospinal system by means of single-pulse transcranial magnetic stimulation (TMS) over the left motor cortex in 16 healthy volunteers while at rest. We recorded the lateral accelerations of the TMS-evoked movement by means of an accelerometer placed on the forearm. Acoustic stimuli (pure tone frequency=1000Hz, duration=50ms) coming from 25 different directions lying in the axial anterior half-plane at the height of the participant's ears were played on earphones. The entire set of sound directions covered a span of 160° (±80° where 0° is the frontal direction) at a fixed azimuth angle. Six different intervals between sound onset and TMS (0, 25, 50, 100, 150 and 200ms) were tested for each sound direction. Significant correlations were found between sound origin and TMS-evoked arm accelerations only when TMS was delivered 50ms prior to sound onset. We show the presence in the upper limb motor system of auditory spatial tuning. Sound information accesses the motor system at very short latency, potentially compatible with both a subcortical and a cortical origin of the response. The use of TMS-evoked accelerations allowed us to disclose a strict directional tuning in audio-motor associations.

Spatial variability in cortex-muscle coherence investigated with magnetoencephalography and high-density surface electromyography

Cortex-muscle coherence (CMC) reflects coupling between magnetoencephalography (MEG) and surface electromyography (sEMG), being strongest during isometric contraction but absent, for unknown reasons, in some individuals. We used a novel nonmagnetic high-density sEMG (HD-sEMG) electrode grid (36 mm × 12 mm; 60 electrodes separated by 3 mm) to study effects of sEMG recording site, electrode derivation, and rectification on the strength of CMC. Monopolar sEMG from right thenar and 306-channel whole-scalp MEG were recorded from 14 subjects during 4-min isometric thumb abduction. CMC was computed for 60 monopolar, 55 bipolar, and 32 Laplacian HD-sEMG derivations, and two derivations were computed to mimic "macroscopic" monopolar and bipolar sEMG (electrode diameter 9 mm; interelectrode distance 21 mm). With unrectified sEMG, 12 subjects showed statistically significant CMC in 91-95% of the HD-sEMG channels, with maximum coherence at ∼25 Hz. CMC was about a fifth stronger for monopolar than bipolar and Laplacian derivations. Monopolar derivations resulted in most uniform CMC distributions across the thenar and in tightest cortical source clusters in the left rolandic hand area. CMC was 19-27% stronger for HD-sEMG than for "macroscopic" monopolar or bipolar derivations. EMG rectification reduced the CMC peak by a quarter, resulted in a more uniformly distributed CMC across the thenar, and provided more tightly clustered cortical sources than unrectifed sEMGs. Moreover, it revealed CMC at ∼12 Hz. We conclude that HD-sEMG, especially with monopolar derivation, can facilitate detection of CMC and that individual muscle anatomy cannot explain the high interindividual CMC variability.

Assessment of net knee moment-angle characteristics by instrumented hand-held dynamometry in children with spastic cerebral palsy and typically developing children

Background

The limited range of motion during walking in children with spastic cerebral palsy (SCP) may be the result of altered mechanical characteristics of muscles and connective tissues around the knee joint. Measurement of static net knee moment-angle relation will provide insights into these alterations, for which instrumented hand-held dynamometry may be applied.

The aims of this study were: (1) to test the measurement error of the estimated net knee moment-angle characteristics, (2) to determine the correlation between knee extension angle measurement at a standardized knee moment and popliteal angle from common physical examination and (3) to compare net knee moment–angle characteristics in SCP versus typically developing children.

Methods

With the child lying in sideward position, the knee was extended by moving the lower leg by a hand-held force transducer on a low friction cart. Force data were collected for a range of knee angles. Data were excluded when activity (EMG) levels of knee extensor and flexor muscles exceeded the EMG level during rest by more than two standard deviations. The net knee flexion moments were calculated from recorded force data and measured moment arm. Reliability for knee angles corresponding with 0.5, 1, 2, 3, and 4 Nm knee net flexion moments was assessed by standard error of measurements (SEM) and smallest detectable difference (SDD).

Results

For between day comparison, SEMs were about 5° and SDDs were below 14° for knee angles at 1-4 Nm net knee flexion moments. In SCP children, the knee angle measured at 4 Nm knee flexion moment was not related to the popliteal angle (r = 0.52). The slope at 4 Nm of the knee moment-angle curve in SCP children was significantly higher than that in typically developing children.

Conclusions

The presented knee hand-held dynamometry allows assessment of net knee flexion moment-knee angle characteristics in typically developing and SCP children and can be used to identify clinically relevant changes as a result of treatment. Overall stiffness of structures that contribute to the net knee flexion moment at the knee (i.e. muscles, tendons, ligaments) is elevated in SCP children.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-015-0056-y) contains supplementary material, which is available to authorized users.

