Design of a Soft Robotic Elbow Sleeve with Passive and Intent-Controlled Actuation

Soft Artificial Muscle Based on Pre-Detwinned Shape Memory Alloy Spring Actuator Achieving High Passive Assistive Torque for Wearable Robot

For designing the assistive wearable rehabilitation robots, it is challenging to design the robot as energy efficient because the actuators have to be capable of overcoming human loads such as gravity of the body and spastic torque continuously during the assistance. To address these challenges, we propose a novel design of soft artificial muscle that utilizes shape memory alloy (SMA) spring actuators with pre-detwinning process. The SMA spring was fabricated through a process called pre-detwinning, which enhances the linearity of the SMA spring in martensite phase and unpowered restoring force, which is called passive force. The fabricated SMA spring can contract >60%. Finally, the soft wearable robot that can assist not only the gravitational torque exerted on the elbow by passive force, but also the elbow movements with active force was designed with a soft artificial muscle. A soft artificial muscle consists of the bundles of pre-detwinned SMA springs integrated with the stretchable coolant vessel. The stiffness of the muscle was measured as 1125 N/m in martensite phase and 1732 N/m in austenite phase. In addition, the muscle showed great actuation frequency performances, the bandwidth of which was measured as 0.5 Hz. The proposed wearable mechanism can fully compensate the gravitational torque for all the angles in passive mode. In addition, the proposed mechanism can produce high torque up to 3.5 Nm and movements in active mode.

Favoring the cognitive-motor process in the closed-loop of BCI mediated post stroke motor function recovery: challenges and approaches

The brain-computer interface (BCI)-mediated rehabilitation is emerging as a solution to restore motor skills in paretic patients after stroke. In the human brain, cortical motor neurons not only fire when actions are carried out but are also activated in a wired manner through many cognitive processes related to movement such as imagining, perceiving, and observing the actions. Moreover, the recruitment of motor cortexes can usually be regulated by environmental conditions, forming a closed-loop through neurofeedback. However, this cognitive-motor control loop is often interrupted by the impairment of stroke. The requirement to bridge the stroke-induced gap in the motor control loop is promoting the evolution of the BCI-based motor rehabilitation system and, notably posing many challenges regarding the disease-specific process of post stroke motor function recovery. This review aimed to map the current literature surrounding the new progress in BCI-mediated post stroke motor function recovery involved with cognitive aspect, particularly in how it refired and rewired the neural circuit of motor control through motor learning along with the BCI-centric closed-loop.

Air Efficient Soft Wearable Robot for High-Torque Elbow Flexion Assistance

Recent developments in soft wearable robots have shown promise for assistive and rehabilitative use-cases. For inflatable approaches, a major challenge in developing portable systems is finding a balance between portability, performance, and usability. In this paper, we present a textile-based robotic sleeve that can provide functional elbow flexion assistance and is compatible with a portable actuation unit (PAU). Flexion is driven by a curved textile actuator with internal pneumatic supports (IPS). We show that the addition of IPS improves torque generation and increases battery-powered actuations by 60%. We demonstrate that the device can provide enough torque throughout the ROM of the elbow joint for daily life assistance. Specifically, the device generates 13.5 Nm of torque at 90°. Experimental testing in five healthy individuals and two individuals with Amyotrophic Lateral Sclerosis (ALS) demonstrates its impact on wearer muscle activity and kinematics. The results with healthy subjects show that the device was able to reduce the bicep muscle activity by an average of 49.1±13.3% during static and dynamic exercises, 43.6±11.1% during simulated ADLs, and provided an assisted ROM of 134°±13°. Both ALS participants reported a reduced rate of perceived exertion during both static and dynamic tasks while wearing the device and had an average ROM of 115°±8°. Future work will explore other applications of the IPS and extend the approach to assisting multiple joints.

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.

Upper limb soft robotic wearable devices: a systematic review

INTRODUCTION

Soft robotic wearable devices, referred to as exosuits, can be a valid alternative to rigid exoskeletons when it comes to daily upper limb support. Indeed, their inherent flexibility improves comfort, usability, and portability while not constraining the user's natural degrees of freedom. This review is meant to guide the reader in understanding the current approaches across all design and production steps that might be exploited when developing an upper limb robotic exosuit.

