Design and testing of a soft parallel robot based on pneumatic artificial muscles for wrist rehabilitation

Soft Sensors and Actuators for Wearable Human-Machine Interfaces

Haptic human-machine interfaces (HHMIs) combine tactile sensation and haptic feedback to allow humans to interact closely with machines and robots, providing immersive experiences and convenient lifestyles. Significant progress has been made in developing wearable sensors that accurately detect physical and electrophysiological stimuli with improved softness, functionality, reliability, and selectivity. In addition, soft actuating systems have been developed to provide high-quality haptic feedback by precisely controlling force, displacement, frequency, and spatial resolution. In this Review, we discuss the latest technological advances of soft sensors and actuators for the demonstration of wearable HHMIs. We particularly focus on highlighting material and structural approaches that enable desired sensing and feedback properties necessary for effective wearable HHMIs. Furthermore, promising practical applications of current HHMI technology in various areas such as the metaverse, robotics, and user-interactive devices are discussed in detail. Finally, this Review further concludes by discussing the outlook for next-generation HHMI technology.

Development of a robot-assisted reduction and rehabilitation system for distal radius fractures

Background: Closed reduction is the preferred treatment for distal radius fractures. However, it requires a multiple experienced medical staff and manually maintaining stable traction is difficult. Additionally, doctors cannot assess the reduction status of a fracture in real-time through radiographic images, which may lead to improper reduction. Furthermore, post-fracture complications such as joint adhesion, stiffness, and impaired mobility pose a challenge for the doctors. So it is necessary to optimize the treatment process of the distal radius fracture through technological means. Methods: A robot-assisted closed reduction and rehabilitation system, which could assist doctors throughout the entire process of reduction, fixation, and rehabilitation of distal radius fractures, was developed. A mechanical system, composed of two grippers and a cooperative robotic arm, was used to grasp and tract the affected limb. A doctor controlled the robot through a joystick console and Windows application program. A biplane radiographic device was integrated into the system, which is not only convenient for doctors to view radiographic images of the fracture at any time but also for them to select the rotation axis of the wrist on the images before reduction and rehabilitation. Important information including the anteroposterior and lateral radiographic data and force and position parameters during the reduction and rehabilitation process were displayed on a graphic user interface. Results: Experimental results showed that the proposed robotic system can meet the technical requirements for the reduction and rehabilitation of distal radius fractures, all the rotation angles could be achieved, a maximum force of more than 50 N could be achieved in all traction directions, and the error in selecting the wrist joint rotation axis line using radiographic images was less than 5 mm. Conclusion: The developed robot-assisted system was shown to be suitable for closed reduction and rehabilitation of distal radius fractures, contributing a potential improvement in the quality of the procedures.

Multi-Objective Optimal Design of a Cable-Driven Parallel Robot Based on an Adaptive Adjustment Inertia Weight Particle Swarm Optimization Algorithm

Cable-driven parallel robots (CDPRs) have been widely used in engineering fields because of their significant advantages including high load-bearing capacity, large workspace, and low inertia. However, the impact of convergence speed and solution accuracy of optimization approaches on optimal performances can become a key issue when it comes to the optimal design of CDPR applied to large storage space. An adaptive adjustment inertia weight particle swarm optimization (AAIWPSO) algorithm is proposed for the multi-objective optimal design of CDPR. The kinematic and static models of CDPR are established based on the principle of virtual work. Subsequently, two performance indices including workspace and dexterity are derived. A multi-objective optimization model is established based on performance indices. The AAIWPSO algorithm introduces an adaptive adjustment inertia weight to improve the convergence efficiency and accuracy of traditional particle swarm optimization (PSO) algorithm. Numerical examples demonstrate that final convergence values of the objective function by the AAIWPSO algorithm can almost be 14∼20% and 19∼40% higher than those by the PSO algorithm and genetic algorithm (GA) for the optimal design of CDPR with different configurations and masses of end-effectors, respectively.

Assisted damage closure and healing in soft robots by shape memory alloy wires

Self-healing soft robots show enormous potential to recover functional performance after healing the damages. However, healing in these systems is limited by the recontact of the fracture surfaces. This paper presents for the first time a shape memory alloy (SMA) wire-reinforced soft bending actuator made out of a castor oil-based self-healing polymer, with the incorporated ability to recover from large incisions via shape memory assisted healing. The integrated SMA wires serve three major purposes; (i) Large incisions are closed by contraction of the current-activated SMA wires that are integrated into the chamber. These pull the fracture surfaces into contact, enabling the healing. (ii) The heat generated during the activation of the SMA wires is synergistically exploited for accelerating the healing. (iii) Lastly, during pneumatic actuation, the wires constrain radial expansion and one-side longitudinal extension of the soft chamber, effectuating the desired actuator bending motion. This novel approach of healing is studied via mechanical and ultrasound tests on the specimen level, as well as via bending characterization of the pneumatic robot in multiple damage healing cycles. This technology allows soft robots to become more independent in terms of their self-healing capabilities from human intervention.

