Moving toward Soft Robotics: A Decade Review of the Design of Hand Exoskeletons

Modeling multi-contact point physical interaction between the anthropomorphic finger and soft robotic exo-digit for wearable rehabilitation robotics applications

Introduction: Effective control of rehabilitation robots requires considering the distributed and multi-contact point physical human-robot interaction and users' biomechanical variation. This paper presents a quasi-static model for the motion of a soft robotic exo-digit while physically interacting with an anthropomorphic finger model for physical therapy. Methods: Quasi-static analytical models were developed for modeling the motion of the soft robot, the anthropomorphic finger, and their coupled physical interaction. An intertwining of kinematics and quasi-static motion was studied to model the distributed (multiple contact points) interaction between the robot and a human finger model. The anthropomorphic finger was modeled as an articulated multi-rigid body structure with multi-contact point interaction. The soft robot was modeled as an articulated hybrid soft-and-rigid model with a constant bending curvature and a constant length for each soft segment. A hyperelastic constitute model based on Yeoh's 3rdorder material model was used for modeling the soft elastomer. The developed models were experimentally evaluated for 1) free motion of individual soft actuators and 2) constrained motion of the soft robotic exo-digit and anthropomorphic finger model. Results and Discussion: Simulation and experimental results were compared for performance evaluations. The theoretical and experimental results were in agreement for free motion, and the deviation from the constrained motion was in the range of the experimental errors. The outcomes also provided an insight into the importance of considering lengthening for the soft actuators.

Development of a novel hybrid securing actuator for a self-securing soft robotic hand exoskeleton

The development of soft robotic hand exoskeletons for rehabilitation has been well-reported in the literature, whereby the emphasis was placed on the development of soft actuators for flexion and extension. Little attention was focused on developing the glove interface and attachments of actuators to the hand. As these hand exoskeletons are largely developed for personnel with impaired hand function for rehabilitation, it may be tedious to aid the patients in donning and doffing the glove, given that patients usually have stiff fingers exhibiting high muscle tone. To address this issue, a hybrid securing actuator was developed and powered pneumatically to allow for rapid securing and release of a body segment. As a proof of concept, the actuator was further adapted into a self-securing glove mechanism and assembled into a complete self-securing soft robotic hand exoskeleton with the attachment of bidirectional actuators. Our validation tests show that the self-wearing soft robotic hand exoskeleton can easily conform and secure onto the human hand and assist with manipulation tasks.

Finger Kinematics during Human Hand Grip and Release

A bionic robotic hand can perform many movements similar to a human hand. However, there is still a significant gap in manipulation between robot and human hands. It is necessary to understand the finger kinematics and motion patterns of human hands to improve the performance of robotic hands. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hands of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a larger dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Additionally, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by the PIP joint. Regarding the finger sequence, the thumb started to move before the four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided a kinematic reference for the design of robotic hands and thus contributes to its development.

NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform

BACKGROUND

This article presents the system architecture and validation of the NeuroSuitUp body-machine interface (BMI). The platform consists of wearable robotics jacket and gloves in combination with a serious game application for self-paced neurorehabilitation in spinal cord injury and chronic stroke.

METHODS

The wearable robotics implement a sensor layer, to approximate kinematic chain segment orientation, and an actuation layer. Sensors consist of commercial magnetic, angular rate and gravity (MARG), surface electromyography (sEMG), and flex sensors, while actuation is achieved through electrical muscle stimulation (EMS) and pneumatic actuators. On-board electronics connect to a Robot Operating System environment-based parser/controller and to a Unity-based live avatar representation game. BMI subsystems validation was performed using exercises through a Stereoscopic camera Computer Vision approach for the jacket and through multiple grip activities for the glove. Ten healthy subjects participated in system validation trials, performing three arm and three hand exercises (each 10 motor task trials) and completing user experience questionnaires.

RESULTS

Acceptable correlation was observed in 23/30 arm exercises performed with the jacket. No significant differences in glove sensor data during actuation state were observed. No difficulty to use, discomfort, or negative robotics perception were reported.

CONCLUSIONS

Subsequent design improvements will implement additional absolute orientation sensors, MARG/EMG based biofeedback to the game, improved immersion through Augmented Reality and improvements towards system robustness.

Soft Robotic Glove with Sensing and Force Feedback for Rehabilitation in Virtual Reality

Many diseases, such as stroke, arthritis, and spinal cord injury, can cause severe hand impairment. Treatment options for these patients are limited by expensive hand rehabilitation devices and dull treatment procedures. In this study, we present an inexpensive soft robotic glove for hand rehabilitation in virtual reality (VR). Fifteen inertial measurement units are placed on the glove for finger motion tracking, and a motor-tendon actuation system is mounted onto the arm and exerts forces on fingertips via finger-anchoring points, providing force feedback to fingers so that the users can feel the force of a virtual object. A static threshold correction and complementary filter are used to calculate the finger attitude angles, hence computing the postures of five fingers simultaneously. Both static and dynamic tests are performed to validate the accuracy of the finger-motion-tracking algorithm. A field-oriented-control-based angular closed-loop torque control algorithm is adopted to control the force applied to the fingers. It is found that each motor can provide a maximum force of 3.14 N within the tested current limit. Finally, we present an application of the haptic glove in a Unity-based VR interface to provide the operator with haptic feedback while squeezing a soft virtual ball.

