A Subject-Specific EMG-Driven Musculoskeletal Model for the Estimation of Moments in Ankle Plantar-Dorsiflexion Movement

In traditional rehabilitation process, ankle movement ability is only qualitatively estimated by its motion performance, however, its movement is actually achieved by the forces acting on the joints produced by muscles contraction. In this paper, the musculoskeletal model is introduced to provide a more physiologic method for quantitative muscle forces and muscle moments estimation during rehabilitation. This paper focuses on the modeling method of musculoskeletal model using electromyography (EMG) and angle signals for ankle plantar-dorsiflexion (P-DF) which is very important in gait rehabilitation and foot prosthesis control. Due to the skeletal morphology differences among people, a subject-specific geometry model is proposed to realize the estimation of muscle lengths and muscle contraction force arms. Based on the principle of forward and inverse dynamics, difference evolutionary (DE) algorithm is used to adjust individual parameters of the whole model, realizing subject-specific parameters optimization. Results from five healthy subjects show the inverse dynamics joint moments are well predicted with an average correlation coefficient of 94.21% and the normalized RMSE of 12.17%. The proposed model provides a good way to estimate muscle moments during movement tasks

Mechanical factors affecting the estimation of tibialis anterior force using an EMG-driven modelling approach

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe tibialis anterior (TA) muscle plays a vital role in human movement such as walking and running. Overuse of TA during these movements leads to an increased susceptibility of injuries e.g. chronic exertional compartment syndrome. TA activation has been shown to be affected by increases in exercise, age, and the external environment (i.e. incline and footwear). Because activation parameters of TA change with condition, it leads to the interpretation that force changes occur too. However,activation is only an approximate indicator of force output of a muscle. Therefore, the overall aim of this thesis was to investigate the parameters affecting accurate measure of TA force, leading to development of a subject-specific EMG-driven model, which takes into consideration specific methodological issues. The first study investigated the reasons why the tendon excursion and geometric method differ so vastly in terms of estimation of TA moment arm. Tendon length changes during the tendon excursion method, and location of the TA line of action and irregularities between talus and foot rotations during the geometric method, were found to affect the accuracy of TA moment arm measurement. A novel, more valid, method was proposed. The second study investigated the errors associated with methods used to account for plantar flexor antagonist co-contraction. A new approach was presented and shown to be, at worse, equivalent to current methods, but allows for accounting throughout the complete range of motion. The final study utilised the outputs from studies one and two to directly measure TA force in vivo. This was used to develop, and validate, an EMG-driven TA force model. Less error was found in the accuracy of estimating TA force when the contractile component length changes were modelled using the ankle, as opposed to the muscle. Overall, these findings increase our understanding of not only the mechanics associated with TA and the ankle, but also improves our ability to accurately monitor these.Headley Court Trust and the Defence Medical Rehabilitation Centre

Mechanical factors affecting the estimation of tibialis anterior force using an EMG-driven modelling approach

The tibialis anterior (TA) muscle plays a vital role in human movement such as walking and running. Overuse of TA during these movements leads to an increased susceptibility of injuries e.g. chronic exertional compartment syndrome. TA activation has been shown to be affected by increases in exercise, age, and the external environment (i.e. incline and footwear). Because activation parameters of TA change with condition, it leads to the interpretation that force changes occur too. However,activation is only an approximate indicator of force output of a muscle. Therefore, the overall aim of this thesis was to investigate the parameters affecting accurate measure of TA force, leading to development of a subject-specific EMG-driven model, which takes into consideration specific methodological issues. The first study investigated the reasons why the tendon excursion and geometric method differ so vastly in terms of estimation of TA moment arm. Tendon length changes during the tendon excursion method, and location of the TA line of action and irregularities between talus and foot rotations during the geometric method, were found to affect the accuracy of TA moment arm measurement. A novel, more valid, method was proposed. The second study investigated the errors associated with methods used to account for plantar flexor antagonist co-contraction. A new approach was presented and shown to be, at worse, equivalent to current methods, but allows for accounting throughout the complete range of motion. The final study utilised the outputs from studies one and two to directly measure TA force in vivo. This was used to develop, and validate, an EMG-driven TA force model. Less error was found in the accuracy of estimating TA force when the contractile component length changes were modelled using the ankle, as opposed to the muscle. Overall, these findings increase our understanding of not only the mechanics associated with TA and the ankle, but also improves our ability to accurately monitor these

Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling.

