CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks

Development of a deep neural network for automated electromyographic pattern classification

Determining the signal quality of surface electromyography (sEMG) recordings is time consuming and requires the judgement of trained observers. An automated procedure to evaluate sEMG quality would streamline data processing and reduce time demands. This paper compares the performance of two supervised and three unsupervised artificial neural networks (ANNs) in the evaluation of sEMG quality. Manually classified sEMG recordings from various lower-limb muscles during motor tasks were used to train (n=28,000), test performance (n=12,000) and evaluate accuracy (n=47,000) of the five ANNs in classifying signals into four categories. Unsupervised ANNs demonstrated a 30-40% increase in classification accuracy (>98%) compared with supervised ANNs. AlexNet demonstrated the highest accuracy (99.55%) with negligible false classifications. The results indicate that sEMG quality evaluation can be automated via an ANN without compromising human-like classification accuracy. This classifier will be publicly available and will be a valuable tool for researchers and clinicians using electromyography.

Immediate effects of valgus knee bracing on tibiofemoral contact forces and knee muscle forces

Background Valgus knee braces have been reported to reduce the external knee adduction moment during walking. However, mechanistic investigations into the effects of valgus bracing on medial compartment contact forces using electromyogram-driven neuromusculoskeletal models are limited. Research question What are the immediate effects of valgus bracing on medial tibiofemoral contact forces and muscular loading of the tibiofemoral joint? Methods Sixteen (9 male) healthy adults (27.7 ± 4.4 years) performed 20 over-ground walking trials at self-selected speed both with and without an Ossür Unloader One® brace. Assessment order (i.e., with or without brace) was randomised and counterbalanced to prevent order effects. While walking, three-dimensional lower-body motion, ground reaction forces, and surface electromyograms from eight lower-limb muscles were acquired. These data were used to calibrate an electromyogram-driven neuromusculoskeletal model of muscle and tibiofemoral contact forces (N), from which muscle and external load contributions (%) to those contact forces were determined. Results Although walking with the brace resulted in no significant changes in peak tibiofemoral contact forces at the group-level, individual responses were variable and non-uniform. At the group-level, wearing the brace resulted in a 2.35% (95% CI 0.46-4.24; p = 0.02) greater relative contribution of muscle to lateral compartment contact loading (54.2 ± 11.1%) compared to not wearing the brace (51.8 ± 12.1%) (p < 0.05). Average relative contributions of muscle and external loads to medial compartment loading were comparable between brace and no brace conditions (p ≥ 0.05). Significance Wearing a valgus knee brace did not immediately reduce peak tibiofemoral contact forces in healthy adults during normal walking. It appears this population may modulate muscle activation patterns to support brace-generated valgus moments, thereby maintaining normal walking knee moments and tibiofemoral contact forces. Future investigations are warranted to better understand effects of valgus knee brace in people with medial knee osteoarthritis using an electromyogram-driven neuromusculoskeletal model.

Tibiofemoral joint contact forces increase with load magnitude and walking speed but remain almost unchanged with different types of carried load

Musculoskeletal injuries (MSI) in the military reduce soldier capability and impose substantial costs. Characterizing biomechanical surrogates of MSI during commonly performed military tasks (e.g., load carriage) is necessary for evaluating the effectiveness of possible interventions to reduce MSI risk. This study determined the effects of body-borne load distribution, load magnitude, and walking speed on tibiofemoral contact forces. Twenty-one Australian Army Reserve soldiers completed a treadmill walking protocol in an unloaded condition and wearing four armor types (standard-issue and three prototypes) with two load configurations (15 and 30 kg) for a total of 8 armor x load ensembles. In each ensemble, participants completed a 5-minute warm-up, and then walked for 10 minutes at both moderate (1.53 m⋅s^-1) and fast (1.81 m⋅s^-1) speeds. During treadmill walking, three-dimensional kinematics, ground reaction forces, and muscle activity from nine lower-limb muscles were collected in the final minute of each speed. These data were used as inputs into a neuromusculoskeletal model, which estimated medial, lateral and total tibiofemoral contact forces. Repeated measures analyses of variance revealed no differences for any variables between armor types, but peak medial compartment contact forces increased when progressing from moderate to fast walking and with increased load (p<0.001). Acute exposure to load carriage increased estimated tibiofemoral contact forces 10.1 and 19.9% with 15 and 30kg of carried load, respectively, compared to unloaded walking. These results suggest that soldiers carrying loads in excess of 15 kg for prolonged periods could be at greater risk of knee MSI than those with less exposure.

