Design of a Passive Wearable Device Using an Optimized Mechanical Metamaterial for Mirror Therapy.

Mirror Therapy (MT) is an effective therapeutic method used in the rehabilitation of hemiplegics. The effectiveness of this method is improved by employing a bi-modal approach which requires the synchronous movement of the affected and unaffected arm. For this purpose, we describe the design of a wearable device using a Mechanical Metamaterial (MM) that is optimized for the specific user to provide passive assistance of wrist flexion-extension and enable synchronous motion of the affected and unaffected arm during MT.

Learning-Based Motion-Intention Prediction for End-Point Control of Upper-Limb-Assistive Robots.

The lack of intuitive and active human-robot interaction makes it difficult to use upper-limb-assistive devices. In this paper, we propose a novel learning-based controller that intuitively uses onset motion to predict the desired end-point position for an assistive robot. A multi-modal sensing system comprising inertial measurement units (IMUs), electromyographic (EMG) sensors, and mechanomyography (MMG) sensors was implemented. This system was used to acquire kinematic and physiological signals during reaching and placing tasks performed by five healthy subjects. The onset motion data of each motion trial were extracted to input into traditional regression models and deep learning models for training and testing. The models can predict the position of the hand in planar space, which is the reference position for low-level position controllers. The results show that using IMU sensor with the proposed prediction model is sufficient for motion intention detection, which can provide almost the same prediction performance compared with adding EMG or MMG. Additionally, recurrent neural network (RNN)-based models can predict target positions over a short onset time window for reaching motions and are suitable for predicting targets over a longer horizon for placing tasks. This study's detailed analysis can improve the usability of the assistive/rehabilitation robots.

Soft, Lightweight Wearable Robots to Support the Upper Limb in Activities of Daily Living: A Feasibility Study on Chronic Stroke Patients.

Stroke can be a devastating condition that impairs the upper limb and reduces mobility. Wearable robots can aid impaired users by supporting performance of Activities of Daily Living (ADLs). In the past decade, soft devices have become popular due to their inherent malleable and low-weight properties that makes them generally safer and more ergonomic. In this study, we present an improved version of our previously developed gravity-compensating upper limb exosuit and introduce a novel hand exoskeleton. The latter uses 3D-printed structures that are attached to the back of the fingers which prevent undesired hyperextension of joints. We explored the feasibility of using this integrated system in a sample of 10 chronic stroke patients who performed 10 ADLs. We observed a significant reduction of 30.3 ± 3.5% (mean ± standard error), 31.2 ± 3.2% and 14.0 ± 5.1% in the mean muscular activity of the Biceps Brachii (BB), Anterior Deltoid (AD) and Extensor Digitorum Communis muscles, respectively. Additionally, we observed a reduction of 14.0 ± 11.5%, 14.7 ± 6.9% and 12.8 ± 4.4% in the coactivation of the pairs of muscles BB and Triceps Brachii (TB), BB and AD, and TB and Pectoralis Major (PM), respectively, typically associated to pathological muscular synergies, without significant degradation of healthy muscular coactivation. There was also a significant increase of elbow flexion angle ( 12.1±1.5° ). These results further cement the potential of using lightweight wearable devices to assist impaired users.

A Microfabricated Dual Slip-Pressure Sensor with Compliant Polymer-Liquid Metal Nanocomposite for Robotic Manipulation.

Conventional grippers fall behind their human counterparts as they do not have integrated sensing capabilities. Piezoresistive and capacitive sensors are popular choices because of their design and sensitivity, but they cannot measure pressure and slip simultaneously. It is imperative to measure slip and pressure concurrently. We demonstrate a dual slip-pressure sensor based on a thermal approach. The sensor comprises two concentric microfabricated heaters maintained at constant temperature. An elastic dome, with embedded liquid metal droplets, is placed on top of concentric heaters. Heat transfer between sensor and the object in contact occurs through the elastic dome. This heat transfer causes changes in the power absorbed by the sensor to maintain its temperature and allows for measurement of pressure while identifying slip events. Liquid metal droplets contribute to enhanced thermal conductivity (0.37 W/m-K) and reduced specific heat (0.86 kJ/kg-K) of the polymer without compromising on mechanical properties (Young's modulus-0.5 MPa). For pressure monitoring, sensor measures change in power ratio against increase in applied force, demonstrating a highly linear performance, with a high sensitivity of 0.0356 N-1 (pressure only) and 0.0189 N-1 (slip with simultaneous pressure applied). The sensor discriminates between different contact types with a 96% accuracy. Response time of the sensor (60-75 ms) matches the measured response time in human skin. The sensor does not get affected by mechanical vibrations paving way for easy integration with robotic manipulators and prosthetics.

