Development and Biomechanical Analysis toward a Mechanically Passive Wearable Shoulder Exoskeleton

Shoulder disability is a prevalent health issue associated with various orthopedic and neurological conditions, like rotator cuff tear and peripheral nerve injury. Many individuals with shoulder disability experience mild to moderate impairment and struggle with elevating the shoulder or holding the arm against gravity. To address this clinical need, I have focused my research on developing wearable passive exoskeletons that provide continuous at-home movement assistance. Through a combination of experiments and computational tools, I aim to optimize the design of these exoskeletons. In pursuit of this goal, I have designed, fabricated, and preliminarily evaluated a wearable, passive, cam-driven shoulder exoskeleton prototype. Notably, the exoskeleton features a modular spring-cam-wheel module, allowing customizable assistive force to compensate for different proportions of the shoulder elevation moment due to gravity. The results of my research demonstrated that this exoskeleton, providing modest one-fourth gravity moment compensation at the shoulder, can effectively reduce muscle activity, including deltoid and rotator cuff muscles. One crucial aspect of passive shoulder exoskeleton design is determining the optimal anti-gravity assistance level. I have addressed this challenge using computational tools and found that an assistance level within the range of 20-30% of the maximum gravity torque at the shoulder joint yields superior performance for specific shoulder functional tasks. When facing a new task dynamic, such as wearing a passive shoulder exoskeleton, the human neuro-musculoskeletal system adapts and modulates limb impedance at the end-limb (i.e., hand) to enhance task stability. I have presented development and validation of a realistic neuromusculoskeletal model of the upper limb that can predict stiffness modulation and motor adaptation in response to newly introduced environments and force fields. Future studies will explore the model\u27s applicability in predicting stiffness modulation for 3D movements in novel environments, such as passive assistive devices\u27 force fields

Optimal exoskeleton design and effective human-in-the-loop control frameworks for rehabilitation robotics

Attention, since they decrease the cost of repetitive movement therapies, enable quantitative measurement of the patient progress and promise development of more e ective rehabilitation protocols. The goal of this dissertation is to provide systematic frameworks for optimal design of rehabilitation robots and e ective delivery of therapeutic exercises. The design framework is built upon identification and categorization of the design requirements, and satisfaction of them through several design stages. In particular, type selection is performed to ensure imperative design requirements of safety, ergonomy and wearability, optimal dimensional synthesis is undertaken to maximize global kinematic and dynamic performance defined over the singularity-free workspace volume, while workspace optimization is performed to utilize maximum singularity-free device workspace computed via Grassmann line theory. Then, humanin- the-loop controllers that ensure coupled stability of the human-robot system are implemented in the robot task space using appropriate error metrics. The design framework is demonstrated on a forearm-wrist exoskeleton, since forearm and wrist rotations are critical in performing activities of daily living and recovery of these joints is essential for achieving functional independence of patients. In particular, a non-symmetric 3RPS-R mechanism is selected as the underlying kinematics type and the performance improvements due to workspace and multi-criteria optimizations are experimentally characterized as 27 % larger workspace volume, 32 % higher position control bandwidth and 17 % increase in kinematic isotropy when compared to a similar device in the literature. The exoskeleton is also shown to feature high passive back-driveability and accurate sti ness rendering capability, even under open-loop impedance control. Local controllers to accommodate for each stage of rehabilitation therapies are designed for the forearm-wrist exoskeleton in SO(3): trajectory tracking controllers are designed for early stages of rehabilitation when severely injured patients are kept passive, impedance controllers are designed to render virtual tunnels implementing forbidden regions in the device workspace and allowing for haptic interactions with virtual environments, and passive contour tracking controllers are implemented to allow for rehabilitation exercises that emphasize coordination and synchronization of multi degrees-of-freedom movements, while leaving the exact timing along the desired contour to the patient. These local controllers are incorporated into a multi-lateral shared controller architecture, which allows for patients to train with online virtual dynamic tasks in collaboration with a therapist. Utilizing this control architecture not only enables the shift of control authority of each agent so that therapists can guide or evaluate movements of patients or share the control with them, but also enables the implementation of remote and group therapies, as well as remote assessments. The proposed control framework to deliver e ective robotic therapies can ensure active involvement of patients through online modification of the task parameters, while simultaneously guaranteeing their safety. In particular, utilizing passive velocity field control and extending it with a method for online generation of velocity fields for parametric curves, temporal, spatial and assistive aspects of a desired task can be seamlessly modified online, while ensuring passivity with respect to externally applied forces. Through human subject experiments, this control framework is shown to be e ective in delivering evidence-based rehabilitation therapies, providing assistance as-needed, preventing slacking behavior of patients, and delivering repetitive therapies without exact repetition. Lastly, to guide design of e ective rehabilitation treatment protocols, a set of healthy human subject experiments are conducted in order to identify underlying principles of adaptation mechanism of human motor control system. In these catch-trial based experiments, equivalent transfer functions are utilized during execution of rhythmic dynamic tasks. Statistical evidence suggests that i) force feedback is the dominant factor that guides human adaptation while performing fast rhythmic dynamic tasks rather than the visual feedback and ii) as the e ort required to perform the task increases, the rate of adaptation decreases; indicating a fundamental trade-o between task performance and level of force feedback provided