METHODS

The literature research regarding such devices was conducted in PubMed, Scopus, and Web of Science. The investigated features are the intended scenario, type of actuation, supported degrees of freedom, low-level control, high-level control with a focus on intention detection, technology readiness level, and type of experiments conducted to evaluate the device.

RESULTS

A total of 105 articles were collected, describing 69 different devices. Devices were grouped according to their actuation type. More than 80% of devices are meant either for rehabilitation, assistance, or both. The most exploited actuation types are pneumatic (52%) and DC motors with cable transmission (29%). Most devices actuate 1 (56%) or 2 (28%) degrees of freedom, and the most targeted joints are the elbow and the shoulder. Intention detection strategies are implemented in 33% of the suits and include the use of switches and buttons, IMUs, stretch and bending sensors, EMG and EEG measurements. Most devices (75%) score a technology readiness level of 4 or 5.

CONCLUSION

Although few devices can be considered ready to reach the market, exosuits show very high potential for the assistance of daily activities. Clinical trials exploiting shared evaluation metrics are needed to assess the effectiveness of upper limb exosuits on target users.

Assisting Forearm Function in Children With Movement Disorders via A Soft Wearable Robot With Equilibrium-Point Control

Wearable robots are envisioned to amplify the independence of people with movement impairments by providing daily physical assistance. For portable, comfortable, and safe devices, soft pneumatic-based robots are emerging as a potential solution. However, due to the inherent complexities, including compliance and nonlinear mechanical behavior, feedback control for facilitating human–robot interaction remains a challenge. Herein, we present the design, fabrication, and control architecture of a soft wearable robot that assists in supination and pronation of the forearm. The soft wearable robot integrates an antagonistic pair of pneumatic-based helical actuators to provide active pronation and supination torques. Our main contribution is a bio-inspired equilibrium-point control scheme for integrating proprioceptive feedback and exteroceptive input (e.g., the user’s muscle activation signals) directly with the on/off valve behavior of the soft pneumatic actuators. The proposed human–robot controller is directly inspired by the equilibrium-point hypothesis of motor control, which suggests that voluntary movements arise through shifts in the equilibrium state of the antagonistic muscle pair spanning a joint. We hypothesized that the proposed method would reduce the required effort during dynamic manipulation without affecting the error. In order to evaluate our proposed method, we recruited seven pediatric participants with movement disorders to perform two dynamic interaction tasks with a haptic manipulandum. Each task required the participant to track a sinusoidal trajectory while the haptic manipulandum behaved as a Spring-Dominate system or Inertia-Dominate system. Our results reveal that the soft wearable robot, when active, reduced user effort on average by 14%. This work demonstrates the practical implementation of an equilibrium-point volitional controller for wearable robots and provides a foundational path toward versatile, low-cost, and soft wearable robots.

Intention Detection Strategies for Robotic Upper-Limb Orthoses: A Scoping Review Considering Usability, Daily Life Application, and User Evaluation

Wearable robotic upper limb orthoses (ULO) are promising tools to assist or enhance the upper-limb function of their users. While the functionality of these devices has continuously increased, the robust and reliable detection of the user's intention to control the available degrees of freedom remains a major challenge and a barrier for acceptance. As the information interface between device and user, the intention detection strategy (IDS) has a crucial impact on the usability of the overall device. Yet, this aspect and the impact it has on the device usability is only rarely evaluated with respect to the context of use of ULO. A scoping literature review was conducted to identify non-invasive IDS applied to ULO that have been evaluated with human participants, with a specific focus on evaluation methods and findings related to functionality and usability and their appropriateness for specific contexts of use in daily life. A total of 93 studies were identified, describing 29 different IDS that are summarized and classified according to a four-level classification scheme. The predominant user input signal associated with the described IDS was electromyography (35.6%), followed by manual triggers such as buttons, touchscreens or joysticks (16.7%), as well as isometric force generated by residual movement in upper-limb segments (15.1%). We identify and discuss the strengths and weaknesses of IDS with respect to specific contexts of use and highlight a trade-off between performance and complexity in selecting an optimal IDS. Investigating evaluation practices to study the usability of IDS, the included studies revealed that, primarily, objective and quantitative usability attributes related to effectiveness or efficiency were assessed. Further, it underlined the lack of a systematic way to determine whether the usability of an IDS is sufficiently high to be appropriate for use in daily life applications. This work highlights the importance of a user- and application-specific selection and evaluation of non-invasive IDS for ULO. For technology developers in the field, it further provides recommendations on the selection process of IDS as well as to the design of corresponding evaluation protocols.