An attempt to bridge muscle architecture dynamics and its instantaneous rate of force development using ultrasonography

Muscle force output is an essential index in rehabilitation assessment or physical exams, and could provide considerable insights for various applications such as load monitoring and muscle assessment in sports science or rehabilitation therapy. Besides direct measurement of force output using a dynamometer, electromyography has earlier been used in several studies to quantify muscle force as an indirect means. However, its spatial resolution is easily compromised as a summation of the action potentials from neighboring motor units of electrode site. To explore an alternative method to indirectly estimate the muscle force output, and with better muscle specificity, we started with an investigation on the relationship between architecture dynamics and force output of triceps surae. The muscular architecture dynamics is captured in ultrasonography sequences and estimated using a previously reported motion estimation method. Then an indicator named as the dorsoventrally averaged motion profile (DAMP) is employed. The performance of force output is represented by an instantaneous version of the rate of force development (RFD), namely I-RFD. From experimental results on ten normal subjects, there were significant correlations between the I-RFD and DAMP for triceps surae, both normalized between 0 and 1, with the sum of squares error at 0.0516±0.0224, R-square at 0.7929±0.0931 and root mean squared error at 0.0159±0.0033. The statistical significance results were less than 0.01. The present study suggested that muscle architecture dynamics extracted from ultrasonography during contraction is well correlated to the I-RFD and it can be a promising option for indirect estimation of muscle force output.

A New Method for Functional Evaluation of Motor Commands in Patients with Cerebellar Ataxia

Quantitative evaluation of motor functions of patients with cerebellar ataxia is vital for evidence-based treatments and has been a focus in previous investigations of movement kinematics. Due to redundancy of the musculoskeletal system, muscle activities contain more information than the movement kinematics. Therefore, it is preferable to analyze causal anomalies of muscle activities to evaluate motor functions in patients. Here we propose a new method to evaluate the motor functions at the level of muscle activities and movement kinematics. Nineteen patients and 10 control subjects performed two movement tasks of the wrist joint, a step-tracking task and a pursuit task, with a manipulandum. The movements of the wrist joint and activities of the four wrist prime movers were recorded. We developed a linear model for the wrist joint to approximate the causal relationship between muscle activities and movement kinematics in terms of the wrist joint torque. We used a canonical correlation analysis to verify the causality between the muscle activities and the movement kinematics in the model. We found that the activities of the four muscles were related almost entirely to the position and velocity, with negligible correlation with the acceleration of the wrist joint. Moreover, the ratio of the weights for position- and velocity-related torque components characterized the contents of the muscle activities in terms of the movement kinematics. Next, we compared the ratios for the two movement tasks between the controls and patients. In control subjects, the ratios indicated clear task-specific changes that conformed to the functional requirements of the tasks. In contrast, in patients, the task-specific changes diminished highly significantly. The present results indicate that this ability to accommodate motor commands to the task requirements provides a novel quantitative parameter to characterize motor functions in patients with cerebellar ataxia.

Human joint motion estimation for electromyography (EMG)-based dynamic motion control

This study aims to investigate a joint motion estimation method from Electromyography (EMG) signals during dynamic movement. In most EMG-based humanoid or prosthetics control systems, EMG features were directly or indirectly used to trigger intended motions. However, both physiological and nonphysiological factors can influence EMG characteristics during dynamic movements, resulting in subject-specific, non-stationary and crosstalk problems. Particularly, when motion velocity and/or joint torque are not constrained, joint motion estimation from EMG signals are more challenging. In this paper, we propose a joint motion estimation method based on muscle activation recorded from a pair of agonist and antagonist muscles of the joint. A linear state-space model with multi input single output is proposed to map the muscle activity to joint motion. An adaptive estimation method is proposed to train the model. The estimation performance is evaluated in performing a single elbow flexion-extension movement in two subjects. All the results in two subjects at two load levels indicate the feasibility and suitability of the proposed method in joint motion estimation. The estimation root-mean-square error is within 8.3% ∼ 10.6%, which is lower than that being reported in several previous studies. Moreover, this method is able to overcome subject-specific problem and compensate non-stationary EMG properties.

Single-Channel EMG Classification With Ensemble-Empirical-Mode-Decomposition-Based ICA for Diagnosing Neuromuscular Disorders

An accurate and computationally efficient quantitative analysis of electromyography (EMG) signals plays an inevitable role in the diagnosis of neuromuscular disorders, prosthesis, and several related applications. Since it is often the case that the measured signals are the mixtures of electric potentials that emanate from surrounding muscles (sources), many EMG signal processing approaches rely on linear source separation techniques such as the independent component analysis (ICA). Nevertheless, naive implementations of ICA algorithms do not comply with the task of extracting the underlying sources from a single-channel EMG measurement. In this respect, the present work focuses on a classification method for neuromuscular disorders that deals with the data recorded using a single-channel EMG sensor. The ensemble empirical mode decomposition algorithm decomposes the single-channel EMG signal into a set of noise-canceled intrinsic mode functions, which in turn are separated by the FastICA algorithm. A reduced set of five time domain features extracted from the separated components are classified using the linear discriminant analysis, and the classification results are fine-tuned with a majority voting scheme. The performance of the proposed method has been validated with a clinical EMG database, which reports a higher classification accuracy (98%). The outcome of this study encourages possible extension of this approach to real settings to assist the clinicians in making correct diagnosis of neuromuscular disorders.