BACKGROUND: Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery. METHODS: We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time. RESULTS: We demonstrated patients' control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients. CONCLUSIONS: Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots

Otimização muscle-in-the-loop em tempo real para reabilitação física com um exosqueleto ativo: uma mudança de paradigma

Assisting human locomotion with a wearable robotic orthosis is still quite challenging, largely due to the complexity of the neuromusculoskeletal system, the time-varying dynamics that accompany motor adaptation, and the uniqueness of every individual’s response to the assistance given by the robot. To this day, these devices have not met their well-known promise yet, mostly due to the fact that they are not perfectly suitable for the rehabilitation of neuropathologic patients. One of the main challenges hampering this goal still relies on the interface and co-dependency between the human and the machine. Nowadays, most commercial exoskeletons replay pre-defined gait patterns, whereas research exoskeletons are switching to controllers based on optimized torque profiles. In most cases, the dynamics of the human musculoskeletal system are still ignored and do not take into account the optimal conditions for inducing a positive modulation of neuromuscular activity. This is because both rehabilitation strategies are still emphasized on the macro level of the whole joint instead of focusing on the muscles’ dynamics and activity, which are the actual anatomical elements that may need to be rehabilitated. Strategies to keep the human in the loop of the exoskeleton’s control laws in real-time may help to overcome these challenges. The main purpose of the present dissertation is to make a paradigm shift in the approach on how the assistance that is given to a subject by an exoskeleton is modelled and controlled during physical rehabilitation. Therefore, in the scope of the present work, it was intended to design, concede, implement, and validate a real-time muscle-in-the-loop optimization model to find the best assistive support ratio that would induce optimal rehabilitation conditions to a specific group of impaired muscles while having a minimum impact on the other healthy muscles. The developed optimization model was implemented in the form of a plugin and was integrated on a neuromechanical model-based interface for driving a bilateral ankle exoskeleton. Experimental pilot tests evaluated the feasibility and effectiveness of the model. Results of the most significant pilots achieved EMG reductions up to 61 ± 3 % in Soleus and 41 ± 10 % in Gastrocnemius Lateralis. Moreover, results also demonstrated the efficiency of the optimization’s specific reduction on rehabilitation by looking into the muscular fatigue after each experiment. Finally, two parallel preliminary studies emerged from the pilots, which looked at muscle adaptation, after a new assistive condition had been applied, over time and at the effect of the lateral positioning of the exoskeleton’s actuators on the leg muscles.Auxiliar a locomoção humana com uma ortose robótica ainda é bastante desafiante, em grande parte devido à complexidade do sistema neuromusculoesquelético, à dinâmica variável no tempo que acompanha a adaptação motora e à singularidade da resposta de cada indivíduo à assistência dada pelo robô. Até hoje, está por cumprir a promessa inicial destes dispositivos, principalmente devido ao facto de não serem perfeitamente adequados para a reabilitação de pacientes neuropatológicos. Um dos principais desafios que dificultam esse objetivo foca-se ainda na interface e na co-dependência entre o ser humano e a máquina. Hoje em dia, a maioria dos exoesqueletos comerciais reproduz padrões de marcha predefinidos, enquanto que os exoesqueletos em investigação estão só agora a mudar para controladores com base em perfis de binário otimizados. Na maioria dos casos, a dinâmica do sistema musculoesquelético humano ainda é ignorada e não tem em consideração as condições ideais para induzir uma modulação positiva da atividade neuromuscular. Isso ocorre porque ambas as estratégias de reabilitação ainda são enfatizadas no nível macro de toda a articulação, em vez de se concentrar na dinâmica e atividade dos músculos, que são os elementos anatómicos que realmente precisam de ser reabilitados. Estratégias para manter o ser humano em loop nos comandos que controlam o exoesqueleto em tempo real podem ajudar a superar estes desafios. O principal objetivo desta dissertação é fazer uma mudança de paradigma na abordagem em como a assistência que é dada a um sujeito por um exosqueleto é modelada e controlada durante a reabilitação física. Portanto, no contexto do presente trabalho, pretendeu-se projetar, conceder, implementar e validar um modelo de otimização muscle-in-the-loop em tempo real para encontrar a melhor relação de suporte capaz de induzir as condições ideais de reabilitação para um grupo específico de músculos fragilizados, tendo um impacto mínimo nos outros músculos saudáveis. O modelo de otimização desenvolvido foi implementado na forma de um plugin e foi integrado numa interface baseada num modelo neuromecânico para o controlo de um exoesqueleto bilateral de tornozelo. Testes experimentais piloto avaliaram a viabilidade e a eficácia do modelo. Os resultados dos testes mais significativos demonstraram reduções de EMG de até 61 ± 3 % no Soleus e 41 ± 10 % no Gastrocnemius Lateral. Adicionalmente, os resultados demonstraram também a eficiência em reabilitação da redução específica no EMG devido à otimização tendo em conta a fadiga muscular após cada teste. Finalmente, dois estudos preliminares paralelos emergiram dos testes piloto, que analisaram a adaptação muscular após uma nova condição assistiva ter sido definida ao longo do tempo e o efeito do posicionamento lateral dos atuadores do exoesqueleto nos músculos da perna.Mestrado em Engenharia Biomédic