Wearable Assistive Robotics: A Perspective on Current Challenges and Future Trends

Wearable assistive robotics is an emerging technology with the potential to assist humans with sensorimotor impairments to perform daily activities. This assistance enables individuals to be physically and socially active, perform activities independently, and recover quality of life. These benefits to society have motivated the study of several robotic approaches, developing systems ranging from rigid to soft robots with single and multimodal sensing, heuristics and machine learning methods, and from manual to autonomous control for assistance of the upper and lower limbs. This type of wearable robotic technology, being in direct contact and interaction with the body, needs to comply with a variety of requirements to make the system and assistance efficient, safe and usable on a daily basis by the individual. This paper presents a brief review of the progress achieved in recent years, the current challenges and trends for the design and deployment of wearable assistive robotics including the clinical and user need, material and sensing technology, machine learning methods for perception and control, adaptability and acceptability, datasets and standards, and translation from lab to the real world.

Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 Pandemic

During the COVID-19 pandemic, the higher susceptibility of post-stroke patients to infection calls for extra safety precautions. Despite the imposed restrictions, early neurorehabilitation cannot be postponed due to its paramount importance for improving motor and functional recovery chances. Utilizing accessible state-of-the-art technologies, home-based rehabilitation devices are proposed as a sustainable solution in the current crisis. In this paper, a comprehensive review on developed home-based rehabilitation technologies of the last 10 years (2011-2020), categorizing them into upper and lower limb devices and considering both commercialized and state-of-the-art realms. Mechatronic, control, and software aspects of the system are discussed to provide a classified roadmap for home-based systems development. Subsequently, a conceptual framework on the development of smart and intelligent community-based home rehabilitation systems based on novel mechatronic technologies is proposed. In this framework, each rehabilitation device acts as an agent in the network, using the internet of things (IoT) technologies, which facilitates learning from the recorded data of the other agents, as well as the tele-supervision of the treatment by an expert. The presented design paradigm based on the above-mentioned leading technologies could lead to the development of promising home rehabilitation systems, which encourage stroke survivors to engage in under-supervised or unsupervised therapeutic activities.

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.

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.

Design and Computational Modeling of Fabric Soft Pneumatic Actuators for Wearable Assistive Devices

Assistive wearable soft robotic systems have recently made a surge in the field of biomedical robotics, as soft materials allow safe and transparent interactions between the users and devices. A recent interest in the field of soft pneumatic actuators (SPAs) has been the introduction of a new class of actuators called fabric soft pneumatic actuators (FSPAs). These actuators exploit the unique capabilities of different woven and knit textiles, including zero initial stiffness, full collapsibility, high power-to-weight ratio, puncture resistant, and high stretchability. By using 2D manufacturing methods we are able to create actuators that can extend, contract, twist, bend, and perform a combination of these motions in 3D space. This paper presents a comprehensive simulation and design tool for various types of FSPAs using finite element method (FEM) models. The FEM models are developed and experimentally validated, in order to capture the complex non-linear behavior of individual actuators optimized for free displacement and blocked force, applicable for wearable assistive tasks.

A Novel Quantitative Spasticity Evaluation Method Based on Surface Electromyogram Signals and Adaptive Neuro Fuzzy Inference System