Kinematics and Robot Design IV, KaRD2021

This volume collects the papers published on the special issue “Kinematics and Robot Design IV, KaRD2021” (https://www.mdpi.com/journal/robotics/special_issues/KaRD2021), which is the forth edition of the KaRD special-issue series, hosted by the open-access journal “MDPI Robotics”. KaRD series is an open environment where researchers can present their works and discuss all the topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”. KaRD2021, after the peer-review process, accepted 12 papers. The accepted papers cover some theoretical and many design/applicative aspects

Proceedings XXII Congresso SIAMOC 2022

Il congresso annuale della Società Italiana di Analisi del Movimento in Clinica dà l’occasione a tutti i professionisti, dell’ambito clinico e ingegneristico, di incontrarsi, presentare le proprie ricerche e rimanere aggiornati sulle più recenti innovazioni nell’ambito dell’applicazione clinica dei metodi di analisi del movimento, al fine di promuoverne lo studio e le applicazioni cliniche per migliorare la valutazione dei disordini motori, aumentare l’efficacia dei trattamenti attraverso l’analisi quantitativa dei dati e una più focalizzata pianificazione dei trattamenti, ed inoltre per quantificare i risultati delle terapie correnti

EEG and ECoG features for Brain Computer Interface in Stroke Rehabilitation

The ability of non-invasive Brain-Computer Interface (BCI) to control an exoskeleton was used for motor rehabilitation in stroke patients or as an assistive device for the paralyzed. However, there is still a need to create a more reliable BCI that could be used to control several degrees of Freedom (DoFs) that could improve rehabilitation results. Decoding different movements from the same limb, high accuracy and reliability are some of the main difficulties when using conventional EEG-based BCIs and the challenges we tackled in this thesis. In this PhD thesis, we investigated that the classification of several functional hand reaching movements from the same limb using EEG is possible with acceptable accuracy. Moreover, we investigated how the recalibration could affect the classification results. For this reason, we tested the recalibration in each multi-class decoding for within session, recalibrated between-sessions, and between sessions. It was shown the great influence of recalibrating the generated classifier with data from the current session to improve stability and reliability of the decoding. Moreover, we used a multiclass extension of the Filter Bank Common Spatial Patterns (FBCSP) to improve the decoding accuracy based on features and compared it to our previous study using CSP. Sensorimotor-rhythm-based BCI systems have been used within the same frequency ranges as a way to influence brain plasticity or controlling external devices. However, neural oscillations have shown to synchronize activity according to motor and cognitive functions. For this reason, the existence of cross-frequency interactions produces oscillations with different frequencies in neural networks. In this PhD, we investigated for the first time the existence of cross-frequency coupling during rest and movement using ECoG in chronic stroke patients. We found that there is an exaggerated phase-amplitude coupling between the phase of alpha frequency and the amplitude of gamma frequency, which can be used as feature or target for neurofeedback interventions using BCIs. This coupling has been also reported in another neurological disorder affecting motor function (Parkinson and dystonia) but, to date, it has not been investigated in stroke patients. This finding might change the future design of assistive or therapeuthic BCI systems for motor restoration in stroke patients