Study on Flexible sEMG Acquisition System and Its Application in Muscle Strength Evaluation and Hand Rehabilitation

Wearable devices based on surface electromyography (sEMG) to detect muscle activity can be used to assess muscle strength with the development of hand rehabilitation applications. However, conventional acquisition devices are usually complicated to operate and poorly comfortable for more medical and scientific application scenarios. Here, we report a flexible sEMG acquisition system that combines a graphene-based flexible electrode with a signal acquisition flexible printed circuit (FPC) board. Our system utilizes a polydimethylsiloxane (PDMS) substrate combined with graphene transfer technology to develop a flexible sEMG sensor. The single-lead sEMG acquisition system was designed and the FPC board was fabricated considering the requirements of flexible bending and twisting. We demonstrate the above design approach and extend this flexible sEMG acquisition system to applications for assessing muscle strength and hand rehabilitation training using a long- and short-term memory network training model trained to predict muscle strength, with 98.81% accuracy in the test set. The device exhibited good flexion and comfort characteristics. In general, the ability to accurately and imperceptibly monitor surface electromyography (EMG) signals is critical for medical professionals and patients.

Energy Harvesting for Robots with Adaptive Morphology

Robots primarily made of soft and elastic materials have potential applications such as traveling in confined spaces due to their adaptive morphology. However, their energy efficiency is still subject to improvement. Although a possible approach to increase efficiency is by harvesting the energy used during their behavioral motion, it is not trivial to do so due to their complex dynamics. This work seeks to pioneer a study that exploits the tight coupling between a robot's adaptive morphology, control, and consequent behaviors to harvest energy and increase energy efficiency. It is hypothesized that since varying the robot's morphology may change the energy use that leads to contrasting behavior and efficiency, harvesting the robot's energy will need to be adapted to its morphology. To verify the hypothesis, we developed a shape-changing robot with an elastic structure that achieves locomotion via vibration controlled by a single motor, such that the complex dynamics of the robot can be characterized through its resonance frequencies. It will be shown that harvesting energy at opportune occasions is more important than maximizing the harvest capacity to increase energy efficiency. We will also show how the robot's shape affects energy use in locomotion and how energy harvesting will feedback additional energy that increases the magnitude and affects the robot's behavior. We conclude with an understanding of the role of the robot's morphology, that is, shape, in using the energy provided to the robot and how the understanding can be used to harvest the robot's energy to increase its efficiency.

A wearable textile-based pneumatic energy harvesting system for assistive robotics

Wearable assistive, rehabilitative, and augmentative devices currently require bulky power supplies, often making these tools more of a burden than an asset. This work introduces a soft, low-profile, textile-based pneumatic energy harvesting system that extracts power directly from the foot strike of a user during walking. Energy is harvested with a textile pump integrated into the insole of the user's shoe and stored in a wearable textile bladder to operate pneumatic actuators on demand, with system performance optimized based on a mechano-fluidic model. The system recovered a maximum average power of nearly 3 W with over 20% conversion efficiency-outperforming electromagnetic, piezoelectric, and triboelectric alternatives-and was used to power a wearable arm-lift device that assists shoulder motion and a supernumerary robotic arm, demonstrating its capability as a lightweight, low-cost, and comfortable solution to support adults with upper body functional limitations in activities of daily living.

3D-Printed Soft Pneumatic Robotic Digit Based on Parametric Kinematic Model for Finger Action Mimicking

A robotic digit with shape modulation, allowing personalized and adaptable finger motions, can be used to restore finger functions after finger trauma or neurological impairment. A soft pneumatic robotic digit consisting of pneumatic bellows actuators as biomimetic artificial joints is proposed in this study to achieve specific finger motions. A parametric kinematic model is employed to describe the tip motion trajectory of the soft pneumatic robotic digit and guide the actuator parameter design (i.e., the pressure supply, actuator material properties, and structure requirements of the adopted pneumatic bellows actuators). The direct 3D printing technique is adopted in the fabrication process of the soft pneumatic robotic digit using the smart material of thermoplastic polyurethane. Each digit joint achieves different ranges of motion (ROM; bending angles of distal, proximal, and metacarpal joint are 107°, 101°, and 97°, respectively) under a low pressure of 30 kPa, which are consistent with the functional ROM of a human finger for performing daily activities. Theoretical model analysis and experiment tests are performed to validate the effectiveness of the digit parametric kinematic model, thereby providing evidence-based technical parameters for the precise control of dynamic pressure dosages to achieve the required motions.

Design of a compliant, stabilizing wrist mechanism for a pediatric hand exoskeleton

Children affected by hand impairment due to cerebral palsy or stroke experience serious difficulties when performing activities of daily life (ADL), which reduces their quality of life and development. Wearable robots such as hand exoskeletons have been proposed to support people with hand impairment in therapy as well as daily tasks. While numerous actuated wearable robots have been developed, few designs support both fingers and wrist function, despite being mutually relevant for reach-to-grasp tasks. A recent feasibility study investigating the use of PEXO, a lightweight and fully wearable pediatric hand exoskeleton, showed that a wrist fixed in a slightly extended position may limit the user's ability to reach and grasp during ADL and restrict the user group. These insights and further interactions with clinicians inspired a novel design of PEXO that features an additional degree of freedom in the wrist. In this paper, we present a compliant wrist mechanism extending the existing leaf spring finger mechanism of the device. The novel design provides both wrist motion capability of 60° in flexion and extension and wrist stabilization at the same time while actively supporting finger motion. Preliminary results suggest that the adjustability in the wrist enables a larger variety of grasping gestures. The implemented wrist support has the potential to allow for a more versatile use of PEXO and increase the potential target user group.

Soft robotics and functional electrical stimulation advances for restoring hand function in people with SCI: a narrative review, clinical guidelines and future directions

Background

Recovery of hand function is crucial for the independence of people with spinal cord injury (SCI). Wearable devices based on soft robotics (SR) or functional electrical stimulation (FES) have been employed to assist the recovery of hand function both during activities of daily living (ADLs) and during therapy. However, the implementation of these wearable devices has not been compiled in a review focusing on the functional outcomes they can activate/elicit/stimulate/potentiate. This narrative review aims at providing a guide both for engineers to help in the development of new technologies and for clinicians to serve as clinical guidelines based on the available technology in order to assist and/or recover hand function in people with SCI.