Stroke patients often suffer from spasticity. Before treatment of spasticity, there are often practical demands for objective and quantitative assessment of muscle spasticity. However, the common quantitative spasticity assessment method, the tonic stretch reflex threshold (TSRT), is time-consuming and complicated to implement due to the requirement of multiple passive stretches. To evaluate spasticity conveniently, a novel spasticity evaluation method based on surface electromyogram (sEMG) signals and adaptive neuro fuzzy inference system (i.e., the sEMG-ANFIS method) was presented in this paper. Eleven stroke patients with spasticity and four healthy subjects were recruited to participate in the experiment. During the experiment, the Modified Ashworth scale (MAS) scores of each subject was obtained and sEMG signals from four elbow flexors or extensors were collected from several times (4–5) repetitions of passive stretching. Four time-domain features (root mean square, the zero-cross rate, the wavelength and a 4th-order autoregressive model coefficient) and one frequency-domain feature (the mean power frequency) were extracted from the collected sEMG signals to reflect the spasticity information. Using the ANFIS classifier, excellent regression performance was achieved [mean accuracy = 0.96, mean root-mean-square error (RMSE) = 0.13], outperforming the classical TSRT method (accuracy = 0.88, RMSE = 0.28). The results showed that the sEMG-ANFIS method not only has higher accuracy but also is convenient to implement by requiring fewer repetitions (4–5) of passive stretches. The sEMG-ANFIS method can help stroke patients develop proper rehabilitation training programs and can potentially be used to provide therapeutic feedback for some new spasticity interventions, such as shockwave therapy and repetitive transcranial magnetic stimulation.

Soft Miniaturized Actuation and Sensing Units for Dynamic Force Control of Cardiac Ablation Catheters

Recently, there has been active research in finding robotized solutions for the treatment of atrial fibrillation (AF) by augmenting catheter systems through the integration of force sensors at the tip. However, limited research has been aimed at providing automatic force control by also integrating actuation of the catheter tip, which can significantly enhance safety in such procedures. This article solves the demanding challenge of miniaturizing both actuation and sensing for integration into flexible catheters. Fabrication strategies are presented for a series of novel soft thick-walled cylindrical actuators, with embedded sensing using eutectic gallium-indium. The functional catheter tips have a diameter in the range of 2.6-3.6 mm and can both generate and detect forces in the range of < 0.4 N, with a bandwidth of 1-2 Hz. The deformation modeling of thick-walled cylinders with fiber reinforcement is presented in the article. An experimental setup developed for static and dynamic characterization of these units is presented. The prototyped units were validated with respect to the design specifications. The preliminary force control results indicate that these units can be used in tracking and control of contact force, which has the potential to make AF procedures much safer and more accurate.

sEMG-Based Trunk Compensation Detection in Rehabilitation Training

Stroke patients often use trunk to compensate for impaired upper limb motor function during upper limb rehabilitation training, which results in a reduced rehabilitation training effect. Detecting trunk compensations can improve the effect of rehabilitation training. This study investigates the feasibility of a surface electromyography-based trunk compensation detection (sEMG-bTCD) method. Five healthy subjects and nine stroke subjects with cognitive and comprehension skills were recruited to participate in the experiments. The sEMG signals from nine superficial trunk muscles were collected during three rehabilitation training tasks (reach-forward-back, reach-side-to-side, and reach-up-to-down motions) without compensation and with three common trunk compensations [lean-forward (LF), trunk rotation (TR), and shoulder elevation (SE)]. Preprocessing like filtering, active segment detection was performed and five time domain features (root mean square, variance, mean absolute value (MAV), waveform length, and the fourth order autoregressive model coefficient) were extracted from the collected sEMG signals. Excellent TCD performance was achieved in healthy participants by using support vector machine (SVM) classifier (LF: accuracy = 94.0%, AUC = 0.97, F1 = 0.94; TR: accuracy = 95.8%, AUC = 0.99, F1 = 0.96; SE: accuracy = 100.0%, AUC = 1.00, F1 = 1.00). By using SVM classifier, TCD performance in stroke participants was also obtained (LF: accuracy = 74.8%, AUC = 0.90, F1 = 0.73; TR: accuracy = 67.1%, AUC = 0.85, F1 = 0.71; SE: accuracy = 91.3%, AUC = 0.98, F1 = 0.90). Compared with the methods based on cameras or inertial sensors, better detection performance was obtained in both healthy and stroke participants. The results demonstrated the feasibility of the sEMG-bTCD method, and it helps to prompt the stroke patients to correct their incorrect posture, thereby improving the effectiveness of rehabilitation training.

