Optimizing User Integration for Individualized Rehabilitation

User integration with assistive devices or rehabilitation protocols to improve movement function is a key principle to consider for developers to truly optimize performance gains. Better integration may entail customizing operation of devices and training programs according to several user characteristics during execution of functional tasks. These characteristics may be physical dimensions, residual capabilities, restored sensory feedback, cognitive perception, or stereotypical actions

A Generalized Method for Predictive Simulation-Based Lower Limb Prosthesis Design

Lower limb prostheses are designed to replace the functions and form of the missing biological anatomy. These functions are hypothesized to improve user outcome measures which are negatively affected by receiving an amputation – such as metabolic cost of transport, preferred walking speed, and perceived discomfort during walking. However, the effect of these design functions on the targeted outcome measures is highly variable, suggesting that these relationships are not fully understood. Biomechanics simulation and modeling tools are increasingly capable of analyzing the effects of a design on the resulting user gait. In this work, prothesis-aided gait is optimized in simulation to reduce both muscle effort and peak loads on the residual limb using a generalized prosthesis model. Compared to a traditional revolute powered ankle joint model, a two degree-of freedom generalized model reduced muscle activations by 50% and peak loads by 15%. Simulated prosthesis behaviors corresponding to the optimal gait patterns were translated into a two degree-of-freedom ankle-foot prosthesis design with powered bidirectional linear translation and plantarflexion. The prototype is capable of delivering up to 171 N-m of plantarflexion torque and 499 N of translation force, with 15° dorsi-/35° plantarflexion and 10 cm translation range of motion. The mass and height of the ankle-foot are 2.29 kg and 19.5 cm, respectively. The mass of the entire system including the wearable offboard system is 8.58 kg. This platform is designed to emulate the behavior of the simulated prosthesis, as well as be configurable to emulate alternate behaviors obtained from simulations with different optimization objectives. The prototype is controlled to replicate simulated walking patterns using a high level finite state controller, mid-level stiffness controller, and low level load controller. Closed loop load control has bandwidth of 15 Hz in translation and 7.2 Hz in flexion. Load tracking during walking with a single able-bodied human subject ranges from 93 to 159 N in translation and 4.6 to 21.3 N-m in flexion. The contribution of this work is to provide a framework for predictive simulation-based prosthesis design, evidence of its practical implementation, and the experimental tools to validate future predictive simulation studies