Methods

A literature search was performed in Scopus, Pubmed and IEEE Xplore for articles involving SR devices or FES systems designed for hand therapy or assistance, published since 2010. Only studies that reported functional outcomes from individuals with SCI were selected. The final collections of both groups (SR and FES) were analysed based on the technical aspects and reported functional outcomes.

Results

A total of 37 out of 1101 articles were selected, 12 regarding SR and 25 involving FES devices. Most studies were limited to research prototypes, designed either for assistance or therapy. From an engineering perspective, technological improvements for home-based use such as portability, donning/doffing and the time spent with calibration were identified. From the clinician point of view, the most suitable technical features (e.g., user intent detection) and assessment tools should be determined according to the particular patient condition. A wide range of functional assessment tests were adopted, moreover, most studies used non-standardized tests.

Conclusion

SR and FES wearable devices are promising technologies to support hand function recovery in subjects with SCI. Technical improvements in aspects such as the user intent detection, portability or calibration as well as consistent assessment of functional outcomes were the main identified limitations. These limitations seem to be be preventing the translation into clinical practice of these technological devices created in the laboratory.

Hand Rehabilitation Devices: A Comprehensive Systematic Review

A cerebrovascular accident, or a stroke, can cause significant neurological damage, inflicting the patient with loss of motor function in their hands. Standard rehabilitation therapy for the hand increases demands on clinics, creating an avenue for powered hand rehabilitation devices. Hand rehabilitation devices (HRDs) are devices designed to provide the hand with passive, active, and active-assisted rehabilitation therapy; however, HRDs do not have any standards in terms of development or design. Although the categorization of an injury's severity can guide a patient into seeking proper assistance, rehabilitation devices do not have a set standard to provide a solution from the beginning to the end stages of recovery. In this paper, HRDs are defined and compared by their mechanical designs, actuation mechanisms, control systems, and therapeutic strategies. Furthermore, devices with conducted clinical trials are used to determine the future development of HRDs. After evaluating the abilities of 35 devices, it is inferred that standard characteristics for HRDs should include an exoskeleton design, the incorporation of challenge-based and coaching therapeutic strategies, and the implementation of surface electromyogram signals (sEMG) based control.

Assessment of the Mechanical Support Characteristics of a Light and Wearable Robotic Exoskeleton Prototype Applied to Upper Limb Rehabilitation

Robotic exoskeletons are active devices that assist or counteract the movements of the body limbs in a variety of tasks, including in industrial environments or rehabilitation processes. With the introduction of textile and soft materials in these devices, the effective motion transmission, mechanical support of the limbs, and resistance to physical disturbances are some of the most desirable structural features. This paper proposes an evaluation protocol and assesses the mechanical support properties of a servo-controlled robotic exoskeleton prototype for rehabilitation in upper limbs. Since this prototype was built from soft materials, it is necessary to evaluate the mechanical behavior in the areas that support the arm. Some of the rehabilitation-supporting movements such as elbow flexion and extension, as well as increased muscle tone (spasticity), are emulated. Measurements are taken using the reference supplied to the system's control stage and then compared with an external high-precision optical tracking system. As a result, it is evidenced that the use of soft materials provides satisfactory outcomes in the motion transfer and support to the limb. In addition, this study lays the groundwork for a future assessment of the prototype in a controlled laboratory environment using human test subjects.

Bio-Inspired Control System for Fingers Actuated by Multiple SMA Actuators

Spiking neural networks are able to control with high precision the rotation and force of single-joint robotic arms when shape memory alloy wires are used for actuation. Bio-inspired robotic arms such as anthropomorphic fingers include more junctions that are actuated simultaneously. Starting from the hypothesis that the motor cortex groups the control of multiple muscles into neural synergies, this work presents for the first time an SNN structure that is able to control a series of finger motions by activation of groups of neurons that drive the corresponding actuators in sequence. The initial motion starts when a command signal is received, while the subsequent ones are initiated based on the sensors’ output. In order to increase the biological plausibility of the control system, the finger is flexed and extended by four SMA wires connected to the phalanges as the main tendons. The results show that the artificial finger that is controlled by the SNN is able to smoothly perform several motions of the human index finger while the command signal is active. To evaluate the advantages of using SNN, we compared the finger behaviours when the SMA actuators are driven by SNN, and by a microcontroller, respectively. In addition, we designed an electronic circuit that models the sensor’s output in concordance with the SNN output.

The Effect of the Degree of Freedom and Weight of the Hand Exoskeleton on Joint Mobility Function

This study aims to investigate the effects of the degree of freedom (DOF) and weight of the hand exoskeleton (HE) on hand joint mobility function (ease of movement, movement range) in fine hand use activities. A three-digit passive HE prototype was built to fit each of the 12 participants. Two DOF setups (three DOF, two DOF), two digits’ weight levels (70 g, 140 g), and barehand conditions were tested. A productivity task (performed with Standardized-Nine Hole Peg Test) and motion tasks, both performing the tip pinch and tripod pinch, were conducted to measure the task completion time and the range of motion (ROM) of the digit joints, respectively, using a motion capture system. The perceived ease rating was also measured. The results showed that DOF reduction and weight addition caused a significant task completion time increase and rating drop (p < 0.05). Meanwhile, the DOF reduction increased the ROM reduction of the proximal interphalangeal joints; however, the weight addition caused a correction of the ROM reduction of several joints (p < 0.05) at the tripod pinch. In conclusion, wearing an HE reduces hand joint mobility, especially in lower DOF. However, a certain weight addition may improve joint mobility in terms of the fingers’ movement range.

