Changing human upper-limb synergies with an exoskeleton using viscous fields

International audienceRobotic exoskeletons can apply forces distributed on the limbs of the subject they are connected to. This offers a great potential in the field of neurorehabilitation, to address the impairment of interjoint coordination in hemiparetic stroke patients. In these patients, the normal flexible joint rotation synergies are replaced by pathological fixed patterns of rotation. In this paper, we investigate how the concept of synergy can be exploited in the control of an upper limb exoskeleton. The long term goal is to develop a device capable of changing the joint synchronization of a patient performing exercises during rehabilitation. The paper presents a controller able of generating joint viscous torques in such a way that constraints on joint velocities can be imposed to the subject without constraining the hand motion. On another hand, the same formalism is used to describe synergies observed on the arm joint motion of subjects realizing pointing tasks. This approach is experimented on a 4 Degrees Of Freedom (DoF) upper arm exoskeleton with subjects performing pointing 3-dimensional tasks. Results exhibit the basic properties of the controller and show its capacity to impose an arbitrary chosen synergy without affecting the hand motion

Robotic exoskeletons: A perspective for the rehabilitation of arm coordination in stroke patients

Upper-limb impairment after stroke is caused by weakness, loss of individual joint control, spasticity, and abnormal synergies. Upper-limb movement frequently involves abnormal, stereotyped, and fixed synergies, likely related to the increased use of sub-cortical networks following the stroke. The flexible coordination of the shoulder and elbow joints is also disrupted. New methods for motor learning, based on the stimulation of activity- dependent neural plasticity have been developed. These include robots that can adaptively assist active movements and generate many movement repetitions. However, most of these robots only control the movement of the hand in space. The aim of the present text is to analyze the potential of robotic exoskeletons to specifically rehabilitate joint motion and particularly inter-joint coordination. First, a review of studies on upper-limb coordination in stroke patients is presented and the potential for recovery of coordination is examined. Second, issues relating to the mechanical design of exoskeletons and the transmission of constraints between the robotic and human limbs are discussed. The third section considers the development of different methods to control exoskeletons: existing rehabilitation devices and approaches to the control and rehabilitation of joint coordinations are then reviewed, along with preliminary clinical results available. Finally, perspectives and future strategies for the design of control mechanisms for rehabilitation exoskeletons are discussed

ReHand - a portable assistive rehabilitation hand exoskeleton

This dissertation presents a synthesis of a novel underactuated exoskeleton (namely ReHand2) thought and designed for a task-oriented rehabilitation and/or for empower the human hand. The first part of this dissertation shows the current context about the robotic rehabilitation with a focus on hand pathologies, which influence the hand capability. The chapter is concluded with the presentation of ReHand2. The second chapter describes the human hand biomechanics. Starting from the definition of human hand anatomy, passing through anthropometric data, to taxonomy on hand grasps and finger constraints, both from static and dynamic point of view. In addition, some information about the hand capability are given. The third chapter analyze the current state of the art in hand exoskeleton for rehabilitation and empower tasks. In particular, the chapter presents exoskeleton technologies, from mechanisms to sensors, passing though transmission and actuators. Finally, the current state of the art in terms of prototype and commercial products is presented. The fourth chapter introduces the concepts of underactuation with the basic explanation and the classical notation used typically in the prosthetic field. In addition, the chapter describe also the most used differential elements in the prosthetic, follow by a statical analysis. Moreover typical transmission tree at inter-finger level as well as the intra- finger underactuation are explained . The fifth chapter presents the prototype called ReHand summarizing the device description and explanation of the working principle. It describes also the kinetostatic analysis for both, inter- and the intra-finger modules. in the last section preliminary results obtained with the exoskeleton are shown and discussed, attention is pointed out on prototype’s problems that have carry out at the second version of the device. The sixth chapter describes the evolution of ReHand, describing the kinematics and dynamics behaviors. In particular, for the mathematical description is introduced the notation used in order to analyze and optimize the geometry of the entire device. The introduced model is also implemented in Matlab Simulink environment. Finally, the chapter presents the new features. The seventh chapter describes the test bench and the methodologies used to evaluate the device statical, and dynamical performances. The chapter presents and discuss the experimental results and compare them with simulated one. Finally in the last chapter the conclusion about the ReHand project are proposed as well as the future development. In particular, the idea to test de device in relevant environments. In addition some preliminary considerations about the thumb and the wrist are introduced, exploiting the possibility to modify the entire layout of the device, for instance changing the actuator location

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

Electromyography Based Human-Robot Interfaces for the Control of Artificial Hands and Wearable Devices