Empowering Hand Rehabilitation with AI-Powered Gesture Recognition: A Study of an sEMG-Based System

Stroke is one of the most prevalent health issues that people face today, causing long-term complications such as paresis, hemiparesis, and aphasia. These conditions significantly impact a patient's physical abilities and cause financial and social hardships. In order to address these challenges, this paper presents a groundbreaking solution-a wearable rehabilitation glove. This motorized glove is designed to provide comfortable and effective rehabilitation for patients with paresis. Its unique soft materials and compact size make it easy to use in clinical settings and at home. The glove can train each finger individually and all fingers together, using assistive force generated by advanced linear integrated actuators controlled by sEMG signals. The glove is also durable and long-lasting, with 4-5 h of battery life. The wearable motorized glove is worn on the affected hand to provide assistive force during rehabilitation training. The key to this glove's effectiveness is its ability to perform the classified hand gestures acquired from the non-affected hand by integrating four sEMG sensors and a deep learning algorithm (the 1D-CNN algorithm and the InceptionTime algorithm). The InceptionTime algorithm classified ten hand gestures' sEMG signals with an accuracy of 91.60% and 90.09% in the training and verification sets, respectively. The overall accuracy was 90.89%. It showed potential as a tool for developing effective hand gesture recognition systems. The classified hand gestures can be used as a control command for the motorized wearable glove placed on the affected hand, allowing it to mimic the movements of the non-affected hand. This innovative technology performs rehabilitation exercises based on the theory of mirror therapy and task-oriented therapy. Overall, this wearable rehabilitation glove represents a significant step forward in stroke rehabilitation, offering a practical and effective solution to help patients recover from stroke's physical, financial, and social impact.

Stiffness characteristics analysis of a Biglide industrial parallel robot considering the gravity of mobile platform and links

For the machining process of industrial parallel robots, the gravity generated by the weight of mobile platform and links will lead to the deviation of the expected machining trajectory of the tool head. In order to evaluate this deviation and then circumvent it, it is necessary to perform the robotic stiffness model. However, the influence of gravity is seldom considered in the previous stiffness analysis. This paper presents an effective stiffness modeling method for industrial parallel robots considering the link/joint compliance, the mobile platform/link gravity, and the mass center position of each link. First, the external gravity corresponding to each component is determined by the static model under the influence of gravity and mass center position. Then, the corresponding Jacobian matrix of each component is obtained by the kinematic model. Subsequently, the compliance of each component is obtained by cantilever beam theory and FEA-based virtual experiments. In turn, the stiffness model of the whole parallel robot is determined and the Cartesian stiffness matrix of the parallel robot is calculated at several positions. Moreover, the principal stiffness distribution of the tool head in each direction over the main workspace is predicted. Finally, the validity of the stiffness model with gravity is experimentally proved by the comparison of the calculated stiffness and measured stiffness in identical conditions.

Lightweight Bioinspired Exoskeleton for Wrist Rehabilitation Powered by Twisted and Coiled Artificial Muscles

Stroke, cerebral palsy, and spinal cord injuries represent the most common leading causes of upper limb impairment. In recent years, rehabilitation robotics has progressed toward developing wearable technologies to promote the portability of assistive devices and to enable home rehabilitation of the upper extremities. However, current wearable technologies mainly rely on electric motors and rigid links or soft pneumatic actuators and are usually bulky and cumbersome. To overcome the limitations of existing technologies, in this paper, a first prototype of a lightweight, ungrounded, soft exoskeleton for wrist rehabilitation powered by soft and flexible carbon fibers-based twisted and coiled artificial muscles (TCAMs) is proposed. The device, which weighs only 0.135 kg, emulates the arrangement and working mechanism of skeletal muscles in the upper extremities and is able to perform wrist flexion/extension and ulnar/radial deviation. The range of motion and the force provided by the exoskeleton is designed through simple kinematic and dynamic theoretical models, while a thermal model is used to design a thermal insulation system for TCAMs during actuation. The device’s ability to perform passive and active-resisted wrist rehabilitation exercises and EMG-based actuation is also demonstrated.

Advances in artificial muscles: A brief literature and patent review

Background: Artificial muscles are an active research area now. Methods: A bibliometric analysis was performed to evaluate the development of artificial muscles based on research papers and patents. A detailed overview of artificial muscles' scientific and technological innovation was presented from aspects of productive countries/regions, institutions, journals, researchers, highly cited papers, and emerging topics. Results: 1,743 papers and 1,925 patents were identified after retrieval in Science Citation Index-Expanded (SCI-E) and Derwent Innovations Index (DII). The results show that China, the United States, and Japan are leading in the scientific and technological innovation of artificial muscles. The University of Wollongong has the most publications and Spinks is the most productive author in artificial muscle research. Smart Materials and Structures is the journal most productive in this field. Materials science, mechanical and automation, and robotics are the three fields related to artificial muscles most. Types of artificial muscles like pneumatic artificial muscles (PAMs) and dielectric elastomer actuator (DEA) are maturing. Shape memory alloy (SMA), carbon nanotubes (CNTs), graphene, and other novel materials have shown promising applications in this field. Conclusion: Along with the development of new materials and processes, researchers are paying more attention to the performance improvement and cost reduction of artificial muscles.