Haptic Manipulation of 3D Scans for Geometric Feature Enhancement.

Localisation of geometric features like holes, edges, slots, etc. is vital to robotic planning in industrial automation settings. Low-cost 3D scanners are crucial in terms of improving accessibility, but pose a practical challenge to feature localisation because of poorer resolution and consequently affect robotic planning. In this work, we address the possibility of enhancing the quality of a 3D scan by a manual 'touch-up' of task-relevant features, to ensure their automatic detection prior to automation. We propose a framework whereby the operator (i) has access to both the actual work-piece and its 3D scan; (ii) evaluates the missing salient features from the scan; (iii) uses a haptic stylus to physically interact with the actual work-piece, around such specific features; (iv) interactively updates the scan using the position and force information from the haptic stylus. The contribution of this work is the use of haptic mismatch for geometric update. Specifically, the geometry from the 3D scan is used to predict haptic feedback at a point on the work-piece surface. The haptic mismatch is derived as a measure of error between this prediction and the real interaction forces from physical contact at that point on the work-piece. The geometric update is driven until the haptic mismatch is minimised. Convergence of the proposed algorithm is first numerically verified on an analytical surface with simulated physical interaction. Error analysis of the surface position and orientations were also plotted. Experiments were conducted using a motion capture system providing sub-mm accuracy in position and a 6 axis F/T sensor. Missing features are successfully detected after the update of the scan using the proposed method in an experiment.

Review of Current Spinal Robotic Orthoses.

Osteoporotic spine fractures (OSF) are common sequelae of osteoporosis. OSF are directly correlated with increasing age and incidence of osteoporosis. OSF are treated conservatively or surgically. Associated acute pain, chronic disabilities, and progressive deformities are well documented. Conservative measures include a combination of initial bed rest, analgesia, early physiotherapy, and a spinal brace (orthosis), with the aim for early rehabilitation to prevent complications of immobile state. Spinal bracing is commonly used for symptomatic management of OSF. While traditional spinal braces aim to maintain the neutral spinal alignment and reduce the axial loading on the fractured vertebrae, they are well known for complications including discomfort with reduced compliance, atrophy of paraspinal muscles, and restriction of chest expansion leading to chest infections. Exoskeletons have been developed to passively assist and actively augment human movements with different types of actuators. Flexible, versatile spinal exoskeletons are designed to better support the spine. As new technologies enable the development of motorized wearable exoskeletons, several types have been introduced into the medical field application. We have provided a thorough review of the current spinal robotic technologies in this paper. The shortcomings in the current spinal exoskeletons were identified. Their limitations on the use for patients with OSF with potential improvement strategies were discussed. With our current knowledge of spinal orthosis for conservatively managed OSF, a semi-rigid backpack style thoracolumbar spinal robotic orthosis will reduce spinal bone stress and improve back muscle support. This will lead to back pain reduction, improved posture, and overall mobility. Early mobilization is an important part of management of patients with OSF as it reduces the chance of developing complications related to their immobile state for patients with OSF, which will be helpful for their recovery.

Elbow Motion Trajectory Prediction Using a Multi-Modal Wearable System: A Comparative Analysis of Machine Learning Techniques.