The design of robotic systems is currently facing human-inspired solutions as a road to replicate the human ability and flexibility in performing motor tasks. Especially for control and teleoperation purposes, the human-in-the-loop approach is a key element within the framework know as Human-Robot Interface. This thesis reports the research activity carried out for the design of Human-Robot Interfaces based on the detection of human motion intentions from surface electromyography. The main goal was to investigate intuitive and natural control solutions for the teleoperation of both robotic hands during grasping tasks and wearable devices during elbow assistive applications. The design solutions are based on the human motor control principles and surface electromyography interpretation, which are reviewed with emphasis on the concept of synergies. The electromyography based control strategies for the robotic hand grasping and the wearable device assistance are also reviewed. The contribution of this research for the control of artificial hands rely on the integration of different levels of the motor control synergistic organization, and on the combination of proportional control and machine learning approaches under the guideline of user-centred intuitiveness in the Human-Robot Interface design specifications. From the side of the wearable devices, the control of a novel upper limb assistive device based on the Twisted String Actuation concept is faced. The contribution regards the assistance of the elbow during load lifting tasks, exploring a simplification in the use of the surface electromyography within the design of the Human-Robot Interface. The aim is to work around complex subject-dependent algorithm calibrations required by joint torque estimation methods

Towards Human-like Walking with Biomechanical and Neuromuscular Control Features: Personalized Attachment Point Optimization Method of Cable-Driven Exoskeleton

The cable-driven exoskeleton can avoid joint misalignment, and is substantial alterations in the pattern of muscle synergy coordination, which arouse more attention in recent years to facilitate exercise for older adults and improve their overall quality of life. This study leverages principles from neuroscience and biomechanical analysis to select attachment points for cable-driven soft exoskeletons. By extracting key features of human movement, the objective is to develop a subject-specific design methodology that provides precise and personalized support in the attachment points optimization of cable-driven exoskeleton to achieve natural gait, energy efficiency, and muscle coordination controllable in the domain of human mobility and rehabilitation. To achieve this, the study first analyzes human walking experimental data and extracts biomechanical features. These features are then used to generate trajectories, allowing better natural movement under complete cable-driven exoskeleton control. Next, a genetic algorithm-based method is employed to minimize energy consumption and optimize the attachment points of the cable-driven system. This process identifies connections that are better suited for the human model, leading to improved efficiency and natural movement. By comparing the calculated elderly human model driven by exoskeleton with experimental subject in terms of joint angles, joint torques and muscle forces, the human model can successfully replicate subject movement and the cable output forces can mimic human muscle coordination. The optimized cable attachment points facilitate more natural and efficient collaboration between humans and the exoskeleton, making significant contributions to the field of assisting the elderly in rehabilitation

Shear-promoted drug encapsulation into red blood cells: a CFD model and μ-PIV analysis

The present work focuses on the main parameters that influence shear-promoted encapsulation of drugs into erythrocytes. A CFD model was built to investigate the fluid dynamics of a suspension of particles flowing in a commercial micro channel. Micro Particle Image Velocimetry (μ-PIV) allowed to take into account for the real properties of the red blood cell (RBC), thus having a deeper understanding of the process. Coupling these results with an analytical diffusion model, suitable working conditions were defined for different values of haematocrit

Biologically – Plausible Load Feedback from Dynamically Scaled Robotic Model Insect Legs

Researchers have been studying the mechanisms underlying animal motor control for many years using computational models and biomimetic robots. Since testing some theories in animals can be challenging, this approach can enable unique contributions to the field. An example of a system that benefits from this modeling and robotics approach is the campaniform sensillum (CS), a kind of sensory organ used to detect the loads exerted on an insect\u27s legs. The CS on the leg are found in groups on high-stress areas of the exoskeleton and have a major influence on the adaptation of walking behavior. The challenge for studying these sensors is recording CS output from freely walking insects, which would show what the sensors detect during behavior. To address this difficulty, 3 dynamically scaled robotic models of the middle leg of the stick insect Carausius morosus (C. morosus) and the fly Drosophila melanogaster (D. melanogaster) were constructed. Two of the robotic legs model the C. morosus and are scaled to a stick insect at a ratio of 15:1 and 25:1. The robotic fly leg is scaled 400:1 to the leg of the D. melanogaster. Strain gauges are affixed to locations and orientations that are analogous to those of major CS groups. The legs were attached to a linear guide to simulate weight and they stepped on a treadmill to mimic walking. Using these robotic models, it is possible to shed light on how the nervous system of insects detects load feedback, examine the effect of different tarsi designs on load feedback, and compare the CS measurement capabilities of different insects. As mentioned earlier, robotic legs allow for any experiment to be conducted, and strain data can still be recorded, unlike animals. I subjected the 15:1 stick leg to a range of stepping conditions, including various static loading, transient loading, and leg slipping. I then processed the strain data through a previously published dynamic computational model of CS discharge. This demonstrated that the CS signal can robustly signal increasing forces at the beginning of the stance phase and decreasing forces at the end of the stance phase or when the foot slips. The same model leg can then be further expanded upon, allowing us to test how different tarsus designs affect load feedback. To isolate various morphological effects, these tarsi were developed with differing degrees of compliance, passive grip, and biomimetic structure. These experiments demonstrated that the tarsus plays a distinct role in loading the leg because of the various effects each design had on the strain. In the final experiment, two morphologically distinct insects with homologous CS groups were compared. The 400:1 robotic fly middle leg and the 25:1 robotic stick insect middle leg were used for these tests. The measured strains were notably influenced by the leg morphology, stepping kinematics, and sensor locations. Additionally, the sensor locations were lacking in one species in comparison to the other measured strains that were already being measured by the present sensors. These findings contributed to the understanding of load sensing in animal locomotion, effects of tarsal morphology, and sensory organ morphology in motor control