An EMG-based, muscle driven forward simulation of single support phase of gait

Evaluating Muscle Synergies With EMG Data and Physics Simulation in the Neurorobotics Platform

Although we can measure muscle activity and analyze their activation patterns, we understand little about how individual muscles affect the joint torque generated. It is known that they are controlled by circuits in the spinal cord, a system much less well-understood than the cortex. Knowing the contribution of the muscles toward a joint torque would improve our understanding of human limb control. We present a novel framework to examine the control of biomechanics using physics simulations informed by electromyography (EMG) data. These signals drive a virtual musculoskeletal model in the Neurorobotics Platform (NRP), which we then use to evaluate resulting joint torques. We use our framework to analyze raw EMG data collected during an isometric knee extension study to identify synergies that drive a musculoskeletal lower limb model. The resulting knee torques are used as a reference for genetic algorithms (GA) to generate new simulated activation patterns. On the platform the GA finds solutions that generate torques matching those observed. Possible solutions include synergies that are similar to those extracted from the human study. In addition, the GA finds activation patterns that are different from the biological ones while still producing the same knee torque. The NRP forms a highly modular integrated simulation platform allowing these in silico experiments. We argue that our framework allows for research of the neurobiomechanical control of muscles during tasks, which would otherwise not be possible.

A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful

The ultimate goal of most neuromusculoskeletal modeling research is to improve the treatment of movement impairments. However, even though neuromusculoskeletal models have become more realistic anatomically, physiologically, and neurologically over the past 25 years, they have yet to make a positive impact on the design of clinical treatments for movement impairments. Such impairments are caused by common conditions such as stroke, osteoarthritis, Parkinson’s disease, spinal cord injury, cerebral palsy, limb amputation, and even cancer. The lack of clinical impact is somewhat surprising given that comparable computational technology has transformed the design of airplanes, automobiles, and other commercial products over the same time period. This paper provides the author’s personal perspective for how neuromusculoskeletal models can become clinically useful. First, the paper motivates the potential value of neuromusculoskeletal models for clinical treatment design. Next, it highlights five challenges to achieving clinical utility and provides suggestions for how to overcome them. After that, it describes clinical, technical, collaboration, and practical needs that must be addressed for neuromusculoskeletal models to fulfill their clinical potential, along with recommendations for meeting them. Finally, it discusses how more complex modeling and experimental methods could enhance neuromusculoskeletal model fidelity, personalization, and utilization. The author hopes that these ideas will provide a conceptual blueprint that will help the neuromusculoskeletal modeling research community work toward clinical utility.

Can Measured Synergy Excitations Accurately Construct Unmeasured Muscle Excitations?

Accurate prediction of muscle and joint contact forces during human movement could improve treatment planning for disorders such as osteoarthritis, stroke, Parkinson's disease, and cerebral palsy. Recent studies suggest that muscle synergies, a low-dimensional representation of a large set of muscle electromyographic (EMG) signals (henceforth called "muscle excitations"), may reduce the redundancy of muscle excitation solutions predicted by optimization methods. This study explores the feasibility of using muscle synergy information extracted from eight muscle EMG signals (henceforth called "included" muscle excitations) to accurately construct muscle excitations from up to 16 additional EMG signals (henceforth called "excluded" muscle excitations). Using treadmill walking data collected at multiple speeds from two subjects (one healthy, one poststroke), we performed muscle synergy analysis on all possible subsets of eight included muscle excitations and evaluated how well the calculated time-varying synergy excitations could construct the remaining excluded muscle excitations (henceforth called "synergy extrapolation"). We found that some, but not all, eight-muscle subsets yielded synergy excitations that achieved >90% extrapolation variance accounted for (VAF). Using the top 10% of subsets, we developed muscle selection heuristics to identify included muscle combinations whose synergy excitations achieved high extrapolation accuracy. For 3, 4, and 5 synergies, these heuristics yielded extrapolation VAF values approximately 5% lower than corresponding reconstruction VAF values for each associated eight-muscle subset. These results suggest that synergy excitations obtained from experimentally measured muscle excitations can accurately construct unmeasured muscle excitations, which could help limit muscle excitations predicted by muscle force optimizations.

