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

Adaptation Strategies for Personalized Gait Neuroprosthetics

Personalization of gait neuroprosthetics is paramount to ensure their efficacy for users, who experience severe limitations in mobility without an assistive device. Our goal is to develop assistive devices that collaborate with and are tailored to their users, while allowing them to use as much of their existing capabilities as possible. Currently, personalization of devices is challenging, and technological advances are required to achieve this goal. Therefore, this paper presents an overview of challenges and research directions regarding an interface with the peripheral nervous system, an interface with the central nervous system, and the requirements of interface computing architectures. The interface should be modular and adaptable, such that it can provide assistance where it is needed. Novel data processing technology should be developed to allow for real-time processing while accounting for signal variations in the human. Personalized biomechanical models and simulation techniques should be developed to predict assisted walking motions and interactions between the user and the device. Furthermore, the advantages of interfacing with both the brain and the spinal cord or the periphery should be further explored. Technological advances of interface computing architecture should focus on learning on the chip to achieve further personalization. Furthermore, energy consumption should be low to allow for longer use of the neuroprosthesis. In-memory processing combined with resistive random access memory is a promising technology for both. This paper discusses the aforementioned aspects to highlight new directions for future research in gait neuroprosthetics.Peer ReviewedPostprint (published version

Adaptation Strategies for Personalized Gait Neuroprosthetics

Personalization of gait neuroprosthetics is paramount to ensure their efficacy for users, who experience severe limitations in mobility without an assistive device. Our goal is to develop assistive devices that collaborate with and are tailored to their users, while allowing them to use as much of their existing capabilities as possible. Currently, personalization of devices is challenging, and technological advances are required to achieve this goal. Therefore, this paper presents an overview of challenges and research directions regarding an interface with the peripheral nervous system, an interface with the central nervous system, and the requirements of interface computing architectures. The interface should be modular and adaptable, such that it can provide assistance where it is needed. Novel data processing technology should be developed to allow for real-time processing while accounting for signal variations in the human. Personalized biomechanical models and simulation techniques should be developed to predict assisted walking motions and interactions between the user and the device. Furthermore, the advantages of interfacing with both the brain and the spinal cord or the periphery should be further explored. Technological advances of interface computing architecture should focus on learning on the chip to achieve further personalization. Furthermore, energy consumption should be low to allow for longer use of the neuroprosthesis. In-memory processing combined with resistive random access memory is a promising technology for both. This paper discusses the aforementioned aspects to highlight new directions for future research in gait neuroprosthetics.AK is funded by a faculty endowment by adidas AG. MA, SKH, NM, MN, RJQ, R-DR, RJT are supported by NSF CPS grant 1739800, VA Merit Reviews A2275-R and 3056, and the NIH (5T32EB004314-15, R01 NS040547-13). MS and AG are funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. 803035). AJd-A, JMF-L, and JCM are supported by coordinated grants RTI2018-097290-B-C31/C32/C33 (TAILOR project) funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. MR is funded by the Lo3-ML project by the Federal Ministry for Education, Science and Technology (BMBF) (Funding No. 16ES1142K). AC, SS, and MV were supported by the European Research Council (ERC) under the project NGBMI (759370), the Einstein Stiftung Berlin, the ERA-NET NEURON project HYBRIDMIND (BMBF, 01GP2121A and -B) and the BMBF project NEO (13GW0483C)

Soft Gloves: A Review on Recent Developments in Actuation, Sensing, Control and Applications

Interest in soft gloves, both robotic and haptic, has enormously grown over the past decade, due to their inherent compliance, which makes them particularly suitable for direct interaction with the human hand. Robotic soft gloves have been developed for hand rehabilitation, for ADLs assistance, or sometimes for both. Haptic soft gloves may be applied in virtual reality (VR) applications or to give sensory feedback in combination with prostheses or to control robots. This paper presents an updated review of the state of the art of soft gloves, with a particular focus on actuation, sensing, and control, combined with a detailed analysis of the devices according to their application field. The review is organized on two levels: a prospective review allows the highlighting of the main trends in soft gloves development and applications, and an analytical review performs an in-depth analysis of the technical solutions developed and implemented in the revised scientific research. Additional minor evaluations integrate the analysis, such as a synthetic investigation of the main results in the clinical studies and trials referred in literature which involve soft gloves