Neuromechanical Tuning for Arm Motor Control

Movement is a fundamental behavior that allows us to interact with the external world. Its importance to human health is most evident when it becomes impaired due to disease or injury. Physical and occupational rehabilitation remains the most common treatment for these types of disorders. Although therapeutic interventions may improve motor function, residual deficits are common for many pathologies, such as stroke. The development of novel therapeutics is dependent upon a better understanding of the underlying mechanisms that govern movement. Movement of the human body adheres to the principles of classic Newtonian mechanics. However, due to the inherent complexity of the body and the highly variable repertoire of environmental contexts in which it operates, the musculoskeletal system presents a challenging control problem and the onus is on the central nervous system to reliably solve this problem. The neural motor system is comprised of numerous efferent and afferent pathways with a hierarchical organization which create a complex arrangement of feedforward and feedback circuits. However, the strategy that the neural motor system employs to reliably control these complex mechanics is still unknown. This dissertation will investigate the neural control of mechanics employing a “bottom-up” approach. It is organized into three research chapters with an additional introductory chapter and a chapter addressing final conclusions. Chapter 1 provides a brief description of the anatomical and physiological principles of the human motor system and the challenges and strategies that may be employed to control it. Chapter 2 describes a computational study where we developed a musculoskeletal model of the upper limb to investigate the complex mechanical interactions due to muscle geometry. Muscle lengths and moment arms contribute to force and torque generation, but the inherent redundancy of these actuators create a high-dimensional control problem. By characterizing these relationships, we found mechanical coupling of muscle lengths which the nervous system could exploit. Chapter 3 describes a study of muscle spindle contribution to muscle coactivation using a computational model of primary afferent activity. We investigated whether these afferents could contribute to motoneuron recruitment during voluntary reaching tasks in humans and found that afferent activity was orthogonal to that of muscle activity. Chapter 4 describes a study of the role of the descending corticospinal tract in the compensation of limb dynamics during arm reaching movements. We found evidence that corticospinal excitability is modulated in proportion to muscle activity and that the coefficients of proportionality vary in the course of these movements. Finally, further questions and future directions for this work are discussed in the Chapter 5

Hybrid walking therapy with fatigue management for spinal cord injured individuals