Non-knee-spanning muscles contribute to tibiofemoral shear as well as valgus and rotational joint reaction moments during unanticipated sidestep cutting

Anterior cruciate ligament (ACL) injuries are a burdensome condition due to potential surgical requirements and increased risk of long term debilitation. Previous studies indicate that muscle forces play an important role in the development of ligamentous loading, yet these studies have typically used cadaveric models considering only the knee-spanning quadriceps, hamstrings and gastrocnemius muscle groups. Using a musculoskeletal modelling approach, we investigated how lower-limb muscles produce and oppose key tibiofemoral reaction forces and moments during the weight acceptance phase of unanticipated sidestep cutting. Muscles capable of opposing (or controlling the magnitude of) the anterior shear force and the external valgus moment at the knee are thought to be have the greatest potential for protecting the anterior cruciate ligament from injury. We found the best muscles for generating posterior shear to be the soleus, biceps femoris long head and medial hamstrings, providing up to 173N, 111N and 77N of force directly opposing the anterior shear force. The valgus moment was primarily opposed by the gluteus medius, gluteus maximus and piriformis, with these muscles providing contributions of up to 32 Nm, 19 Nm and 21 Nm towards a knee varus moment, respectively. Our findings highlight key muscle targets for ACL preventative and rehabilitative interventions.

sEMG-assisted inverse modelling of 3D lip movement: a feasibility study towards person-specific modelling

We propose a surface-electromyographic (sEMG) assisted inverse-modelling (IM) approach for a biomechanical model of the face to obtain realistic person-specific muscle activations (MA) by tracking movements as well as innervation trajectories. We obtained sEMG data of facial muscles and 3D positions of lip markers in six volunteers and, using a generic finite element (FE) face model in ArtiSynth, performed inverse static optimisation with and without sEMG tracking on both simulation data and experimental data. IM with simulated data and experimental data without sEMG data showed good correlations of tracked positions (0.93 and 0.67) and poor correlations of MA (0.27 and 0.20). When utilising the sEMG-assisted IM approach, MA correlations increased drastically (0.83 and 0.59) without sacrificing performance in position correlations (0.92 and 0.70). RMS errors show similar trends with an error of 0.15 in MA and of 1.10 mm in position. Therefore, we conclude that we were able to demonstrate the feasibility of an sEMG-assisted inverse modelling algorithm for the perioral region. This approach may help to solve the ambiguity problem in inverse modelling and may be useful, for instance, in future applications for preoperatively predicting treatment-related function loss.

Muscle contributions to the acceleration of the whole body centre of mass during recovery from forward loss of balance by stepping in young and older adults

The purpose of this study was to determine the muscular contributions to the acceleration of the whole body centre of mass (COM) of older compared to younger adults that were able to recover from forward loss of balance with a single step. Forward loss of balance was achieved by releasing participants (14 older adults and 6 younger adults) from a static whole-body forward lean angle of approximately 18 degrees. 10 older adults and 6 younger adults were able to recover with a single step and included in subsequent analysis. A scalable anatomical model consisting of 36 degrees-of-freedom was used to compute kinematics and joint moments from motion capture and force plate data. Forces for 92 muscle actuators were computed using Static Optimisation and Induced Acceleration Analysis was used to compute individual muscle contributions to the three-dimensional acceleration of the whole body COM. There were no significant differences between older and younger adults in step length, step time, 3D COM accelerations or muscle contributions to 3D COM accelerations. The stance and stepping leg Gastrocnemius and Soleus muscles were primarily responsible for the vertical acceleration experienced by the COM. The Gastrocnemius and Soleus from the stance side leg together with bilateral Hamstrings accelerated the COM forwards throughout balance recovery while the Vasti and Soleus of the stepping side leg provided the majority of braking accelerations following foot contact. The Hip Abductor muscles provided the greatest contribution to medial-lateral accelerations of the COM. Deficits in the neuromuscular control of the Gastrocnemius, Soleus, Vasti and Hip Abductors in particular could adversely influence balance recovery and may be important targets in interventions to improve balance recovery performance.