Motion intention detection is fundamental in the implementation of human-machine interfaces applied to assistive robots. In this paper, multiple machine learning techniques have been explored for creating upper limb motion prediction models, which generally depend on three factors: the signals collected from the user (such as kinematic or physiological), the extracted features and the selected algorithm. We explore the use of different features extracted from various signals when used to train multiple algorithms for the prediction of elbow flexion angle trajectories. The accuracy of the prediction was evaluated based on the mean velocity and peak amplitude of the trajectory, which are sufficient to fully define it. Results show that prediction accuracy when using solely physiological signals is low, however, when kinematic signals are included, it is largely improved. This suggests kinematic signals provide a reliable source of information for predicting elbow trajectories. Different models were trained using 10 algorithms. Regularization algorithms performed well in all conditions, whereas neural networks performed better when the most important features are selected. The extensive analysis provided in this study can be consulted to aid in the development of accurate upper limb motion intention detection models.

Multi-Compartment 3D-Cultured Organ-on-a-Chip: Towards a Biomimetic Lymph Node for Drug Development.

The interaction of immune cells with drugs and/or with other cell types should be mechanistically investigated in order to reduce attrition of new drug development. However, they are currently only limited technologies that address this need. In our work, we developed initial but significant building blocks that enable such immune-drug studies. We developed a novel microfluidic platform replicating the Lymph Node (LN) microenvironment called LN-on-a-chip, starting from design all the way to microfabrication, characterization and validation in terms of architectural features, fluidics, cytocompatibility, and usability. To prove the biomimetics of this microenvironment, we inserted different immune cell types in a microfluidic device, which showed an in-vivo-like spatial distribution. We demonstrated that the developed LN-on-a-chip incorporates key features of the native human LN, namely, (i) similarity in extracellular matrix composition, morphology, porosity, stiffness, and permeability, (ii) compartmentalization of immune cells within distinct structural domains, (iii) replication of the lymphatic fluid flow pattern, (iv) viability of encapsulated cells in collagen over the typical timeframe of immunotoxicity experiments, and (v) interaction among different cell types across chamber boundaries. Further studies with this platform may assess the immune cell function as a step forward to disclose the effects of pharmaceutics to downstream immunology in more physiologically relevant microenvironments.

IMU-based assistance modulation in upper limb soft wearable exosuits.

Soft exosuits have advantages over their rigid counterparts in terms of portability, transparency and ergonomics. Our previous work has shown that a soft, fabric-based exosuit, actuated by an electric motor and a Bowden cable, reduced the muscular effort of the user when flexing the elbow. This previous exosuit used a gravity compensation algorithm with the assumption that the shoulder was adducted at the trunk. In this investigation, the shoulder elevation angle was incorporated into the gravity compensation control via inertial measurement units (IMUs). We assessed our updated gravity compensation model with four healthy, male subjects (age: $26.2 \pm 1.19$ years) who followed an elbow flexion reference trajectory which reached three amplitudes $(25^{\circ}, 50^{\circ}, 75^{\circ})$ and was repeated at three shoulder angles $(25^{\circ}, 50^{\circ}, 75^{\circ})$. To assess the performance of the exosuit; the smoothness, tracking accuracy and muscle activity were investigated during each motion. We found a reduction of biceps brachii activation (24.3%) in the powered condition compared to the unpowered condition. In addition, there was an improvement in kinematic smoothness (0.83%) and a reduction of tracking accuracy (26.5%) in the powered condition with respect to the unpowered condition. We can conclude that the updated gravity compensation algorithm has increased the number of supported movements by considering the shoulder elevation, which has improved the usability of the device.

Switching Assistance for Exoskeletons During Cyclic Motions.

This paper proposes a novel control algorithm for torque-controlled exoskeletons assisting cyclic movements. The control strategy is based on the injection of energy parcels into the human-robot system with a timing that minimizes perturbations, i.e., when the angular momentum is maximum. Electromyographic activity of main flexor-extensor knee muscles showed that the proposed controller mostly favors extensor muscles during extension, with a statistically significant reduction in muscular activity in the range of 10-20% in 60 out of 72 trials (i.e., 83%), while no effect related to swinging speed was recorded (speed variation was lower than 10% in 92% of the trials). In the remaining cases muscular activity increment, when statistically significant, was less than 10%. These results showed that the proposed algorithm reduced muscular effort during the most energetically demanding part of the movement (the extension of the knee against gravity) without perturbing the spatio-temporal characteristics of the task and making it particularly suitable for application in exoskeleton-assisted cyclic motions.