Design and Prototyping of an Underactuated Hand Exoskeleton With Fingers Coupled by a Gear-Based Differential

Exoskeletons and more in general wearable mechatronic devices represent a promising opportunity for rehabilitation and assistance to people presenting with temporary and/or permanent diseases. However, there are still some limits in the diffusion of robotic technologies for neuro-rehabilitation, notwithstanding their technological developments and evidence of clinical effectiveness. One of the main bottlenecks that constrain the complexity, weight, and costs of exoskeletons is represented by the actuators. This problem is particularly evident in devices designed for the upper limb, and in particular for the hand, in which dimension limits and kinematics complexity are particularly challenging. This study presents the design and prototyping of a hand finger exoskeleton. In particular, we focus on the design of a gear-based differential mechanism aimed at coupling the motion of two adjacent fingers and limiting the complexity and costs of the system. The exoskeleton is able to actuate the flexion/extension motion of the fingers and apply bidirectional forces, that is, it is able to both open and close the fingers. The kinematic structure of the finger actuation system has the peculiarity to present three DoFs when the exoskeleton is not worn and one DoF when it is worn, allowing better adaptability and higher wearability. The design of the gear-based differential is inspired by the mechanism widely used in the automotive field; it allows actuating two fingers with one actuator only, keeping their movements independent.

Processing of Self-Healing Polymers for Soft Robotics

Soft robots are, due to their softness, inherently safe and adapt well to unstructured environments. However, they are prone to various damage types. Self-healing polymers address this vulnerability. Self-healing soft robots can recover completely from macroscopic damage, extending their lifetime. For developing healable soft robots, various formative and additive manufacturing methods have been exploited to shape self-healing polymers into complex structures. Additionally, several novel manufacturing techniques, noted as (re)assembly binding techniques that are specific to self-healing polymers, have been created. Herein, the wide variety of processing techniques of self-healing polymers for robotics available in the literature is reviewed, and limitations and opportunities discussed thoroughly. Based on defined requirements for soft robots, these techniques are critically compared and validated. A strong focus is drawn to the reversible covalent and (physico)chemical cross-links present in the self-healing polymers that do not only endow healability to the resulting soft robotic components, but are also beneficial in many manufacturing techniques. They solve current obstacles in soft robots, including the formation of robust multi-material parts, recyclability, and stress relaxation. This review bridges two promising research fields, and guides the reader toward selecting a suitable processing method based on a self-healing polymer and the intended soft robotics application.

Effect of proprioceptive stimulation using a soft robotic glove on motor activation and brain connectivity in stroke survivors

OBJECTIVE

Soft-robotic-assisted training may improve motor function during post-stroke recovery, but the underlying physiological changes are not clearly understood. We applied a single-session of intensive proprioceptive stimulation to stroke survivors using a soft robotic glove to delineate its short-term influence on brain functional activity and connectivity.

APPROACH

In this study, we utilized task-based and resting-state functional magnetic resonance imaging (fMRI) to characterize the changes in different brain networks following a soft robotic intervention. Nine stroke patients with hemiplegic upper limb engaged in resting-state and motor-task fMRI. The motor tasks comprised two conditions: active movement of fingers (active task) and glove-assisted active movement using a robotic glove (glove-assisted task), both with visual instruction. Each task was performed using bilateral hands simultaneously or the affected hand only. The same set of experiments was repeated following a 30-minute treatment of continuous passive motion (CPM) using a robotic glove.

MAIN RESULTS

On simultaneous bimanual movement, increased activation of supplementary motor area (SMA) and primary motor area (M1) were observed after CPM treatment compared to the pre-treatment condition, both in active and glove-assisted task. However, when performing the tasks solely using the affected hand, the phenomena of increased activity were not observed either in active or glove-assisted task. The comparison of the resting-state fMRI between before and after CPM showed the connectivity of the supramarginal gyrus and SMA was increased in the somatosensory network and salience network.

SIGNIFICANCE

This study demonstrates how passive motion exercise activates M1 and SMA in the post-stroke brain. The effective proprioceptive motor integration seen in bimanual exercise in contrast to the unilateral affected hand exercise suggests that the unaffected hemisphere might reconfigure connectivity to supplement damaged neural networks in the affected hemisphere. The somatosensory modulation rendered by the intense proprioceptive stimulation would affect the motor learning process in stroke survivors.

Biomimetic Artificial Joints Based on Multi-Material Pneumatic Actuators Developed for Soft Robotic Finger Application

To precisely achieve a series of daily finger bending motions, a soft robotic finger corresponding to the anatomical range of each joint was designed in this study with multi-material pneumatic actuators. The actuator as a biomimetic artificial joint was developed on the basis of two composite materials of different shear modules, and the pneumatic bellows as expansion parts was restricted by frame that made from polydimethylsiloxane (PDMS). A simplified mathematical model was used for the bending mechanism description and provides guidance for the multi-material pneumatic actuator fabrication (e.g., stiffness and thickness) and structural design (e.g., cross length and chamber radius), as well as the control parameter optimization (e.g., the air pressure supply). An actuation pressure of over 70 kPa is required by the developed soft robotic finger to provide a full motion range (MCP = 36°, PIP = 114°, and DIP = 75°) for finger action mimicking. In conclusion, a multi-material pneumatic actuator was designed and developed for soft robotic finger application and theoretically and experimentally demonstrated its feasibility in finger action mimicking. This study explored the mechanical properties of the actuator and could provide evidence-based technical parameters for pneumatic robotic finger design and precise control of its dynamic air pressure dosages in mimicking actions. Thereby, the conclusion was supported by the results theoretically and experimentally, which also aligns with our aim to design and develop a multi-material pneumatic actuator as a biomimetic artificial joint for soft robotic finger application.