Bioinspired Technologies to Connect Musculoskeletal Mechanobiology to the Person for Training and Rehabilitation

Musculoskeletal tissues respond to optimal mechanical signals (e.g., strains) through anabolic adaptations, while mechanical signals above and below optimal levels cause tissue catabolism. If an individual's physical behavior could be altered to generate optimal mechanical signaling to musculoskeletal tissues, then targeted strengthening and/or repair would be possible. We propose new bioinspired technologies to provide real-time biofeedback of relevant mechanical signals to guide training and rehabilitation. In this review we provide a description of how wearable devices may be used in conjunction with computational rigid-body and continuum models of musculoskeletal tissues to produce real-time estimates of localized tissue stresses and strains. It is proposed that these bioinspired technologies will facilitate a new approach to physical training that promotes tissue strengthening and/or repair through optimal tissue loading.

On the Value of Estimating Human Arm Stiffness during Virtual Teleoperation with Robotic Manipulators

Teleoperated robotic systems are widely spreading in multiple different fields, from hazardous environments exploration to surgery. In teleoperation, users directly manipulate a master device to achieve task execution at the slave robot side; this interaction is fundamental to guarantee both system stability and task execution performance. In this work, we propose a non-disruptive method to study the arm endpoint stiffness. We evaluate how users exploit the kinetic redundancy of the arm to achieve stability and precision during the execution of different tasks with different master devices. Four users were asked to perform two planar trajectories following virtual tasks using both a serial and a parallel link master device. Users' arm kinematics and muscular activation were acquired and combined with a user-specific musculoskeletal model to estimate the joint stiffness. Using the arm kinematic Jacobian, the arm end-point stiffness was derived. The proposed non-disruptive method is capable of estimating the arm endpoint stiffness during the execution of virtual teleoperated tasks. The obtained results are in accordance with the existing literature in human motor control and show, throughout the tested trajectory, a modulation of the arm endpoint stiffness that is affected by task characteristics and hand speed and acceleration.

Protocol for a multi-centre randomised controlled trial comparing arthroscopic hip surgery to physiotherapy-led care for femoroacetabular impingement (FAI): the Australian FASHIoN trial

BACKGROUND

Femoroacetabular impingement syndrome (FAI), a hip disorder affecting active young adults, is believed to be a leading cause of hip osteoarthritis (OA). Current management approaches for FAI include arthroscopic hip surgery and physiotherapy-led non-surgical care; however, there is a paucity of clinical trial evidence comparing these approaches. In particular, it is unknown whether these management approaches modify the future risk of developing hip OA. The primary objective of this randomised controlled trial is to determine if participants with FAI who undergo hip arthroscopy have greater improvements in hip cartilage health, as demonstrated by changes in delayed gadolinium-enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC) index between baseline and 12 months, compared to those who undergo physiotherapy-led non-surgical management.

METHODS

This is a pragmatic, multi-centre, two-arm superiority randomised controlled trial comparing hip arthroscopy to physiotherapy-led management for FAI. A total of 140 participants with FAI will be recruited from the clinics of participating orthopaedic surgeons, and randomly allocated to receive either surgery or physiotherapy-led non-surgical care. The surgical intervention involves arthroscopic FAI surgery from one of eight orthopaedic surgeons specialising in this field, located in three different Australian cities. The physiotherapy-led non-surgical management is an individualised physiotherapy program, named Personalised Hip Therapy (PHT), developed by a panel to represent the best non-operative care for FAI. It entails at least six individual physiotherapy sessions over 12 weeks, and up to ten sessions over six months, provided by experienced musculoskeletal physiotherapists trained to deliver the PHT program. The primary outcome measure is the change in dGEMRIC score of a ROI containing both acetabular and femoral head cartilages at the chondrolabral transitional zone of the mid-sagittal plane between baseline and 12 months. Secondary outcomes include patient-reported outcomes and several structural and biomechanical measures relevant to the pathogenesis of FAI and development of hip OA. Interventions will be compared by intention-to-treat analysis.