Foot and Ankle Function at Maturity After Ilizarov Treatment for Atrophic-Type Congenital Pseudarthrosis of the Tibia: A Comprehensive Outcome Comparison with Normal Controls

BACKGROUND

The purpose of this study was to evaluate clinical outcomes and the biomechanical function of the foot and ankle at skeletal maturity of patients treated for atrophic-type congenital pseudarthrosis of the tibia (CPT) compared with healthy young adult controls.

METHODS

Twenty-four patients (mean age of 19.1 years) who had undergone Ilizarov treatment for unilateral atrophic-type CPT were compared with twenty-four controls (mean age of 19.6 years). All participants were evaluated using validated outcome questionnaires, radiographs, physical examination, instrumented motion analysis including a multisegmental foot model, and pedobarographic measurement.

RESULTS

Within the CPT group, the mean score of the American Orthopaedic Foot & Ankle Society (AOFAS) ankle-hindfoot scale was 89.9 (range, 76 to 100), and the mean score of the Oxford Ankle Foot Questionnaire (OAFQ) was 42.8 (range, 15 to 60). Motion analysis and pedobarographic measurement showed differences in biomechanical function of the foot and ankle on the side affected by CPT: a slower walking speed due to the short stride length; decreased dorsiflexion in hallux motion; increased hindfoot pronation in the presence of forefoot supination; diminished ankle push-off power; delayed time to heel-rise; and decreased forefoot pressure relative to hindfoot pressure. However, sagittal motion of the hindfoot and forefoot on the affected side was relatively well preserved. Subgroup analysis demonstrated no significant differences in terms of clinical outcome scores and most biomechanical parameters between the tibiofibular synostosis group and the intact-fibula group.

CONCLUSIONS

Children with atrophic-type CPT can obtain satisfactory foot and ankle function at maturity after successful Ilizarov treatment. Early stabilization of the ankle mortise by fibular stabilization and preservation of ankle mobility during and after treatment is thought to be crucial to maintaining function of the ankle in patients with CPT.

LEVEL OF EVIDENCE

Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

FEASIBILITY STUDY FOR ANFIS AND EMG UTILIZATION IN MODELING PROSTHESIS FOR TRANS-FEMORAL CUT REHABILITATION AND GAIT CYCLE RESTORATION

Rehabilitation of lower limbs with high-level amputation (Trans-femoral Cut) requires an alternative method of inverse and forward dynamics to be employed. Inverse and forward dynamics are capable of solving the problem of redundancy of muscles in human lower limbs. Furthermore, inverse and forward dynamics can be used for estimating joints moments, predicting body segment kinematics, and estimating the distribution of forces between the agonist/antagonist muscle group with reasonable accuracy [Riener R, Lünenburger L, Colombo G, Human-Centered robotics applied to gait training and assessment robert, J Rehabil Res Dev43:679, 2006; Keller T, Perry JC, Rehabilitation robotics for outpatient clinical and domestic use, WC IFMBE Proc25:291, 2009; Crespo LM, Reinkensmeyer DJ, Review of control strategies for robotic movement training after neurologic injury, J Neuroeng Rehabil6:20, 2009; Hillman MI, Rehabilitation robotics from past to present — A historical prespective, Adv Rehabil Robotics, Lect Notes Contr Inf306:25, 2004.]. However, the application of these methods, in rehabilitation, is still limited due to their dependence on multiple input data that cannot be measured using conventional measurement tools. This study is aimed at verifying and validating new models which are capable of predicting body segment kinematics accurately using features obtained from electromyography (EMG) and adaptive neuro fuzzy inference system (ANFIS). These features are used to model a set of (input\output) dynamic data. EMG signals obtained from full gait cycle trials of a subject are used to calculate joint moments. Kinematics of the body segments are obtained by applying Euler numerical integration. The relative percentage root mean square (RMS) error between predicted kinematics from ANFIS and measured values for hip, knee, and ankle were 2.23%, 0.98%, and 0.69%, respectively. However, the achieved minimal reasonable accuracy for minimum number of measured inputs depends on the characteristics of the gait parameters such as cyclic nature and delayed symmetric activities between right and left leg about mid sagittal plane. Results of the combined model show that higher prediction accuracy of the gait cycle is achieved and so rehabilitation of lower limbs is feasible.