Actuators for Implantable Devices: A Broad View

The choice of actuators dictates how an implantable biomedical device moves. Specifically, the concept of implantable robots consists of the three pillars: actuators, sensors, and powering. Robotic devices that require active motion are driven by a biocompatible actuator. Depending on the actuating mechanism, different types of actuators vary remarkably in strain/stress output, frequency, power consumption, and durability. Most reviews to date focus on specific type of actuating mechanism (electric, photonic, electrothermal, etc.) for biomedical applications. With a rapidly expanding library of novel actuators, however, the granular boundaries between subcategories turns the selection of actuators a laborious task, which can be particularly time-consuming to those unfamiliar with actuation. To offer a broad view, this study (1) showcases the recent advances in various types of actuating technologies that can be potentially implemented in vivo, (2) outlines technical advantages and the limitations of each type, and (3) provides use-specific suggestions on actuator choice for applications such as drug delivery, cardiovascular, and endoscopy implants.

Design of Spiral-Cable Forearm Exoskeleton to Assist Supination for Hemiparetic Stroke Subjects

We present the development of a cable-based passive forearm exoskeleton that is designed to assist supination for hemiparetic stroke survivors. Our device uniquely provides torque sufficient for counteracting spasticity within a below-elbow apparatus. The mechanism consists of a spiral single-tendon routing embedded in a rigid forearm brace and terminated at the hand and upper-forearm. A spool with an internal releasable-ratchet mechanism allows the user to manually retract the tendon and rotate the hand to counteract involuntary pronation synergies due to stroke. We characterize the mechanism with benchtop testing and five healthy subjects, and perform a preliminary assessment of the exoskeleton with a single chronic stroke subject having minimal supination ability. The mechanism can be integrated into an existing active hand-opening orthosis to enable supination support during grasping tasks, and also allows for a future actuated supination strategy.

Current State of Robotics in Hand Rehabilitation after Stroke: A Systematic Review

Among the methods of hand function rehabilitation after stroke, robot-assisted rehabilitation is widely used, and the use of hand rehabilitation robots can provide functional training of the hand or assist the paralyzed hand with activities of daily living. However, patients with hand disorders consistently report that the needs of some users are not being met. The purpose of this review is to understand the reasons why these user needs are not being adequately addressed, to explore research on hand rehabilitation robots, to review their current state of research in recent years, and to summarize future trends in the hope that it will be useful to researchers in this research area. This review summarizes the techniques in this paper in a systematic way. We first provide a comprehensive review of research institutions, commercial products, and literature. Thus, the state of the art and deficiencies of functional hand rehabilitation robots are sought and guide the development of subsequent hand rehabilitation robots. This review focuses specifically on the actuation and control of hand functional rehabilitation robots, as user needs are primarily focused on actuation and control strategies. We also review hand detection technologies and compare them with patient needs. The results show that the trends in recent years are more inclined to pursue new lightweight materials to improve hand adaptability, investigating intelligent control methods for human-robot interaction in hand functional rehabilitation robots to improve control robustness and accuracy, and VR virtual task positioning to improve the effectiveness of active rehabilitation training.

Modelling and implementation of soft bio-mimetic turtle using echo state network and soft pneumatic actuators

Advances of soft robotics enabled better mimicking of biological creatures and closer realization of animals' motion in the robotics field. The biological creature's movement has morphology and flexibility that is problematic deportation to a bio-inspired robot. This paper aims to study the ability to mimic turtle motion using a soft pneumatic actuator (SPA) as a turtle flipper limb. SPA's behavior is simulated using finite element analysis to design turtle flipper at 22 different geometrical configurations, and the simulations are conducted on a large pressure range (0.11-0.4 Mpa). The simulation results are validated using vision feedback with respect to varying the air pillow orientation angle. Consequently, four SPAs with different inclination angles are selected to build a bio-mimetic turtle, which is tested at two different driving configurations. The nonlinear dynamics of soft actuators, which is challenging to model the motion using traditional modeling techniques affect the turtle's motion. Conclusively, according to kinematics behavior, the turtle motion path is modeled using the Echo State Network (ESN) method, one of the reservoir computing techniques. The ESN models the turtle path with respect to the actuators' rotation motion angle with maximum root-mean-square error of [Formula: see text]. The turtle is designed to enhance the robot interaction with living creatures by mimicking their limbs' flexibility and the way of their motion.