In paraplegic individuals with upper motor neuron lesions the descending path for signals from central nervous system to the muscles are lost or diminished. Motor neuroprosthesis based on electrical stimulation can be applied to induce restoration of motor function in paraplegic patients. Furthermore, electrical stimulation of such motor neuroprosthesis can be more efficiently managed and delivered if combined with powered exoskeletons that compensate the limited force in the stimulated muscles and bring additional support to the human body. Such hybrid overground gait therapy is likely to be more efficient to retrain the spinal cord in incomplete injuries than conventional, robotic or neuroprosthetic approaches. However, the control of bilateral joints is difficult due to the complexity, non-linearity and time-variance of the system involved. Also, the effects of muscle fatigue and spasticity in the stimulated muscles complicate the control task. Furthermore, a compliant joint actuation is required to allow for a cooperative control approach that is compatible with the assist-as-needed rehabilitation paradigm. These were direct motivations for this research. The overall aim was to generate the necessary knowledge to design a novel hybrid walking therapy with fatigue management for incomplete spinal cord injured subjects. Research activities were conducted towards the establishment of the required methods and (hardware and software) systems that required to proof the concept with a pilot clinical evaluation. Speciffically, a compressive analysis of the state of the art on hybrid exoskeletons revealed several challenges which were tackled by this dissertation. Firstly, assist-as-needed was implemented over the basis of a compliant control of the robotic exoskeleton and a closed-loop control of the neuroprosthesis. Both controllers are integrated within a hybrid-cooperative strategy that is able to balance the assistance of the robotic exoskeleton regarding muscle performance. This approach is supported on the monitoring of the leg-exoskeleton physical interaction. Thus the fatigue caused by neuromuscular stimulation was also subject of speciffic research. Experimental studies were conducted with paraplegic patients towards the establishment of an objective criteria for muscle fatigue estimation and management. The results of these studies were integrated in the hybrid-cooperative controller in order to detect and manage muscle fatigue while providing walking therapy. Secondly closed-loop control of the neuroprosthesis was addressed in this dissertation. The proposed control approach allowed to tailor the stimulation pattern regarding the speciffic residual motor function of the lower limb of the patient. In order to uncouple the closed-loop control from muscle performance monitoring, the hybrid-cooperative control approach implemented a sequential switch between closed-loop and open-loop control of the neuroprosthesis. Lastly, a comprehensive clinical evaluation protocol allowed to assess the impact of the hybrid walking therapy on the gait function of a sample of paraplegic patients. Results demonstrate that: 1) the hybrid controller adapts to patient residual function during walking, 2) the therapy is tolerated by patients, and 3) the walking function of patients was improved after participating in the study. In conclusion, the hybrid walking therapy holds potential for rehabilitate walking in motor incomplete paraplegic patients, guaranteeing further research on this topic. This dissertation is framed within two research projects: REHABOT (Ministerio de Ciencia e Innovación, grant DPI2008-06772-C03-02) and HYPER (Hybrid Neuroprosthetic and Neurorobotic Devices for Functional Compensation and Rehabilitation of Motor Disorders, grant CSD2009-00067 CONSOLIDER INGENIO 2010). Within these research projects, cutting-edge research is conducted in the eld of hybrid actuation and control for rehabilitation of motor disorders. This dissertation constitutes proof-of concept of the hybrid walking therapy for paraplegic individuals for these projects. ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------En individuos parapléjicos con lesiones de la motoneurona superior, la conexión descendente para la transmisión de las señales del sistema nervioso central a los músculos se ve perdida o disminuida. Las neuroprótesis motoras basadas en la estimulación eléctrica pueden ser aplicadas para inducir la restauración de la función motora en pacientes con paraplejia. Además, la estimulación eléctrica de tales neuroprótesis motoras se puede gestionar y aplicar de manera más eficiente mediante la combinación con exoesqueletos robóticos que compensen la generación limitada de fuerza de los músculos estimulados, y proporcionen soporte adicional para el cuerpo. Dicha terapia de marcha ambulatoria puede ser probablemente más eficaz para la recuperación de las funciones de la médula espinal en lesiones incompletas que las terapias convencionales, robóticas o neuroprotesicas. Sin embargo, el control bilateral de las articulaciones es difícil debido a la complejidad, no-linealidad y la variación con el tiempo de las características del sistema en cuestión. Además, la fatiga muscular y la espasticidad de los músculos estimulados complican la tarea de control. Por otra parte, se requiere una actuación robótica modulable para permitir un enfoque de control cooperativo compatible con el paradigma de rehabilitación de asistencia bajo demanda. Todo lo anterior constituyó las motivaciones directas para esta investigación. El objetivo general fue generar el conocimiento necesario para diseñar un nuevo tratamiento híbrido de rehabilitación marcha con gestión de la fatiga para lesionados medulares incompletos. Se llevaron a cabo actividades de investigación para el establecimiento de los métodos necesarios y los sistemas (hardware y software) requeridos para probar el concepto mediante una evaluación clínica piloto. Específicamente, un análisis del estado de la técnica sobre exoesqueletos híbridos reveló varios retos que fueron abordados en esta tesis. En primer lugar, el paradigma de asistencia bajo demanda se implementó sobre la base de un control adaptable del exoesqueleto robótico y un control en lazo cerrado de la neuroprótesis. Ambos controladores están integrados dentro de una estrategia híbrida cooperativa que es capaz de equilibrar la asistencia del exoesqueleto robótico en relación con el rendimiento muscular. Este enfoque se soporta sobre la monitorización de la interacción física entre la pierna y el exoesqueleto. Por tanto, la fatiga causada por la estimulación neuromuscular también fue objeto de una investigación específica. Se realizaron estudios experimentales con pacientes parapléjicos para el establecimiento de un criterio objetivo para la detección y la gestión de la fatiga muscular. Los resultados de estos estudios fueron integrados en el controlador híbrido-cooperativo con el fin de detectar y gestionar la fatiga muscular mientras se realiza la terapia híbrida de rehabilitación de la marcha. En segundo lugar, el control en lazo cerrado de la neuroprótesis fue abordado en esta tesis. El método de control propuesto permite adaptar el patrón de estimulación en relación con la funcionalidad residual específica de la extremidad inferior del paciente. Sin embargo, con el n de desacoplar el control en lazo cerrado de la monitorización del rendimiento muscular, el enfoque de control híbrido-cooperativo incorpora una conmutación secuencial entre el control en lazo cerrado y en lazo abierto de la neuropr otesis. Por último, un protocolo de evaluación clínica global permitido evaluar el impacto de la terapia híbrida de la marcha en la función de la marcha de una muestra de pacientes parapléjicos. Los resultados demuestran que: 1) el controlador híbrido se adapta a la función residual del paciente durante la marcha, 2) la terapia es tolerada por los pacientes, y 3) la funci on de marcha del paciente mejora despu es de participar en el estudio. En conclusión, la terapia de híbrida de la marcha alberga un potencial para la rehabilitación de la marcha en pacientes parapléjicos incompletos motor, garantizando realizar investigación más profunda sobre este tema. Esta tesis se enmarca dentro de los dos proyectos de investigación: REHABOT (Ministerio de Ciencia e Innovación, referencia DPI2008-06772-C03-02) y HYPER (Hybrid Neuroprosthetic and Neurorobotic Devices for Functional Compensation and Rehabilitation of Motor Disorders, referencia CSD2009-00067 CONSOLIDER INGENIO 2010). Dentro de estos proyectos se lleva a cabo investigación de vanguardia en el campo de la actuación y el control híbrido de la combinación robot-neuroprótesis para la rehabilitación de trastornos motores. Esta tesis constituye la prueba de concepto de la terapia de híbrida de la marcha para individuos parapléjicos en estos proyectos.This dissertation is framed within two research projects: REHABOT (Ministerio de Ciencia e Innovación, grant DPI2008-06772-C03-02) and HYPER (Hybrid Neuroprosthetic and Neurorobotic Devices for Functional Compensation and Rehabilitation of Motor Disorders, grant CSD2009-00067 CONSOLIDER INGENIO 2010