Muscle synergies may improve optimization prediction of knee contact forces during walking

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values.

Analysis of joint force and torque for the human and non-human ape foot during bipedal walking with implications for the evolution of the foot

The feet of apes have a different morphology from those of humans. Until now, it has merely been assumed that the morphology seen in humans must be adaptive for habitual bipedal walking, as the habitual use of bipedal walking is generally regarded as one of the most clear-cut differences between humans and apes. This study asks simply whether human skeletal proportions do actually enhance foot performance during human-like bipedalism, by examining the influence of foot proportions on force, torque and work in the foot joints during simulated bipedal walking. Skeletons of the common chimpanzee, orangutan, gorilla and human were represented by multi-rigid-body models, where the components of the foot make external contact via finite element surfaces. The models were driven by identical joint motion functions collected from experiments on human walking. Simulated contact forces between the ground and the foot were found to be reasonably comparable with measurements made during human walking using pressure- and force-platforms. Joint force, torque and work in the foot were then predicted. Within the limitations of our model, the results show that during simulated human-like bipedal walking, (1) the human and non-human ape (NHA) feet carry similar joint forces, although the distributions of the forces differ; (2) the NHA foot incurs larger joint torques than does the human foot, although the human foot has higher values in the first tarso-metatarsal and metatarso-phalangeal joints, whereas the NHA foot incurs higher values in the lateral digits; and (3) total work in the metatarso-phalangeal joints is lower in the human foot than in the NHA foot. The results indicate that human foot proportions are indeed well suited to performance in normal human walking.

Compensatory strategies during walking in response to excessive muscle co-contraction at the ankle joint

Excessive co-contraction causes inefficient or abnormal movement in several neuromuscular pathologies. How synergistic muscles spanning the ankle, knee and hip adapt to co-contraction of ankle muscles is not well understood. This study aimed to identify the compensation strategies required to retain normal walking with excessive antagonistic ankle muscle co-contraction. Muscle-actuated simulations of normal walking were performed to quantify compensatory mechanisms of ankle and knee muscles during stance in the presence of normal, medium and high levels of co-contraction of antagonistic pairs gastrocnemius+tibialis anterior and soleus+tibialis anterior. The study showed that if co-contraction increases, the synergistic ankle muscles can compensate; with gastrocmemius+tibialis anterior co-contraction, the soleus will increase its contribution to ankle plantarflexion acceleration. At the knee, however, almost all muscles spanning the knee and hip are involved in compensation. We also found that ankle and knee muscles alone can provide sufficient compensation at the ankle joint, but hip muscles must be involved to generate sufficient knee moment. Our findings imply that subjects with a rather high level of dorsiflexor+plantarflexor co-contraction can still perform normal walking. This also suggests that capacity of other lower limb muscles to compensate is important to retain normal walking in co-contracted persons. The compensatory mechanisms can be useful in clinical interpretation of motion analyses, when secondary muscle co-contraction or other deficits may present simultaneously in subjects with motion disorders.

Computational modelling of the natural hip: a review of finite element and multibody simulations

PRIMARY OBJECTIVE

The hip joint suffers from a high prevalence of degenerative conditions. Athough patient's well-being could be improved through early and more effective interventions, without a greater understanding of the mechanics of the hip, these developments cannot be attained. Thus, this review article summarises the current literature on this subject in order to provide a platform for future developments. To illustrate the influence computational simulations have had on the knowledge advancement in hip mechanics, we explored two methodological approaches: finite element (FE) analysis and multibody dynamics (MBD).

MAIN OUTCOMES AND RESULTS

Notwithstanding the unique capabilities of FE and MBD, the former generally offers the micromechanics of the articulating surfaces whereas the latter the macromechanics of the skeleton, these two methodologies also provide the bulk of the literature regarding computational modelling of the musculoskeletal system. Although FE has provided significant knowledge on contact pressures and the effects of musculoskeletal geometries, in particular cartilage and bone shapes, MBD has afforded a wealth of understanding on the influence of gait patterns and muscle attachment locations on force magnitudes.