How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

A Biomimetic Approach to Controlling Restorative Robotics

Movement is the only way a person can interact with the world around them. When trauma to the neuromuscular systems disrupts the control of movement, quality of life suffers. To restore limb functionality, active robotic interventions and/or rehabilitation are required. Unfortunately, the primary obstacle in a person’s recovery is the limited robustness of the human-machine interfaces. Current systems rely on control approaches that rely on the person to learn how the system works instead of the system being more intuitive and working with the person naturally. My research goal is to design intuitive control mechanisms based on biological processes termed the biomimetic approach. I have applied this control scheme to problems with restorative robotics focused on the upper and lower limb control. Operating an advanced active prosthetic hand is a two-pronged problem of actuating a high-dimensional mechanism and controlling it with an intuitive interface. Our approach attempts to solve these problems by going from muscle activity, electromyography (EMG), to limb kinematics calculated through dynamic simulation of a musculoskeletal model. This control is more intuitive to the user because they attempt to move their hand naturally, and the prosthetic hand performs that movement. The key to this approach was validating simulated muscle paths using both experimental measurements and anatomical constraints where data is missing. After the validation, simulated muscle paths and forces are used to decipher the intended movement. After we have calculated the intended movement, we can move a prosthetic hand to match. This approach required minimal training to give an amputee the ability to control prosthetic hand movements, such as grasping. A more intuitive controller has the potential to improve how people interact and use their prosthetic hands. Similarly, the rehabilitation of the locomotor system in people with damaged motor pathways or missing limbs require appropriate interventions. The problem of decoding human motor intent in a treadmill walking task can be solved with a biomimetic approach. Estimated limb speed is essential for this approach according to the theoretical input-output computation performed by spinal central pattern generators (CPGs), which represents neural circuitry responsible for autonomous control of stepping. The system used the locomotor phases, swing and stance, to estimate leg speeds and enable self-paced walking as well as steering in virtual reality with congruent visual flow. The unique advantage of this system over the previous state-of-art is the independent leg speed control, which is required for multidirectional movement in VR. This system has the potential to contribute to VR gait rehab techniques. Creating biologically-inspired controllers has the potential to improve restorative robotics and allow people a better opportunity to recover lost functionality post-injury. Movement is the only way a person can interact with the world around them. When trauma to the neuromuscular systems disrupts the control of movement, quality of life suffers. To restore limb functionality, active robotic interventions and/or rehabilitation are required. Unfortunately, the primary obstacle in a person’s recovery is the limited robustness of the human-machine interfaces. Current systems rely on control approaches that rely on the person to learn how the system works instead of the system being more intuitive and working with the person naturally. My research goal is to design intuitive control mechanisms based on biological processes termed the biomimetic approach. I have applied this control scheme to problems with restorative robotics focused on the upper and lower limb control.Operating an advanced active prosthetic hand is a two-pronged problem of actuating a high-dimensional mechanism and controlling it with an intuitive interface. Our approach attempts to solve these problems by going from muscle activity, electromyography (EMG), to limb kinematics calculated through dynamic simulation of a musculoskeletal model. This control is more intuitive to the user because they attempt to move their hand naturally, and the prosthetic hand performs that movement. The key to this approach was validating simulated muscle paths using both experimental measurements and anatomical constraints where data is missing. After the validation, simulated muscle paths and forces are used to decipher the intended movement. After we have calculated the intended movement, we can move a prosthetic hand to match. This approach required minimal training to give an amputee the ability to control prosthetic hand movements, such as grasping. A more intuitive controller has the potential to improve how people interact and use their prosthetic hands.Similarly, the rehabilitation of the locomotor system in people with damaged motor pathways or missing limbs require appropriate interventions. The problem of decoding human motor intent in a treadmill walking task can be solved with a biomimetic approach. Estimated limb speed is essential for this approach according to the theoretical input-output computation performed by spinal central pattern generators (CPGs), which represents neural circuitry responsible for autonomous control of stepping. The system used the locomotor phases, swing and stance, to estimate leg speeds and enable self-paced walking as well as steering in virtual reality with congruent visual flow. The unique advantage of this system over the previous state-of-art is the independent leg speed control, which is required for multidirectional movement in VR. This system has the potential to contribute to VR gait rehab techniques.Creating biologically-inspired controllers has the potential to improve restorative robotics and allow people a better opportunity to recover lost functionality post-injury

A Novel Approach to Simulating Realistic Exoskeleton Behavior in Response to Human Motion

Simulation models are a valuable tool for exoskeleton development, especially for system optimization and evaluation. It allows an assessment of the performance and effectiveness of exoskeletons even at an early stage of their development without physical realization. Due to the closed physical interaction between the exoskeleton and the user, accurate modeling of the human–exoskeleton interaction in defined scenarios is essential for exoskeleton simulations. This paper presents a novel approach to simulate exoskeleton motion in response to human motion and the interaction forces at the physical interfaces between the human and the exoskeleton. Our approach uses a multibody model of a shoulder exoskeleton in MATLAB R2021b and imports human motion via virtual markers from a digital human model to simulate human–exoskeleton interaction. To validate the human-motion-based approach, simulated exoskeleton motion and interaction forces are compared with experimental data from a previous lab study. The results demonstrate the feasibility of our approach to simulate human–exoskeleton interaction based on human motion. In addition, the approach is used to optimize the support profile of an exoskeleton, indicating its potential to assist exoskeleton development prior to physical prototyping

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