A Compact and Lightweight Rehabilitative Exoskeleton to Restore Grasping Functions for People with Hand Paralysis

Millions of individuals suffer from upper extremity paralysis caused by neurological disorders including stroke, traumatic brain injury, or spinal cord injury. Robotic hand exoskeletons can substitute the missing motor control and help restore the functions in daily operations. However, most of the hand exoskeletons are bulky, stationary, and cumbersome to use. We have modified a recent existing design (Tenoexo) to prototype a motorized, lightweight, fully wearable rehabilitative hand exoskeleton by combining rigid parts with a soft mechanism capable of producing various grasps needed for the execution of daily tasks. Mechanical evaluation of our exoskeleton showed that it can produce fingertip force up to 8 N and can cover 91.5° of range of motion in just 3 s. We further tested the performance of the developed robotic exoskeleton in two quadriplegics with chronic hand paralysis and observed immediate success on independent grasping of different daily objects. The results suggested that our exoskeleton is a viable option for hand function assistance, allowing patients to regain lost finger control for everyday activities.

Robotic devices for paediatric rehabilitation: a review of design features

Children with physical disabilities often have limited performance in daily activities, hindering their physical development, social development and mental health. Therefore, rehabilitation is essential to mitigate the adverse effects of the different causes of physical disabilities and improve independence and quality of life. In the last decade, robotic rehabilitation has shown the potential to augment traditional physical rehabilitation. However, to date, most robotic rehabilitation devices are designed for adult patients who differ in their needs compared to paediatric patients, limiting the devices' potential because the paediatric patients' needs are not adequately considered. With this in mind, the current work reviews the existing literature on robotic rehabilitation for children with physical disabilities, intending to summarise how the rehabilitation robots could fulfil children's needs and inspire researchers to develop new devices. A literature search was conducted utilising the Web of Science, PubMed and Scopus databases. Based on the inclusion-exclusion criteria, 206 publications were included, and 58 robotic devices used by children with a physical disability were identified. Different design factors and the treated conditions using robotic technology were compared. Through the analyses, it was identified that weight, safety, operability and motivation were crucial factors to the successful design of devices for children. The majority of the current devices were used for lower limb rehabilitation. Neurological disorders, in particular cerebral palsy, were the most common conditions for which devices were designed. By far, the most common actuator was the electric motor. Usually, the devices present more than one training strategy being the assistive strategy the most used. The admittance/impedance method is the most popular to interface the robot with the children. Currently, there is a trend on developing exoskeletons, as they can assist children with daily life activities outside of the rehabilitation setting, propitiating a wider adoption of the technology. With this shift in focus, it appears likely that new technologies to actuate the system (e.g. serial elastic actuators) and to detect the intention (e.g. physiological signals) of children as they go about their daily activities will be required.

Soft Exoskeletons: Development, Requirements, and Challenges of the Last Decade

In this article, various investigations on soft exoskeletons are presented and their functional and structural characteristics are analyzed. The present work is oriented to the studies of the last decade and covers the upper and lower joints, specifically the shoulder, elbow, wrist, hand, hip, knee, and ankle. Its functionality, applicability, and main characteristics are exposed, such as degrees of freedom, force, actuators, power transmission methods, control systems, and sensors. The purpose of this work is to show the current trend in the development of soft exoskeletons, in addition to specifying the essential characteristics that must be considered in its design and the challenges that its construction implies.

A prototype characterization of ExoFinger, a finger exoskeleton

This article presents an experimental characterization of ExoFinger, a finger exoskeleton for finger motion assistance. The exoskeletal device is analyzed in experimental lab activities that have been conducted with different users to characterize the operation performance and to demonstrate the adaptability of the proposed device. The behavior of this device is characterized in detail using sensors to measure finger motion and power consumption. Sensor measures also demonstrate the given motion assistance performance in terms of an electrical finger response and finger temperature by resulting in an efficient solution with a large motion range of a finger in assistance of recovering finger motion.

Soft pneumatic elbow exoskeleton reduces the muscle activity, metabolic cost and fatigue during holding and carrying of loads

To minimize fatigue, sustain workloads, and reduce the risk of injuries, the exoskeleton Carry was developed. Carry combines a soft human-machine interface and soft pneumatic actuation to assist the elbow in load holding and carrying. We hypothesize that the assistance of Carry would decrease, muscle activity, net metabolic rate, and fatigue. With Carry providing 7.2 Nm of assistance, we found reductions of up to 50% for the muscle activity, up to 61% for the net metabolic rate, and up to 99% for fatigue in a group study of 12 individuals. Analyses of operation dynamics and autonomous use demonstrate the applicability of Carry to a variety of use cases, presumably with increased benefits for increased assistance torque. The significant benefits of Carry indicate this device could prevent systemic, aerobic, and/or possibly local muscle fatigue that may increase the risk of joint degeneration and pain due to lifting, holding, or carrying.

Mechanical Design and Analysis of the End-Effector Finger Rehabilitation Robot (EFRR) for Stroke Patients

Most existing finger rehabilitation robots are structurally complex and cannot be adapted to multiple work conditions, such as clinical and home. In addition, there is a lack of attention to active adduction/abduction (A/A) movement, which prevents stroke patients from opening the joint in time and affects the rehabilitation process. In this paper, an end-effector finger rehabilitation robot (EFRR) with active A/A motion that can be applied to a variety of applications is proposed. First, the natural movement curve of the finger is analyzed, which is the basis of the mechanism design. Based on the working principle of the cam mechanism, the flexion/extension (F/E) movement module is designed and the details used to ensure the safety and reliability of the device are introduced. Then, a novel A/A movement module is proposed, using the components that can easily individualized design to achieve active A/A motion only by one single motor, which makes up for the shortcomings of the existing devices. As for the control system, a fuzzy proportional-derivative (PD) adaptive impedance control strategy based on the position information is proposed, which can make the device more compliant, avoid secondary injuries caused by excessive muscle tension, and protect the fingers effectively. Finally, some preliminary experiments of the prototype are reported, and the results shows that the EFRR has good performance, which lays the foundation for future work.