Technology applications

A summary of NASA Technology Utilization programs for the period of 1 December 1971 through 31 May 1972 is presented. An abbreviated description of the overall Technology Utilization Applications Program is provided as a background for the specific applications examples. Subjects discussed are in the broad headings of: (1) cancer, (2) cardiovascular disease, (2) medical instrumentation, (4) urinary system disorders, (5) rehabilitation medicine, (6) air and water pollution, (7) housing and urban construction, (8) fire safety, (9) law enforcement and criminalistics, (10) transportation, and (11) mine safety

Empowering and assisting natural human mobility: The simbiosis walker

This paper presents the complete development of the Simbiosis Smart Walker. The device is equipped with a set of sensor subsystems to acquire user-machine interaction forces and the temporal evolution of user's feet during gait. The authors present an adaptive filtering technique used for the identification and separation of different components found on the human-machine interaction forces. This technique allowed isolating the components related with the navigational commands and developing a Fuzzy logic controller to guide the device. The Smart Walker was clinically validated at the Spinal Cord Injury Hospital of Toledo - Spain, presenting great acceptability by spinal chord injury patients and clinical staf

A virtual hand assessment system for efficient outcome measures of hand rehabilitation

Previously held under moratorium from 1st December 2016 until 1st December 2021.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control

Elbow exoskeleton mechanism for multistage poststroke rehabilitation.

More than three million people are suffering from stroke in England. The process of post-stroke rehabilitation consists of a series of biomechanical exercises- controlled joint movement in acute phase; external assistance in the mid phase; and variable levels of resistance in the last phase. Post-stroke rehabilitation performed by physiotherapist has many limitations including cost, time, repeatability and intensity of exercises. Although a large variety of arm exoskeletons have been developed in the last two decades to substitute the conventional exercises provided by physiotherapist, most of these systems have limitations with structural configuration, sensory data acquisition and control architecture. It is still difficult to facilitate multistage post-stroke rehabilitation to patients sited around hospital bed without expert intervention. To support this, a framework for elbow exoskeleton has been developed that is portable and has the potential to offer all three types of exercises (external force, assistive and resistive) in a single structure. The design enhances torque to weight ratio compared to joint based actuation systems. The structural lengths of the exoskeleton are determined based on the mean anthropometric parameters of healthy users and the lengths of upperarm and forearm are determined to fit a wide range of users. The operation of the exoskeleton is divided into three regions where each type of exercise can be served in a specific way depending on the requirements of users. Electric motor provides power in the first region of operation whereas spring based assistive force is used in the second region and spring based resistive force is applied in the third region. This design concept provides an engineering solution of integrating three phases of post-stroke exercises in a single device. With this strategy, the energy source is only used in the first region to power the motor whereas the other two modes of exercise can work on the stored energy of springs. All these operations are controlled by a single motor and the maximum torque of the motor required is only 5 Nm. However, due to mechanical advantage, the exoskeleton can provide the joint torque up to 10 Nm. To remove the dependency on biosensor, the exoskeleton has been designed with a hardware-based mechanism that can provide assistive and resistive force. All exoskeleton components are integrated into a microcontroller-based circuit for measuring three joint parameters (angle, velocity and torque) and for controlling exercises. A user-friendly, multi-purpose graphical interface has been developed for participants to control the mode of exercise and it can be managed manually or in automatic mode. To validate the conceptual design, a prototype of the exoskeleton has been developed and it has been tested with healthy subjects. The generated assistive torque can be varied up to 0.037 Nm whereas resistive torque can be varied up to 0.057 Nm. The mass of the exoskeleton is approximately 1.8 kg. Two comparative studies have been performed to assess the measurement accuracy of the exoskeleton. In the first study, data collected from two healthy participants after using the exoskeleton and Kinect sensor by keeping Kinect sensor as reference. The mean measurement errors in joint angle are within 5.18 % for participant 1 and 1.66% for participant 2; the errors in torque measurement are within 8.48% and 7.93% respectively. In the next study, the repeatability of joint measurement by exoskeleton is analysed. The exoskeleton has been used by three healthy users in two rotation cycles. It shows a strong correction (correlation coefficient: 0.99) between two consecutive joint angle measurements and standard deviation is calculated to determine the error margin which comes under acceptable range (maximum: 8.897). The research embodied in this thesis presents a design framework of a portable exoskeleton model for providing three modes of exercises, which could provide a potential solution for all stages of post- stroke rehabilitation

Physical Diagnosis and Rehabilitation Technologies

The book focuses on the diagnosis, evaluation, and assistance of gait disorders; all the papers have been contributed by research groups related to assistive robotics, instrumentations, and augmentative devices

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