Studying the magnetic stimulation of nervous tissues: A calculation framework to investigate stimulation areas.

The electromagnetic stimulation of nervous tissue has represented an alternative to electrical stimulation since the 1980s. The growing number of potential applications has led to an increasing interest in the development of modeling tools that can help the design of novel electromagnetic stimulators. In this context, the aim of this paper is to provide a versatile calculation framework to investigate the properties of the electric field generated by a plurality of miniature coils, arranged in cuff configuration. Furthermore, the capability of the miniature coils to elicit a neuronal response in specific portions of the (peripheral) nerve will be investigated. Starting from Jefimenko's equations, a model was implemented in MATLAB. It calculates the electromagnetic field induced by coils, with arbitrary shape and spatial orientation, and the activating function around the coils through simple numerical integration. By studying the activating functions, it is possible to determine where the neurons can be excited. The model was validated by comparison with FEM simulations. A dimensional analysis was conducted to compare in terms of shape and depth of the stimulation volumes different coil geometries, regardless of design parameters such as current, number of turns and coil sizes.The dimensionless groups identified according to Buckingham's theorem provide a direct estimate of the stimulation depth reached within the nerve.The calculation tools developed in this paper can be used in the design of coils to quickly compare different geometries and spatial distribution of coils in order to identify the optimal configurations for the specific application addressed by the designer.

Swallowable smart pills for local drug delivery: present status and future perspectives.

Smart pills were originally developed for diagnosis; however, they are increasingly being applied to therapy - more specifically drug delivery. In addition to smart drug delivery systems, current research is also looking into localization systems for reaching the target areas, novel locomotion mechanisms and positioning systems. Focusing on the major application fields of such devices, this article reviews smart pills developed for local drug delivery. The review begins with the analysis of the medical needs and socio-economic benefits associated with the use of such devices and moves onto the discussion of the main implemented technological solutions with special attention given to locomotion systems, drug delivery systems and power supply. Finally, desired technical features of a fully autonomous robotic capsule for local drug delivery are defined and future research trends are highlighted.

Self-entrainment to optimal gaits of an underactuated biomimetic swimming robot using adaptive frequency oscillators.

Underactuated compliant swimming robots are characterized by a simple mechanical structure, capable to mimic the body undulation of many fish species. One of the design issue for these robots is the generation and control of best performing swimming gaits. In this paper we propose a new controller, based on AFO oscillators, to address this issue. After analyzing the effects of the motion on the robot natural frequencies, we show that the closed loop system is able to generate self-sustained oscillations, at a characteristic frequency, while maximizing swimming velocity.

Post-Human and scientific researcha: How engineering carried out the project / El posthumano y la investigación científica: como la ingeniería lleva a cabo el proyecto

We start with a definition of robot in order to understand which are legitimate robotics’ objectives. Then it is provided an outline of new robot generations and their industrial and biomedical applications. We consider the consequences of this new kind of technology on the notion of intelligence, stressing how the exteroceptive sensor systems provide a new bottom up approach to the AI debate. We consider three challenges Robotics have to face nowadays. First materials and components, which are built with technologies top-down, set huge limits in terms of weight, speed, safety and cost, not to mention reliability and durability. Second the metholdological aspects: the challenge concerns the management of complexity. How to achieve intelligent and adaptive behaviors out of the control system of the robot, which must remain intrisically simple? A third issue we address is the cultural one: the unreasonable expectations of the general public often provoked by a misunderstanding of the notion of intelligence itself. We consider then what makes human specifically human from a broader philosophic point of view, pointing out how the will is strangely absent in the AI debate. We show three advantages connected with this different perspective instead of the classical one intellect centered. First, while intellect is not used only by man, will is. Second, desire involves intellect while the reciprocal is not necessarily true. Third, looking at robotics and more specifically to cybernetics the key concept of these fields are control and govenrance, whereas both of them are specifically relate to the domain of will rather than intellect. We look then into the concept of participation as essential to the understanding of the notion of will, to overcome some roboethics’ issues related to the adoption of the still dominant rationalitsic paradigm