Electrode Evaluation and Electrocortical Dynamics of Adapting to Small Perturbations during Treadmill Walking

Mobile brain-body imaging (MoBI) seeks to understand human brain and body dynamics during movement and locomotor tasks such as walking with perturbations that challenge balance and lead to adaptation of walking behavior. In this dissertation, I evaluated the long-term electromyography (EMG) recording performance of dry epidermal electrodes for measuring electrical muscle activity. I also evaluated the relationships between the signals recorded from the two sides of dual-sided electroencephalography (EEG) electrodes, a recent advancement in EEG electrode design for measuring electrical brain activity. Last, I investigated adaptation of brain and body responses to small and frequent perturbations during treadmill walking while I recorded brain activity using a custom-built dual-layer EEG system and body kinematics using motion capture. Dry epidermal electrodes provided better Signal Quality Indices, a metric I developed that accounts for signal-to-noise and signal-to-motion contributions, during limited dynamic movements, indicating that high-quality EMG for long-term recording was possible but also limited. For the dual-sided EEG electrode evaluation, I quantified correlations between dual-sided EEG signals in a benchtop experiment. Signals recorded from two sides of a dual-sided EEG electrode were highly correlated during constrained movements but degraded in more realistic random movements. This information is critical for developing EEG cleaning algorithms based on dual-layer EEG systems. For the locomotor adaptation studies, I quantified gait stability using margin of stability and its components and performed source localization and time-frequency analyses to determine electrocortical processes during perturbed walking. Small and frequent treadmill perturbations disrupted gait stability and quickly induced direction-dependent gait stability adaptation. Anterior cingulate theta-band adaptation occurred and was more evident during belt deceleration perturbations compared to belt acceleration perturbations. These results add new knowledge about the characteristics of novel EMG and EEG electrodes and revealed the potential of modulating perturbation direction to tune gait stability strategy and activation of electrocortical dynamics

Novel Neural Interfaces For Upper-Limb Motor Rehabilitation After Stroke

Stroke is the third most common cause of death and the main cause of acquired adult disability in developed countries. The most common consequence of stroke is motor impairment, which becomes chronic in 56% of stroke survivors. However, reorganization of brain networks can occur in response to sensory input, expe- rience and learning. Although several post-stroke neurorehabilitation techniques have been investigated, there is no standardized therapy for severely impaired chronic stroke patients except for brain-machine interfaces (BMIs), which have shown positive results but still fail to elicit full motor function restoration. This work presents novel neural interfaces that aim to improve the existing rehabilita- tion therapies and to offer an alternative treatment to severely paralyzed stroke patients. First, we propose a novel myoelectric interface (MI) that is calibrated with electromyographic (EMG) data from the healthy limb, mirrored and used as a reference model for the paretic arm in order to reshape the pathological muscle synergy organization of stroke patients. A 4-session motor training with this mir- ror MI sufficed to induce motor learning in 10 healthy participants, suggesting that it might be a potential tool for the correction of maladaptive muscle activations and by extension, for the subsequent motor rehabilitation after stroke. Second, although significant positive results have been achieved with non-invasive BMIs based on electroencephalographic (EEG) activity, the functional motor recovery induced by such therapies still remains modest mainly due to poor decoding per- formance. Here, we explored the possibility of using novel algorithms to increase the performance of multi-class EEG-decoding of movements from the same limb, showing encouraging but still limited results. Finally, we propose integrating the novel mirror MI into a cortico-muscular hybrid BMI that combines brain and resid- ual muscle activity to increase decoding accuracy and hence, allow a more natural and dexterous control of the interface, facilitating neuroplasticity and motor re- covery. The system was validated in a healthy participant and a stroke patient, setting the premise for its application in a clinical setup

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information