CONCLUSIONS

These two computational techniques have, and will continue to, provide significant contributions towards the development of interventions. It is hoped that this article will help focus ongoing technological developments by highlighting areas of success, but also areas of under development.

The effect of knee model on estimates of muscle and joint forces in recumbent pedaling

The usefulness of forward dynamic simulations to studies of human motion is well known. Although the musculoskeletal models used in these studies are generic, the modeling of specific components, such as the knee joint, may vary. Our two objectives were (1) to investigate the effects of three commonly used knee models on forward dynamic simulation results, and (2) to study the sensitivity of simulation results to variations in kinematics for the most commonly used knee model. To satisfy the first objective, three different tibiofemoral models were incorporated into an existing forward dynamic simulation of recumbent pedaling, and the resulting kinematics, pedal forces, muscle forces, and joint reaction forces were compared. Two of these models replicated the rolling and sliding motion of the tibia on the femur, while the third was a simple pin joint. To satisfy the second objective, variations in the most widely used of the three knee models were created by adjusting the experimental data used in the development of this model. These variations were incorporated into the pedaling simulation, and the resulting data were compared with the unaltered model. Differences between the two rolling-sliding models were smaller than differences between the pin-joint model and the rolling-sliding models. Joint reactions forces, particularly at the knee, were highly sensitive to changes in knee joint model kinematics, as high as 61% root mean squared difference, normalized by the corresponding peak force of the unaltered reference model. Muscle forces were also sensitive, as high as 30% root mean squared difference. Muscle excitations were less sensitive. The observed changes in muscle force and joint reaction forces were caused primarily by changes in the moment arms and musculotendon lengths of the quadriceps. Although some level of inaccuracy in the knee model may be acceptable for calculations of muscle excitation timing, a representative model of knee kinematics is necessary for accurate calculation of muscle and joint reaction forces.

Predicting the effects of knee focal articular surface injury with a patient-specific finite element model

Successful focal articular surface injury (FAI) repair depends on appropriate matching of the geometrical/material properties of the repaired site, and on the overall dynamic response of the knee to in-vivo loading. There is evidence linking the pathogenesis of lesion progression (e.g. osteoarthritis) to weightbearing site and defect size. The paper investigates further this link by studying the effects of osteochondral defect size on the load distribution at the human knee. Experimental data from cadaver knees (n=8) loaded at 30 degrees of flexion was used as input to a validated finite element (FE) model. Contact pressure was assessed for the intact knees and over a range of circular osteochondral defects (5 mm to 20 mm) at 30 degrees of flexion with 700 N axial load. Patient specific FE models and the specific boundary conditions of the experimental set-up were used to analyze the osteochondral defects. Stress concentration around the rims of defects 8 mm and smaller was not significant and pressure distribution was dominated by the menisci. Experimental data was confirmed by the model. For defects 10 mm and greater, distribution of peak pressures followed the rim of the defect with a mean distance from the rim of 2.64 mm on the medial condyle and 2.90 mm on the lateral condyle (model predictions were 2.63 and 2.87 mm respectively). Statistical significance was reported when comparing defects that differed by 4 mm or greater (except for the 5 mm case). Peak rim pressure did not significantly increase as defects were enlarged from 10 mm to 20 mm. Peak values were always significantly higher over the medial femoral condyle. Although the decision to treat osteochondral lesions is multifactorial, the results of this finite element analysis indicate that a size threshold of 10 mm, may be a useful early adjunct to guide clinical decision-making. This modified FE method can be employed for in-vivo studies.

Multichannel SEMG in clinical gait analysis: a review and state-of-the-art

BACKGROUND

Application of surface electromyography (SEMG) to the clinical evaluation of neuromuscular disorders can provide relevant "diagnostic" contributions in terms of nosological classification, localization of focal impairments, detection of pathophysiological mechanisms, and functional assessment.