Assist-as-needed EMG-based control strategy for wearable powered assistive devices

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)Robotic-based gait rehabilitation and assistance using Wearable Powered Assistive Devices (WPADs), such as orthosis and exoskeletons, has been growing in the rehabilitation area to recover and augment the motor function of neurologically impaired subjects. These WPADs should provide a personalized assistance, since physical condition and muscular fatigue modify from patient to patient. In this field, electromyography (EMG) signals have been used to control WPADs given their ability to infer the user’s motion intention. However, in cases of motor disability conditions, EMG signals present lower magnitudes when compared to EMG signals under healthy conditions. Thus, the use of WPADs managed by EMG signals may not have potential to provide the assistance that the patient requires. The main goal of this dissertation aims the development of an Assisted-As-Needed (AAN) EMG-based control strategy for a future insertion in a Smart Active Orthotic System (SmartOs). To achieve this goal, the following elements were developed and validated: (i) an EMG system to acquire muscle activity signals from the most relevant muscles during the motion of the ankle joint; (ii) machine learning-based tool for ankle joint torque estimation to serve as reference in the AAN EMG-based control strategy; and (iii) a tool for real EMG-based torque estimation using Tibialis Anterior (TA) and Gastrocnemius Lateralis (GASL) muscles and real ankle joint angles. EMG system showed satisfactory pattern correlations with a commercial system. The reference ankle joint torque was generated based on predicted reference ankle joint kinematics, walking speed information (from 1 to 4 km/h) and anthropometric data (body height from 1.51 m to 1.83 m and body mass from 52.0 kg to 83.7 kg), using five machine learning algorithms: Support Vector Regression (SVR), Random Forest (RF), Multilayer Perceptron (MLP), Long-Short Term Memory (LSTM) and Convolutional Neural Network (CNN). CNN provided the best performance, predicting the reference ankle joint torque with fitting curves ranging from 74.7 to 89.8 % and Normalized Root Mean Square Errors (NRMSEs) between 3.16 and 8.02 %. EMG-based torque estimation beneficiates of a higher number of muscles, since EMG data from TA and GASL are not enough to estimate the real ankle joint torque.A assistência e reabilitação robótica usando dispositivos de assistência ativos vestíveis (WPADs), como ortóteses e exosqueletos, tem crescido na área da reabilitação com o fim de recuperar e aumentar a função motora de sujeitos com alterações neurológicas. Estes dispositivos devem fornecer uma assistência personalizada, uma vez que a condição física e a fadiga muscular variam de paciente para paciente. Nesta área, sinais de eletromiografia (EMG) têm sido usados para controlar WPADs, dada a sua capacidade de inferir a intenção de movimento do utilizador. Contudo, em casos de deficiência motora, os sinais de EMG apresentam menor amplitude quando comparados com sinais de EMG em condições saudáveis e, portanto, o uso de WPADs geridos por sinais de EMG pode não oferecer a assistência que o paciente necessita. O principal objetivo desta dissertação visa o desenvolvimento de uma estratégia de controlo baseada em EMG capaz de fornecer assistência quando necessário, para futura integração num sistema ortótico ativo e inteligente (SmartOs). Para atingir este objetivo foram desenvolvidos e validados os seguintes elementos: (i) sistema de EMG para adquirir sinais de atividade muscular dos músculos mais relevantes no movimento da articulação do tornozelo; (ii) ferramenta de machine learning para estimação do binário da articulação do tornozelo para servir como referência na estratégia de controlo; e (iii) ferramenta de estimação do binário real do tornozelo considerando sinais de EMG dos músculos Tibialis Anterior (TA) e Gastrocnemius Lateralis (GASL) e ângulo real do tornozelo. O sistema de EMG apresentou correlações satisfatórias com um sistema comercial. O binário de referência para o tornozelo foi gerado com base no ângulo de referência da mesma articulação, velocidade de marcha (de 1 até 4 km/h) e dados antropométricos (alturas de 1.51 m até 1.83 e massas de 52.0 kg até 83.7 kg), usando cinco algoritmos de machine learning: Support Vector Machine, Random Forest, Multilayer Perceptron, Long-Short Term Memory e Convolutional Neural Network. CNN apresentou a melhor performance, prevendo binários de referência do tornozelo com um fit entre 74.7 e 89.8 % e Normalized Root Mean Square Errors (NRMSE) entre 3.16 e 8.02 %. A estimativa do torque com base em sinais de EMG requer a inclusão de um maior número de músculos, uma vez que sinais de EMG dos músculos TA e GASL não foram suficientes