DISCUSSION

The findings will help determine whether hip arthroscopy or an individualised physiotherapy program is superior for the management of FAI, including for the prevention of hip OA.

TRIAL REGISTRATION

Australia New Zealand Clinical Trials Registry reference: ACTRN12615001177549 . Trial registered 2/11/2015 (retrospectively registered).

Simulation of facial expressions using person-specific sEMG signals controlling a biomechanical face model

PURPOSE

Functional inoperability in advanced oral cancer is difficult to assess preoperatively. To assess functions of lips and tongue, biomechanical models are required. Apart from adjusting generic models to individual anatomy, muscle activation patterns (MAPs) driving patient-specific functional movements are necessary to predict remaining functional outcome. We aim to evaluate how volunteer-specific MAPs derived from surface electromyographic (sEMG) signals control a biomechanical face model.

METHODS

Muscle activity of seven facial muscles in six volunteers was measured bilaterally with sEMG. A triple camera set-up recorded 3D lip movement. The generic face model in ArtiSynth was adapted to our needs. We controlled the model using the volunteer-specific MAPs. Three activation strategies were tested: activating all muscles [Formula: see text], selecting the three muscles showing highest muscle activity bilaterally [Formula: see text]-this was calculated by taking the mean of left and right muscles and then selecting the three with highest variance-and activating the muscles considered most relevant per instruction [Formula: see text], bilaterally. The model's lip movement was compared to the actual lip movement performed by the volunteers, using 3D correlation coefficients [Formula: see text].

RESULTS

The correlation coefficient between simulations and measurements with [Formula: see text] resulted in a median [Formula: see text] of 0.77. [Formula: see text] had a median [Formula: see text] of 0.78, whereas with [Formula: see text] the median [Formula: see text] decreased to 0.45.

CONCLUSION

We demonstrated that MAPs derived from noninvasive sEMG measurements can control movement of the lips in a generic finite element face model with a median [Formula: see text] of 0.78. Ultimately, this is important to show the patient-specific residual movement using the patient's own MAPs. When the required treatment tools and personalisation techniques for geometry and anatomy become available, this may enable surgeons to test the functional results of wedge excisions for lip cancer in a virtual environment and to weigh surgery versus organ-sparing radiotherapy or photodynamic therapy.

Closed-loop EMG-informed model-based analysis of human musculoskeletal mechanics on rough terrains

This work aims at estimating the musculoskeletal forces acting in the human lower extremity during locomotion on rough terrains. We employ computational models of the human neuro-musculoskeletal system that are informed by multi-modal movement data including foot-ground reaction forces, 3D marker trajectories and lower extremity electromyograms (EMG). Data were recorded from one healthy subject locomoting on rough grounds realized using foam rubber blocks of different heights. Blocks arrangement was randomized across all locomotion trials to prevent adaptation to specific ground morphology. Data were used to generate subject-specific models that matched an individual's anthropometry and force-generating capacity. EMGs enabled capturing subject- and ground-specific muscle activation patterns employed for walking on the rough grounds. This allowed integrating realistic activation patterns in the forward dynamic simulations of the musculoskeletal system. The ability to accurately predict the joint mechanical forces necessary to walk on different terrains have implications for our understanding of human movement but also for developing intuitive human machine interfaces for wearable exoskeletons or prosthetic limbs that can seamlessly adapt to different mechanical demands matching biological limb performance.