Motor Training Using Mental Workload (MWL) With an Assistive Soft Exoskeleton System: A Functional Near-Infrared Spectroscopy (fNIRS) Study for Brain-Machine Interface (BMI)

Mental workload is a neuroergonomic human factor, which is widely used in planning a system's safety and areas like brain-machine interface (BMI), neurofeedback, and assistive technologies. Robotic prosthetics methodologies are employed for assisting hemiplegic patients in performing routine activities. Assistive technologies' design and operation are required to have an easy interface with the brain with fewer protocols, in an attempt to optimize mobility and autonomy. The possible answer to these design questions may lie in neuroergonomics coupled with BMI systems. In this study, two human factors are addressed: designing a lightweight wearable robotic exoskeleton hand that is used to assist the potential stroke patients with an integrated portable brain interface using mental workload (MWL) signals acquired with portable functional near-infrared spectroscopy (fNIRS) system. The system may generate command signals for operating a wearable robotic exoskeleton hand using two-state MWL signals. The fNIRS system is used to record optical signals in the form of change in concentration of oxy and deoxygenated hemoglobin (HbO and HbR) from the pre-frontal cortex (PFC) region of the brain. Fifteen participants participated in this study and were given hand-grasping tasks. Two-state MWL signals acquired from the PFC region of the participant's brain are segregated using machine learning classifier-support vector machines (SVM) to utilize in operating a robotic exoskeleton hand. The maximum classification accuracy is 91.31%, using a combination of mean-slope features with an average information transfer rate (ITR) of 1.43. These results show the feasibility of a two-state MWL (fNIRS-based) robotic exoskeleton hand (BMI system) for hemiplegic patients assisting in the physical grasping tasks.

A Review of Active Hand Exoskeletons for Rehabilitation and Assistance

Disabilities are a global issue due to the decrease in life quality and mobility of patients, especially people suffering from hand disabilities. This paper presents a review of active hand exoskeleton technologies, over the past decade, for rehabilitation, assistance, augmentation, and haptic devices. Hand exoskeletons are still an active research field due to challenges that engineers face and are trying to solve. Each hand exoskeleton has certain requirements to fulfil to achieve their aims. These requirements have been extracted and categorized into two sections: general and specific, to give a common platform for developing future devices. Since this is still a developing area, the requirements are also shaped according to the advances in the field. Technical challenges, such as size requirements, weight, ergonomics, rehabilitation, actuators, and sensors are all due to the complex anatomy and biomechanics of the hand. The hand is one of the most complex structures in the human body; therefore, to understand certain design approaches, the anatomy and biomechanics of the hand are addressed in this paper. The control of these devices is also an arising challenge due to the implementation of intelligent systems and new rehabilitation techniques. This includes intention detection techniques (electroencephalography (EEG), electromyography (EMG), admittance) and estimating applied assistance. Therefore, this paper summarizes the technology in a systematic approach and reviews the state of the art of active hand exoskeletons with a focus on rehabilitation and assistive devices.

Learning Optimal Fin-Ray Finger Design for Soft Grasping

The development of soft hands is an important progress to empower robotic grasping with passive compliance while greatly decreasing the complexity of control. Despite the advances during the past decades, it is still not clear how to design optimal hands or fingers given the task requirements. In this paper, we propose a framework to learn the optimal design parameter for a fin-ray finger in order to achieve stable grasping. First, the pseudo-kinematics of the soft finger is learned in simulation. Second, the task constraints are encoded as a combination of desired grasping force and the empirical grasping quality function in terms of winding number. Finally, the effectiveness of the proposed approach is validated with experiments in simulation and using real-world examples as well.

A functional assembly framework based on implementable neurobionic material

Neurobionic material is an emerging field in material and translational science. For material design, much focus has already been transferred from von Neumann architecture to the neuromorphic framework. As it is impractical to reconstruct the real neural tissue solely from materials, it is necessary to develop a feasible neurobionics framework to realize advanced brain function. In this study, we proposed a mathematical neurobionic material model, and attempted to explore advanced function only by simple and feasible structures. Here an equivalent simplified framework was used to describe the dynamics expressed in an equation set, while in vivo study was performed to verify simulation results. In neural tissue, the output of neurobionic material was characterized by spike frequency, and the stability is based on the excitatory/inhibitory proportion. Spike frequency in mathematical neurobionic material model can spontaneously meet the solution of a nonlinear equation set. Assembly can also evolve into a certain distribution under different stimulations, closely related to decision making. Short-term memory can be formed by coupling neurobionic material assemblies. In vivo experiments further confirmed predictions in our mathematical neurobionic material model. The property of this neural biomimetic material model demonstrates its intrinsic neuromorphic computational ability, which should offer promises for implementable neurobionic device design.