Validation of an extended foot-ankle musculoskeletal model using in vivo 4D CT data

openPer simulare il movimento del corpo umano, è necessario creare dei modelli che rappresentino le strutture anatomiche. In questo elaborato ci si concentrerà su un modello biomeccanico del complesso piede-caviglia implementato in un software per la modellazione muscoloscheletrica, nella fattispecie OpenSim. OpenSim è un software che consente di sviluppare modelli di strutture muscoloscheletriche e creare simulazioni dinamiche in grado di stimare i parametri interni delle strutture anatomiche (come le forze muscolari e di contatto tra le ossa), attraverso la simulazione della cinematica e la cinetica del movimento delle varie strutture coinvolte. Nel presente elaborato, si è partiti dallo studio di un dataset, acquisito da Boey et al. (2020) tramite scansione 4D CT in combinazione con un dispositivo di manipolazione del piede su soggetti sani e pazienti affetti da instabilità cronica di caviglia. In questo modo è stata valutata la cinematica dell’osso del piede durante il cammino simulato. Lo scopo di questo elaborato è quindi validare un modello del complesso piede-caviglia sviluppato da Malaquias et al. (2016), partendo dai dati acquisiti affinché, imponendo il movimento della pedana, la simulazione restituisca delle variabili comparabili a quelle reali. Il modello muscoloscheletrico esteso del complesso piede-caviglia è composto da sei segmenti rigidi e cinque articolazioni anatomiche (caviglia, sottoastragalica, mediotarsica, tarsometatrsale e metatarsofalangea) per un totale di otto gradi di libertà. A questo modello è stata aggiunto una pedana (per simulare il dispositivo di manipolazione utilizzato nella sperimentazione) e sono stati incrementati i gradi di libertà delle articolazioni di caviglia e sottoastragalica, per ottenere tre gradi di libertà ciascuna. Dopodiché, è stato imposto un movimento combinato di inversione\eversione ed ab-adduzione alla pedana ed è stato valutato il movimento del modello del piede rispetto al dataset.To simulate the movement of the human body, it is necessary to create models that represent anatomical structures. In this thesis the focus will be placed on a biomechanical model of the complex foot-ankle implemented in a software for musculoskeletal modeling, in particular OpenSim. OpenSim is software that allows to develop models of musculoskeletal structures and create dynamic simulations capable of estimating the internal parameters of anatomical structures (such as muscle and contact forces between bones), through the simulation of the kinematics and kinetics of the movement of the various anatomical structures involved. In this paper, the starting point was the study of a dataset, acquired by Boey et al. (2020) with 4D CT scan in combination with a foot manipulator device. The study was run on healthy subjects as well as patients with chronic ankle instability. In this way, the kinematics of the movement of the foot bones during simulated gait was evaluated. The aim of this project was to validate a model of the foot-ankle complex, developed by Malaquias et al. (2016), starting from the acquired data, so that, by imposing the movement of the platform, the simulation would return variables comparable to the dataset. This extended musculoskeletal model of the foot-ankle complex is composed of six rigid segments and five anatomical joints (ankle, subtalar, midtarsal, tarsometatarsal, and metatarsophalangeal) for a total of eight degrees of freedom. A footplate was added to this model (to simulate the foot manipulator device utilized in the experiment) and the degrees of freedom of the ankle and subtalar joints were increased, to obtain three degrees of freedom each. After that, a combined inversion\eversion and plantar\dorsiflexion movement was imposed on the footplate and the movement of the foot model was evaluated against the dataset