Megane Pro: Myo-electricity, visual and gaze tracking data acquisitions to improve hand prosthetics

During the past 60 years scientific research proposed many techniques to control robotic hand prostheses with surface electromyography (sEMG). Few of them have been implemented in commercial systems also due to limited robustness that may be improved with multimodal data. This paper presents the first acquisition setup, acquisition protocol and dataset including sEMG, eye tracking and computer vision to study robotic hand control. A data analysis on healthy controls gives a first idea of the capabilities and constraints of the acquisition procedure that will be applied to amputees in a next step. Different data sources are not fused together in the analysis. Nevertheless, the results support the use of the proposed multimodal data acquisition approach for prosthesis control. The sEMG movement classification results confirm that it is possible to classify several grasps with sEMG alone. sEMG can detect the grasp type and also small differences in the grasped object (accuracy: 95%). The simultaneous recording of eye tracking and scene camera data shows that these sensors allow performing object detection for grasp selection and that several neurocognitive parameters need to be taken into account for this. In conclusion, this work on intact subjects presents an innovative acquisition setup and protocol. The first results in terms of data analysis are promising and set the basis for future work on amputees, aiming to improve the robustness of prostheses with multimodal data.

Robust Real-Time Musculoskeletal Modeling Driven by Electromyograms

OBJECTIVE

Current clinical biomechanics involves lengthy data acquisition and time-consuming offline analyses with biomechanical models not operating in real-time for man-machine interfacing. We developed a method that enables online analysis of neuromusculoskeletal function in vivo in the intact human.

METHODS

We used electromyography (EMG)-driven musculoskeletal modeling to simulate all transformations from muscle excitation onset (EMGs) to mechanical moment production around multiple lower-limb degrees of freedom (DOFs). We developed a calibration algorithm that enables adjusting musculoskeletal model parameters specifically to an individual's anthropometry and force-generating capacity. We incorporated the modeling paradigm into a computationally efficient, generic framework that can be interfaced in real-time with any movement data collection system.

RESULTS

The framework demonstrated the ability of computing forces in 13 lower-limb muscle-tendon units and resulting moments about three joint DOFs simultaneously in real-time. Remarkably, it was capable of extrapolating beyond calibration conditions, i.e., predicting accurate joint moments during six unseen tasks and one unseen DOF.

CONCLUSION

The proposed framework can dramatically reduce evaluation latency in current clinical biomechanics and open up new avenues for establishing prompt and personalized treatments, as well as for establishing natural interfaces between patients and rehabilitation systems.

SIGNIFICANCE

The integration of EMG with numerical modeling will enable simulating realistic neuromuscular strategies in conditions including muscular/orthopedic deficit, which could not be robustly simulated via pure modeling formulations. This will enable translation to clinical settings and development of healthcare technologies including real-time bio-feedback of internal mechanical forces and direct patient-machine interfacing.

Muscle contributions to medial tibiofemoral compartment contact loading following ACL reconstruction using semitendinosus and gracilis tendon grafts

Background

The muscle-tendon properties of the semitendinosus (ST) and gracilis (GR) are substantially altered following tendon harvest for the purpose of anterior cruciate ligament reconstruction (ACLR). This study adopted a musculoskeletal modelling approach to determine how the changes to the ST and GR muscle-tendon properties alter their contribution to medial compartment contact loading within the tibiofemoral joint in post ACLR patients, and the extent to which other muscles compensate under the same external loading conditions during walking, running and sidestep cutting.

Materials and methods

Motion capture and electromyography (EMG) data from 16 lower extremity muscles were acquired during walking, running and cutting in 25 participants that had undergone an ACLR using a quadruple (ST+GR) hamstring auto-graft. An EMG-driven musculoskeletal model was used to estimate the medial compartment contact loads during the stance phase of each gait task. An adjusted model was then created by altering muscle-tendon properties for the ST and GR to reflect their reported changes following ACLR. Parameters for the other muscles in the model were calibrated to match the experimental joint moments.

Results

The medial compartment contact loads for the standard and adjusted models were similar. The combined contributions of ST and GR to medial compartment contact load in the adjusted model were reduced by 26%, 17% and 17% during walking, running and cutting, respectively. These deficits were balanced by increases in the contribution made by the semimembranosus muscle of 33% and 22% during running and cutting, respectively.