An Exoneuromusculoskeleton for Self-Help Upper Limb Rehabilitation After Stroke

This article presents a novel electromyography (EMG)-driven exoneuromusculoskeleton that integrates the neuromuscular electrical stimulation (NMES), soft pneumatic muscle, and exoskeleton techniques, for self-help upper limb training after stroke. The developed system can assist the elbow, wrist, and fingers to perform sequential arm reaching and withdrawing tasks under voluntary effort control through EMG, with a lightweight, compact, and low-power requirement design. The pressure/torque transmission properties of the designed musculoskeletons were quantified, and the assistive capability of the developed system was evaluated on patients with chronic stroke (n = 10). The designed musculoskeletons exerted sufficient mechanical torque to support joint extension for stroke survivors. Compared with the limb performance when no assistance was provided, the limb performance (measured as the range of motion in joint extension) significantly improved when mechanical torque and NMES were provided (p < 0.05). A pilot trial was conducted on patients with chronic stroke (n = 15) to investigate the feasibility of using the developed system in self-help training and the rehabilitation effects of the system. All the participants completed the self-help device-assisted training with minimal professional assistance. After a 20-session training, significant improvements were noted in the voluntary motor function and release of muscle spasticity at the elbow, wrist, and fingers, as indicated by the clinical scores (p < 0.05). The EMG parameters (p < 0.05) indicated that the muscular coordination of the entire upper limb improved significantly after training. The results suggested that the developed system can effectively support self-help upper limb rehabilitation after stroke. ClinicalTrials.gov Register Number NCT03752775.

Preliminary Results in Testing of a Novel Asymmetric Underactuated Robotic Hand Exoskeleton for Motor Impairment Rehabilitation

Robotic exoskeletons are a trending topic in both robotics and rehabilitation therapy. The research presented in this paper is a summary of robotic exoskeleton development and testing for a human hand, having application in motor rehabilitation treatment. The mechanical design of the robotic hand exoskeleton implements a novel asymmetric underactuated system and takes into consideration a number of advantages and disadvantages that arose in the literature in previous mechanical design, regarding hand exoskeleton design and also aspects related to the symmetric and asymmetric geometry and behavior of the biological hand. The technology used for the manufacturing and prototyping of the mechanical design is 3D printing. A comprehensive study of the exoskeleton has been done with and without the wearer’s hand in the exoskeleton, where multiple feedback sources are used to determine symmetric and asymmetric behaviors related to torque, position, trajectory, and laws of motion. Observations collected during the experimental testing proved to be valuable information in the field of augmenting the human body with robotic devices.

Upper Limb Bionic Orthoses: General Overview and Forecasting Changes

Using robotics in modern medicine is slowly becoming a common practice. However, there are still important life science fields which are currently devoid of such advanced technology. A noteworthy example of a life sciences field which would benefit from process automation and advanced robotic technology is rehabilitation of the upper limb with the use of an orthosis. Here, we present the state-of-the-art and prospects for development of mechanical design, actuator technology, control systems, sensor systems, and machine learning methods in rehabilitation engineering. Moreover, current technical solutions, as well as forecasts on improvement, for exoskeletons are presented and reviewed. The overview presented might be the cornerstone for future research on advanced rehabilitation engineering technology, such as an upper limb bionic orthosis.

Joint Angle Estimation of a Tendon-Driven Soft Wearable Robot through a Tension and Stroke Measurement

The size of a device and its adaptability to human properties are important factors in developing a wearable device. In wearable robot research, therefore, soft materials and tendon transmissions have been utilized to make robots compact and adaptable to the human body. However, when used for wearable robots, these methods sometimes cause uncertainties that originate from elongation of the soft material or from undefined human properties. In this research, to consider these uncertainties, we propose a data-driven method that identifies both kinematic and stiffness parameters using tension and wire stroke of the actuators. Through kinematic identification, a method is proposed to find the exact joint position as a function of the joint angle. Through stiffness identification, the relationship between the actuation force and the joint angle is obtained using Gaussian Process Regression (GPR). As a result, by applying the proposed method to a specific robot, the research outlined in this paper verifies how the proposed method can be used in wearable robot applications. This work examines a novel wearable robot named Exo-Index, which assists a human’s index finger through the use of three actuators. The proposed identification methods enable control of the wearable robot to result in appropriate postures for grasping objects of different shapes and sizes.

Review of the effects of soft robotic gloves for activity-based rehabilitation in individuals with reduced hand function and manual dexterity following a neurological event

Despite limited scientific evidence, there is an increasing interest in soft robotic gloves to optimize hand- and finger-related functional abilities following a neurological event. This review maps evidence on the effects and effectiveness of soft robotic gloves for hand rehabilitation and, whenever possible, patients' satisfaction. A systematized search of the literature was conducted using keywords structured around three areas: technology attributes, anatomy, and rehabilitation. A total of 272 titles, abstracts, and keywords were initially retrieved, and data were extracted out of 13 articles. Six articles investigated the effects of wearing a soft robotic glove and eight studied the effect or effectiveness of an intervention with it. Some statistically significant and meaningful beneficial effects were confirmed with the 29 outcome measures used. Finally, 11 articles also confirmed users' satisfaction with regard to the soft robotic glove, while some articles also noticed an increased engagement in the rehabilitation program with this technology. Despite the heterogeneity across studies, soft robotic gloves stand out as a safe and promising technology to improve hand- and finger-related dexterity and functional performance. However, strengthened evidence of the effects or effectiveness of such devices is needed before their transition from laboratory to clinical practice.

Soft sensors for a sensing-actuation system with high bladder voiding efficiency

Sensing-actuation systems can assist a bladder with lost sensation and weak muscle control. Here, we advance the relevant technology by integrating a soft and thin capacitive sensor with a shape memory alloy-based actuator to achieve a high-performance closed-loop configuration. In our design, sensors capable of continuous bladder volume detection and actuators with strong emptying force have been used. This integration has previously hindered performance due to large bladder volume changes. Our solution integrates sensing-actuation elements that are bladder compatible but do not interfere with one another, achieving real-time bladder management. The system attains a highly desirable voiding target of 71 to 100% of a rat's bladder with a volume sensitivity of 0.7 μF/liter. Our system represents an efficient voiding solution that avoids overfilling and represents a technological solution to bladder impairment treatment, serving as a model for similar soft sensor-actuator integration with other organs.