Task variation during simulated, repetitive, low-intensity work--influence on manifestation of shoulder muscle fatigue, perceived discomfort and upper-body postures

Work-related musculoskeletal disorders are increasing due to industrialisation of work processes. Task variation has been suggested as potential intervention. The objectives of this study were to investigate, first, the influence of task variation on electromyographic (EMG) manifestations of shoulder muscle fatigue and discomfort; second, noticeable postural shoulder changes over time; third, if the association between task variation and EMG might be biased by postural changes. Outcome parameters were recorded using multichannel EMG, Optotrak and the Borg scale. Fourteen participants performed a one-hour repetitive Pegboard task in one continuous and two interrupted conditions with rest and a pick-and-place task, respectively. Manifestations of shoulder muscle fatigue and discomfort feelings were observed throughout the conditions but these were not significantly influenced by task variation. After correction for joint angles, the relation between task variation and EMG was significantly biased but significant effects of task variation remained absent.

PRACTITIONER SUMMARY

Comparing a one-hour continuous, repetitive Pegboard task with two interrupted conditions revealed no significant influences of task variation. We did observe that the relation between task variation and EMG was biased by posture and therefore advise taking account for posture when investigating manifestations of muscle fatigue in assembly tasks.

Influence of Joint Angle on EMG-Torque Model During Constant-Posture, Torque-Varying Contractions

Relating the electromyogram (EMG) to joint torque is useful in various application areas, including prosthesis control, ergonomics and clinical biomechanics. Limited study has related EMG to torque across varied joint angles, particularly when subjects performed force-varying contractions or when optimized modeling methods were utilized. We related the biceps-triceps surface EMG of 22 subjects to elbow torque at six joint angles (spanning 60° to 135°) during constant-posture, torque-varying contractions. Three nonlinear EMG σ -torque models, advanced EMG amplitude (EMG σ ) estimation processors (i.e., whitened, multiple-channel) and the duration of data used to train models were investigated. When EMG-torque models were formed separately for each of the six distinct joint angles, a minimum "gold standard" error of 4.01±1.2% MVC(F90) resulted (i.e., error relative to maximum voluntary contraction at 90° flexion). This model structure, however, did not directly facilitate interpolation across angles. The best model which did so achieved a statistically equivalent error of 4.06±1.2% MVC(F90). Results demonstrated that advanced EMG σ processors lead to improved joint torque estimation as do longer model training durations.

Altered movement patterns and muscular activity during single and double leg squats in individuals with anterior cruciate ligament injury

BACKGROUND

Individuals with Anterior Cruciate Ligament (ACL) injury often show altered movement patterns, suggested to be partly due to impaired sensorimotor control. Here, we therefore aimed to assess muscular activity during movements often used in ACL-rehabilitation and to characterize associations between deviations in muscular activity and specific altered movement patterns, using and further exploring the previously developed Test for substitution Patterns (TSP).

METHODS

Sixteen participants (10 women) with unilateral ACL rupture performed Single and Double Leg Squats (SLS; DLS). Altered movement patterns were scored according to TSP, and Surface Electromyography (SEMG) was recorded bilaterally in six hip, thigh and shank muscles. To quantify deviations in muscular activity, SEMG ratios were calculated between homonymous muscles on injured and non-injured sides, and between antagonistic muscles on the same side. Correlations between deviations of injured/non-injured side SEMG ratios and specific altered movement patterns were calculated.

RESULTS

Injured/non-injured ratios were low at transition from knee flexion to extension in quadriceps in SLS, and in quadriceps and hamstrings in DLS. On injured side, the quadriceps/hamstrings ratio prior to the beginning of DLS and end of DLS and SLS, and tibialis/gastrocnemius ratio at end of DLS were lower than on non-injured side. Correlations were found between specific altered movement patterns and deviating muscular activity at transition from knee flexion to extension in SLS, indicating that the more deviating the muscular activity on injured side, the more pronounced the altered movement pattern. "Knee medial to supporting foot" correlated to lower injured/non-injured ratios in gluteus medius (rs = -0.73, p = 0.001), "lateral displacement of hip-pelvis-region" to lower injured/non-injured ratios in quadriceps (rs = -0.54, p = 0.03) and "displacement of trunk" to higher injured/non-injured ratios in gluteus medius (rs = 0.62, p = 0.01).

CONCLUSIONS

Deviations in muscular activity between injured and non-injured sides and between antagonistic muscular activity within injured as compared to non-injured sides indicated specific alterations in sensorimotor control of the lower limb in individuals with ACL rupture. Also, correlations between deviating muscular activity and specific altered movement patterns were suggested as indications of altered sensorimotor control. We therefore advocate that quantitative assessments of altered movement patterns should be considered in ACL-rehabilitation.