Conclusion

Alterations to the ST and GR muscle-tendon properties in ACLR patients resulted in reduced contribution to medial compartment contact loads during gait tasks, for which the semimembranosus muscle can compensate.

Biofeedback for Gait Retraining Based on Real-Time Estimation of Tibiofemoral Joint Contact Forces

Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this paper, we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed five healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only three subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this paper focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body.

Model-Based Estimation of Ankle Joint Stiffness

We address the estimation of biomechanical parameters with wearable measurement technologies. In particular, we focus on the estimation of sagittal plane ankle joint stiffness in dorsiflexion/plantar flexion. For this estimation, a novel nonlinear biomechanical model of the lower leg was formulated that is driven by electromyographic signals. The model incorporates a two-dimensional kinematic description in the sagittal plane for the calculation of muscle lever arms and torques. To reduce estimation errors due to model uncertainties, a filtering algorithm is necessary that employs segmental orientation sensor measurements. Because of the model's inherent nonlinearities and nonsmooth dynamics, a square-root cubature Kalman filter was developed. The performance of the novel estimation approach was evaluated in silico and in an experimental procedure. The experimental study was conducted with body-worn sensors and a test-bench that was specifically designed to obtain reference angle and torque measurements for a single joint. Results show that the filter is able to reconstruct joint angle positions, velocities and torque, as well as, joint stiffness during experimental test bench movements.

An entropy-assisted musculoskeletal shoulder model

Optimization combined with a musculoskeletal shoulder model has been used to estimate mechanical loading of musculoskeletal elements around the shoulder. Traditionally, the objective function is to minimize the summation of the total activities of the muscles with forces, moments, and stability constraints. Such an objective function, however, tends to neglect the antagonist muscle co-contraction. In this study, an objective function including an entropy term is proposed to address muscle co-contractions. A musculoskeletal shoulder model is developed to apply the proposed objective function. To find the optimal weight for the entropy term, an experiment was conducted. In the experiment, participants generated various 3-D shoulder moments in six shoulder postures. The surface EMG of 8 shoulder muscles was measured and compared with the predicted muscle activities based on the proposed objective function using Bhattacharyya distance and concordance ratio under different weight of the entropy term. The results show that a small weight of the entropy term can improve the predictability of the model in terms of muscle activities. Such a result suggests that the concept of entropy could be helpful for further understanding the mechanism of muscle co-contractions as well as developing a shoulder biomechanical model with greater validity.

Cervical Spine Injuries: A Whole-Body Musculoskeletal Model for the Analysis of Spinal Loading

Cervical spine trauma from sport or traffic collisions can have devastating consequences for individuals and a high societal cost. The precise mechanisms of such injuries are still unknown as investigation is hampered by the difficulty in experimentally replicating the conditions under which these injuries occur. We harness the benefits of computer simulation to report on the creation and validation of i) a generic musculoskeletal model (MASI) for the analyses of cervical spine loading in healthy subjects, and ii) a population-specific version of the model (Rugby Model), for investigating cervical spine injury mechanisms during rugby activities. The musculoskeletal models were created in OpenSim, and validated against in vivo data of a healthy subject and a rugby player performing neck and upper limb movements. The novel aspects of the Rugby Model comprise i) population-specific inertial properties and muscle parameters representing rugby forward players, and ii) a custom scapula-clavicular joint that allows the application of multiple external loads. We confirm the utility of the developed generic and population-specific models via verification steps and validation of kinematics, joint moments and neuromuscular activations during rugby scrummaging and neck functional movements, which achieve results comparable with in vivo and in vitro data. The Rugby Model was validated and used for the first time to provide insight into anatomical loading and cervical spine injury mechanisms related to rugby, whilst the MASI introduces a new computational tool to allow investigation of spinal injuries arising from other sporting activities, transport, and ergonomic applications. The models used in this study are freely available at simtk.org and allow to integrate in silico analyses with experimental approaches in injury prevention.