A pilot study on the design and validation of a hybrid exoskeleton robotic device for hand rehabilitation

STUDY DESIGN

An iterative design process was used to obtain design parameters that satisfy both kinematic and dynamic requirements for the hand exoskeleton. This design was validated through experimental studies.

INTRODUCTION

The success of hand rehabilitation after impairments depends on the timing, intensity, repetition, and frequency, as well as task-specific training. Considering the continuing constraints placed on therapist-led rehabilitation and need for better outcomes, robot-assisted rehabilitation has been explored. Soft robotic approaches have been implemented for a hand rehabilitation exoskeleton as they have more tolerance for alignment with biological joints than those of hard exoskeletons.

PURPOSE OF THE STUDY

The purpose of the study was to design, develop, and validate a soft robotic exoskeleton for hand rehabilitation.

METHODS

A motion capture system validated the kinematics of the soft robotic digit attached on top of a human index finger. A pneumatic control system and algorithms were developed to operate the exoskeleton based on three therapeutic modes: continuous passive, active assistive, and active resistive motion. Pilot studies were carried out on one healthy and one poststroke participant using continuous passive motion and bilateral/bimanual therapy modes.

RESULTS

The soft robotic digits were able to produce required range of motion and accommodate for dorsal lengthening, with trajectories of the center of rotation of the soft robotic joints in close agreement with the center of rotation of the human finger joints.

DISCUSSION

The exoskeleton showed the robust performance of the robot in applying continuous passive motion and bilateral/bimanual therapy.

CONCLUSIONS

This soft robotic exoskeleton is promising for assisting in the rehabilitation of the hand.

Identification of the best strategy to command variable stiffness using electromyographic signals

OBJECTIVE

In the last decades, many EMG-controlled robotic devices were developed. Since stiffness control may be required to perform skillful interactions, different groups developed devices whose stiffness is real-time controlled based on EMG signal samples collected from the operator. However, this control strategy may be fatiguing. In this study, we proposed and experimentally validated a novel stiffness control strategy, based on the average muscle co-contraction estimated from EMG samples collected in the previous 1 or 2 s.

APPROACH

Nine subjects performed a tracking task with their right wrist in five different sessions. In four sessions a haptic device (Hi-5) applied a sinusoidal perturbing torque. In Baseline session, co-contraction reduced the effect of the perturbation only by stiffening the wrist. In contrast, during aided sessions the perturbation amplitude was also reduced (mimicking the effect of additional stiffening provided by EMG-driven robotic device) either proportionally to the co-contraction exerted by the subject sample-by-sample (Proportional), or according to the average co-contraction exerted in the previous 1 s (Integral 1s), or 2 s (Integral 2s). Task error, metabolic cost during the tracking task, perceived fatigue, and the median EMG frequency calculated during a sub-maximal isometric torque generation tasks that alternated with the tracking were compared across sessions.

MAIN RESULTS

Positive effects of the reduction of the perturbation provided by co-contraction estimation was identified in all the investigated variables. Integral 1s session showed lower metabolic cost with respect to the Proportional session, and lower perceived fatigue with respect to both the Proportional and the Integral 2s sessions.

SIGNIFICANCE

This study's results showed that controlling the stiffness of an EMG-driven robotic device proportionally to the operator's co-contraction, averaged in the previous 1 s, represents the best control strategy because it required less metabolic cost and led to a lower perceived fatigue.

Myoelectric Control of a Soft Hand Exoskeleton Using Kinematic Synergies

Soft hand exoskeletons offer a lightweight, low-profile alternative to rigid rehabilitative robotic systems, enabling their use to restore activities of daily living (ADL) in those with hand paresis due to stroke or other conditions. The hand exoskeleton with embedded synergies (HEXOES) is a soft cable-driven hand exoskeleton capable of independently actuating and sensing 10 degrees of freedom (DoF) of the hand. Control of the 10 DoF exoskeleton is dimensionally reduced using three manually defined synergies in software corresponding to thumb, index, and 3-finger flexion and extension. In this paper, five healthy subjects control HEXOES using a neural network which decodes synergy weights from contralateral electromyography (EMG) activity. The three synergies are manipulated in real time to grasp and lift 15 ADL objects of various sizes and weights. The neural network's training and validation mean squared error, object grasp time, and grasp success rate were measured for five healthy subjects. The final training error of the neural network was 4.8 ± 1.8% averaged across subjects and tasks, with 8.3 ± 3.4% validation error. The time to reach, grasp, and lift an object was 11.15 ± 4.35 s on average, with an average success rate of 66.7% across all objects. The complete system demonstrates real time use of biosignals and machine learning to allow subjects to operate kinematic synergies to grasp objects using a wearable hand exoskeleton. Future work and applications are further discussed, including possible design improvements and enrollment of individuals with stroke.

The Sparthan Three-Dimensional Printed Exo-Glove: A Preliminary Evaluation of Performance Via Case Study

This paper describes the development and testing of a low-cost three-dimensional (3D) printed wearable hand exoskeleton to assist people with limited finger mobility and grip strength. The function of the presented orthosis is to support and enable light intensity activities of daily living and improve the ability to grasp and hold objects. The Sparthan Exoskeleton prototype utilizes a cable-driven design applied to individual digits with motors. The initial prototype is presented in this paper along with a preliminary evaluation of durability and performance efficacy.

Soft Robotics

In Nature, the adaptability of many organisms and their capability to survive in challenging and dynamically changing environments are closely linked to their characteristics and the morphology of their body parts [...].