Después de haber propuesto una definición del concepto de robot, pasamos a considerar cuáles son los objetivos legítimos de una robótica epistemológicamente coherente. Se analizan las nuevas y emergentes tecnologías robóticas y las consecuencias que han tenido en campo biomédico e industrial, con particular atención a los efectos que tienen estas novedades en relación con el concepto de inteligencia. En particular, como la nueva sensoristica, permitiendo la construcción de extero-ceptive systems, ha promovido nuevamente el acercamiento bottom up en el debate sobre la AI. Se consideran tres problemas: el componente hardware, construido hasta hoy con tecnologías top down, poco eficaces para las necesidades bio-médicas; los aspectos metodológicos, concretamente, cómo obtener comportamientos inteligentes y adaptativos, manteniendo el control simple; la cuestión cultural, es decir, cómo responder a las expectativas crecientes y muy frecuentemente inadecuadas que el público espera de la robótica. Atendiendo a algunas razones, se prefiere plantear la cuestión de la especificidad humana apuntando no al tema de la inteligencia sino al de la voluntad: porque es mayormente específica; porque el querer implica el comprender, mientras que no es siempre verdadero lo contrario; porque la robótica nos enseña que el gobierno y el control son problemas reales de los que es necesario hacerse cargo. Profundizaremos, por tanto, la noción de participación como instrumento conceptual útil para la comprensión de la voluntad, que permite, además, superar los nudos irresueltos de la robótica, fundada hasta hoy en acercamientos racionalistas

Invasive neural interfaces: the perspective of the surgeon.

BACKGROUND: By implanting electrodes inside peripheral nerves, amputee's intentions are picked up and exploited to control novel dexterous sensorized hand prostheses. Under the pretext of presenting surgical technique and clinical outcomes of the implant of invasive peripheral neural interfaces in a human amputee, this article critically comments, from the point of view of the surgeon, strengths and weaknesses of the procedure. MATERIALS AND METHODS: Four multielectrodes were implanted in the medial and ulnar nerves of a young volunteer, which, following a car-crash, had a left transradial amputation. Both nerves were approached with a single incision in the medial aspect of the upper arm. Four weeks later, the electrodes were removed. RESULTS: Even if the trauma and the postamputation plastic processes altered the anatomy, electrodes were proficiently implanted with an overall success of 66%. Looking at the procedure from the surgeon's viewpoint unveils few still open issues. Electrodes weaknesses were related to the absence of stabilizing structures, the cable transit through the skin, the implant angle, and the unproven magnetic resonance imaging compatibility. Future investigations are needed to definitely address the better anesthesia, number and sites of incisions, the nerves to implant, and the convenience of performing epineural microdissection. CONCLUSIONS: Invasive neural interfaces developmental process almost completely relies on the efforts of bioengineers and neurophysiologists; however, the surgeon is responsible for intra and perioperative factors. Therefore, he deserves to play a major role also at the stage of specifying the requirements, to satisfy the requisites of a safe, stable, and long-lasting implant.

Post-human and scientific research: how engineering carried out the project.