METHODS

The present review article elaborates on: (i) the technical aspects of the myoelectric signals acquisition within a protocol of clinical gait analysis (multichannel recording, surface vs. deep probes, electrode placing, encumbrance effects), (ii) the sequence of procedures for the subsequent data processing (filtering, averaging, normalization, repeatability control), and (iii) a set of feasible strategies for the final extraction of clinically useful information.

FINDINGS

Relevant examples of SEMG application to functional diagnosis are provided.

INTERPRETATION

Emphasis is given to the key role of SEMG along with kinematic and kinetic analysis, for non-invasive assessment of relevant pathophysiological mechanisms potentially hindering the gait function, such as changes in passive muscle-tendon properties (peripheral non-neural component), paresis, spasticity, and loss of selectivity of motor output in functionally antagonist muscles.

A neuromusculoskeletal tracking method for estimating individual muscle forces in human movement

A neuromusculoskeletal tracking (NMT) method was developed to estimate muscle forces from observed motion data. The NMT method combines skeletal motion tracking and optimal neuromuscular tracking to produce forward simulations of human movement quickly and accurately. The skeletal motion tracker calculates the joint torques needed to actuate a skeletal model and track observed segment angles and ground forces in a forward simulation of the motor task. The optimal neuromuscular tracker resolves the muscle redundancy problem dynamically and finds the muscle excitations (and muscle forces) needed to produce the joint torques calculated by the skeletal motion tracker. To evaluate the accuracy of the NMT method, kinematics and ground forces obtained from an optimal control (parameter optimization) solution for maximum-height jumping were contaminated with both random and systematic noise. These data served as input observations to the NMT method as well as an inverse dynamics analysis. The NMT solution was compared to the input observations, the original optimal solution, and a simulation driven by the inverse dynamics torques. The results show that, in contrast to inverse dynamics, the NMT method is able to produce an accurate forward simulation consistent with the optimal control solution. The NMT method also requires 3 orders-of-magnitude less CPU time than parameter optimization. The speed and accuracy of the NMT method make it a promising new tool for estimating muscle forces using experimentally obtained kinematics and ground force data.

A new method to investigate in vivo knee behavior using a finite element model of the lower limb

Several finite element models have been developed for estimating the mechanical response of joint internal structures, where direct or indirect in vivo measurement is difficult or impossible. The quality of the predictions made by those models is largely dependent on the quality of the experimental data (e.g. load/displacement) used to drive them. Also numerical problems have been described in the literature when using implicit finite element techniques to simulate problems that involve contacts and large displacements. In this study, a unique strategy was developed combining high accuracy in vivo three-dimensional kinematics and a lower limb finite element model based on explicit finite element techniques. The method presents an analytical technique applied to a dynamic loading condition (impact during hopping on one leg). The validation of the lower limb model focused on the response of the whole model and the knee joint in particular to the imposed 3D femoral in vivo kinematics and ground reaction forces. The approach outlined in this study introduces a generic tool for the study of in vivo knee joint behavior.

The complementary role of the plantarflexors, hamstrings and gluteus maximus in the control of stance limb stability during gait

This paper focuses on the contributions of the gluteus maximus, biceps femoris, gastrocnemius and soleus in maintaining the stability of the stance limb in the sagittal plane during the mid-stance phase of gait. In the absence of any one of these muscles, the potential compensatory changes in muscle activation are explored, the aim being to restore stability to the stance limb. The investigation was carried out by integrating musculoskeletal modelling, forward simulation and optimization techniques. We concluded that maintenance of stance limb stability requires a subtle interplay of muscle activations. Weakness in a single muscle is unlikely to be adequately compensated for by increasing or decreasing the activation of one muscle alone.

The study of muscle action during single support and swing phase of gait: clinical relevance of forward simulation techniques

Individual muscle function during single stance and swing phase of gait were analyzed using muscle driven forward simulation. The activation of each of 22 muscles in a musculoskeletal model with seven degrees of freedom were excluded from the forward simulation and the resulting changes in joint angles studied. A classification of muscle function during single support and swing phase of gait is presented. Altered joint kinematics due to the absence of individual muscle action is discussed in the light of pathological gait kinematics and clinical decision-making.