A Pilot Study of Individual Muscle Force Prediction during Elbow Flexion and Extension in the Neurorehabilitation Field

This paper proposes a neuromusculoskeletal (NMS) model to predict individual muscle force during elbow flexion and extension. Four male subjects were asked to do voluntary elbow flexion and extension. An inertial sensor and surface electromyography (sEMG) sensors were attached to subject's forearm. Joint angle calculated by fusion of acceleration and angular rate using an extended Kalman filter (EKF) and muscle activations obtained from the sEMG signals were taken as the inputs of the proposed NMS model to determine individual muscle force. The result shows that our NMS model can predict individual muscle force accurately, with the ability to reflect subject-specific joint dynamics and neural control solutions. Our method incorporates sEMG and motion data, making it possible to get a deeper understanding of neurological, physiological, and anatomical characteristics of human dynamic movement. We demonstrate the potential of the proposed NMS model for evaluating the function of upper limb movements in the field of neurorehabilitation.

Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim

Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time.

Prophylactic knee bracing alters lower-limb muscle forces during a double-leg drop landing

Anterior cruciate ligament (ACL) injury can be a painful, debilitating and costly consequence of participating in sporting activities. Prophylactic knee bracing aims to reduce the number and severity of ACL injury, which commonly occurs during landing maneuvers and is more prevalent in female athletes, but a consensus on the effectiveness of prophylactic knee braces has not been established. The lower-limb muscles are believed to play an important role in stabilizing the knee joint. The purpose of this study was to investigate the changes in lower-limb muscle function with prophylactic knee bracing in male and female athletes during landing. Fifteen recreational athletes performed double-leg drop landing tasks from 0.30m and 0.60m with and without a prophylactic knee brace. Motion analysis data were used to create subject-specific musculoskeletal models in OpenSim. Static optimization was performed to calculate the lower-limb muscle forces. A linear mixed model determined that the hamstrings and vasti muscles produced significantly greater flexion and extension torques, respectively, and greater peak muscle forces with bracing. No differences in the timings of peak muscle forces were observed. These findings suggest that prophylactic knee bracing may help to provide stability to the knee joint by increasing the active stiffness of the hamstrings and vasti muscles later in the landing phase rather than by altering the timing of muscle forces. Further studies are necessary to quantify whether prophylactic knee bracing can reduce the load placed on the ACL during intense dynamic movements.

Neural Data-Driven Musculoskeletal Modeling for Personalized Neurorehabilitation Technologies

OBJECTIVES

The development of neurorehabilitation technologies requires the profound understanding of the mechanisms underlying an individual's motor ability and impairment. A major factor limiting this understanding is the difficulty of bridging between events taking place at the neurophysiologic level (i.e., motor neuron firings) with those emerging at the musculoskeletal level (i.e. joint actuation), in vivo in the intact moving human. This review presents emerging model-based methodologies for filling this gap that are promising for developing clinically viable technologies.

METHODS

We provide a design overview of musculoskeletal modeling formulations driven by recordings of neuromuscular activity with a critical comparison to alternative model-free approaches in the context of neurorehabilitation technologies. We present advanced electromyography-based techniques for interfacing with the human nervous system and model-based techniques for translating the extracted neural information into estimates of motor function.

RESULTS

We introduce representative application areas where modeling is relevant for accessing neuromuscular variables that could not be measured experimentally. We then show how these variables are used for designing personalized rehabilitation interventions, biologically inspired limbs, and human-machine interfaces.

CONCLUSION

The ability of using electrophysiological recordings to inform biomechanical models enables accessing a broader range of neuromechanical variables than analyzing electrophysiological data or movement data individually. This enables understanding the neuromechanical interplay underlying in vivo movement function, pathology, and robot-assisted motor recovery.

SIGNIFICANCE

Filling the gap between our understandings of movement neural and mechanical functions is central for addressing one of the major challenges in neurorehabilitation: personalizing current technologies and interventions to an individual's anatomy and impairment.