We start with a definition of robot in order to understand which are legitimate robotics' objectives. Then it is provided an outline of new robot generations and their industrial and biomedical applications. We consider the consequences of this new kind of technology on the notion of intelligence, stressing how the exteroceptive sensor systems provide a new bottom up approach to the AI debate. We consider three challenges Robotics have to face nowadays. First materials and components, which are built with technologies top-down, set huge limits in terms of weight, speed, safety and cost, not to mention reliability and durability. Second the methodological aspects: the challenge concerns the management of complexity. How to achieve intelligent and adaptive behaviours out of the control system of the robot, which must remain intrinsically simple? A third issue we address is the cultural one: the unreasonable expectations of the general public often provoked by a misunderstanding of the notion of intelligence itself. We consider then what makes human specifically human from a broader philosophic point of view, pointing out how the will is strangely absent in the AI debate. We show three advantages connected with this different perspective instead of the classical one intellect centered. First, while intellect is not used only by man, will is. Second, desire involves intellect while the reciprocal is not necessarily true. Third, looking at robotics and more specifically to cybernetics the key concept of these fields are control and governance, whereas both of them are specifically relate to the domain of will rather than intellect. We look then into the concept of participation as essential to the understanding of the notion of will, to overcome some roboethics' issues related to the adoption of the still dominant rationalistic paradigm.

Human-robot interaction tests on a novel robot for gait assistance.

This paper presents tests on a treadmill-based non-anthropomorphic wearable robot assisting hip and knee flexion/extension movements using compliant actuation. Validation experiments were performed on the actuators and on the robot, with specific focus on the evaluation of intrinsic backdrivability and of assistance capability. Tests on a young healthy subject were conducted. In the case of robot completely unpowered, maximum backdriving torques were found to be in the order of 10 Nm due to the robot design features (reduced swinging masses; low intrinsic mechanical impedance and high-efficiency reduction gears for the actuators). Assistance tests demonstrated that the robot can deliver torques attracting the subject towards a predicted kinematic status.

Experimental characterization of a flexible thermal slip sensor.

Tactile sensors are needed for effectively controlling the interaction between a robotic hand and the environment, e.g., during manipulation of objects, or for the tactile exploration of unstructured environments, especially when other sensing modalities, such as vision or audition, become ineffective. In the case of hand prostheses, mainly intended for dexterous manipulation of daily living objects, the possibility of quickly detecting slip occurrence, thus avoiding inadvertent falling of the objects, is prodromal to any manipulation task. In this paper we report on a slip sensor with no-moving parts, based on thermo-electrical phenomena, fabricated on a flexible substrate and suitable for integration on curved surfaces, such as robotic finger pads. Experiments performed using a custom made test bench, which is capable of generating controlled slip velocities, show that the sensor detects slip events in less than 50 ms. This response time is short enough for enabling future applications in the field of hand prosthetics.

Load-adaptive scaffold architecturing: a bioinspired approach to the design of porous additively manufactured scaffolds with optimized mechanical properties.

Computer-Aided Tissue Engineering (CATE) is based on a set of additive manufacturing techniques for the fabrication of patient-specific scaffolds, with geometries obtained from medical imaging. One of the main issues regarding the application of CATE concerns the definition of the internal architecture of the fabricated scaffolds, which, in turn, influences their porosity and mechanical strength. The present study envisages an innovative strategy for the fabrication of highly optimized structures, based on the a priori finite element analysis (FEA) of the physiological load set at the implant site. The resulting scaffold micro-architecture does not follow a regular geometrical pattern; on the contrary, it is based on the results of a numerical study. The algorithm was applied to a solid free-form fabrication process, using poly(ε-caprolactone) as the starting material for the processing of additive manufactured structures. A simple and intuitive geometry was chosen as a proof-of-principle application, on which finite element simulations and mechanical testing were performed. Then, to demonstrate the capability in creating mechanically biomimetic structures, the proximal femur subjected to physiological loading conditions was considered and a construct fitting a femur head portion was designed and manufactured.

Design of a rotary passive viscoelastic joint for wearable robots.

In the design of wearable robots that strictly interact with the human body and, in general, in any robotics application that involves the human component, the possibility of having modular joints able to produce a viscoelastic behaviour is very useful to achieve an efficient and safe human-robot interaction and to give rise to emergent dynamical behaviors. In this paper we propose the design of a compact, passive, rotary viscoelastic joint for assistive wearable robotics applications. The system integrates two functionally distinct sub-modules: one to render a desired torsional stiffness profile and the other to provide a desired torsional damping. Concepts and design choices regarding the overall architecture and the single components are presented and discussed. A viscoelastic model of the system has been developed and the design of the joint is presented.