Soft Elbow Exoskeleton for Upper Limb Assistance Incorporating Dual Motor-Tendon Actuator

Loss of muscle functions, such as the elbow, can affect the quality of life of a person. This research is aimed at developing an affordable two DOF soft elbow exoskeleton incorporating a dual motor-tendon actuator. The soft elbow exoskeleton can be used to assist two DOF motions of the upper limb, especially elbow and wrist movements. The exoskeleton is developed using fabric for the convenience purpose of the user. The dual motor-tendon actuator subsystem employs two DC motors coupled with lead-to-screw converting motion from angular into linear motion. The output is connected to the upper arm hook on the soft exoskeleton elbow. With this mechanism, the proposed actuator system is able to assist two DOF movements for flexion/extension and pronation/supination motion. Proportional-Integral (PI) control is implemented for controlling the motion. The optimized value of Kp and Ki are 200 and 20, respectively. Based on the test results, there is a slight steady-state error between the first and the second DC motor. When the exoskeleton is worn by a user, it gives more steady-state errors because of the load from the arm weight. The test results demonstrate that the proposed soft exoskeleton elbow can be worn easily and comfortably by a user to assist two DOF for elbow and wrist motion. The resulted range of motion (ROM) for elbow flexion–extension can be varied from 90° to 157°, whereas the maximum of ROM that can be achieved for pronation and supination movements are 19° and 18°, respectively.

Integration, Sensing, and Control of a Modular Soft-Rigid Pneumatic Lower Limb Exoskeleton

This article presents the system integration, sensing, and control of a novel modular soft-rigid pneumatic exoskeleton for lower limb. The proposed exoskeleton consists of three soft hinges (to drive the hip, knee, and ankle joints) and four rigid links (aligned with the waist, thigh, crus, and foot). Each soft hinge is made of and actuated by a customized bidirectional curl pneumatic artificial muscle (CPAM), whereas the links are three-dimensional printed. Each of the rigid links combined with its lower soft hinge (if any) is made into an independent soft-rigid module, that is, the waist-hip, thigh-knee, crus-ankle, and foot modules. With each of the modules are multiple sensors integrated, including two pressure sensors for detecting the inflating pressures, and two flex sensors and an inertia measurement unit for estimating the bending angles of the soft hinges via data fusion. Through a data-fitted angle-torque-pressure relationship of the CPAM, the actuation torque is estimated. An external electropneumatic control system is also developed. The double closed-loop control system consisting of pressure servos and position/torque controllers is designed to control the bending angles and actuation torques of the exoskeleton hinges. Experiment shows good motion controllability of the proposed exoskeleton in the range of motion of a gait cycle.

Physiological and kinematic effects of a soft exosuit on arm movements

BACKGROUND

Soft wearable robots (exosuits), being lightweight, ergonomic and low power-demanding, are attractive for a variety of applications, ranging from strength augmentation in industrial scenarios, to medical assistance for people with motor impairments. Understanding how these devices affect the physiology and mechanics of human movements is fundamental for quantifying their benefits and drawbacks, assessing their suitability for different applications and guiding a continuous design refinement.

METHODS

We present a novel wearable exosuit for assistance/augmentation of the elbow and introduce a controller that compensates for gravitational forces acting on the limb while allowing the suit to cooperatively move with its wearer. Eight healthy subjects wore the exosuit and performed elbow movements in two conditions: with assistance from the device (powered) and without assistance (unpowered). The test included a dynamic task, to evaluate the impact of the assistance on the kinematics and dynamics of human movement, and an isometric task, to assess its influence on the onset of muscular fatigue.

RESULTS

Powered movements showed a low but significant degradation in accuracy and smoothness when compared to the unpowered ones. The degradation in kinematics was accompanied by an average reduction of 59.20±5.58% (mean ± standard error) of the biological torque and 64.8±7.66% drop in muscular effort when the exosuit assisted its wearer. Furthermore, an analysis of the electromyographic signals of the biceps brachii during the isometric task revealed that the exosuit delays the onset of muscular fatigue.

CONCLUSIONS

The study examined the effects of an exosuit on the characteristics of human movements. The suit supports most of the power needed to move and reduces the effort that the subject needs to exert to counteract gravity in a static posture, delaying the onset of muscular fatigue. We interpret the decline in kinematic performance as a technical limitation of the current device. This work suggests that a powered exosuit can be a good candidate for industrial and clinical applications, where task efficiency and hardware transparency are paramount.