Soft pneumatic muscles for post-stroke lower limb ankle rehabilitation: leveraging the potential of soft robotics to optimize functional outcomes

Introduction: A soft pneumatic muscle was developed to replicate intricate ankle motions essential for rehabilitation, with a specific focus on rotational movement along the x-axis, crucial for walking. The design incorporated precise geometrical parameters and air pressure regulation to enable controlled expansion and motion.Methods: The muscle’s response was evaluated under pressure conditions ranging from 100-145 kPa. To optimize the muscle design, finite element simulation was employed to analyze its performance in terms of motion range, force generation, and energy efficiency. An experimental platform was created to assess the muscle’s deformation, utilizing advanced techniques such as high-resolution imaging and deep-learning position estimation models for accurate measurements. The fabrication process involved silicone-based materials and 3D-printed molds, enabling precise control and customization of muscle expansion and contraction.Results: The experimental results demonstrated that, under a pressure of 145 kPa, the y-axis deformation (y-def) reached 165 mm, while the x-axis and z-axis deformations were significantly smaller at 0.056 mm and 0.0376 mm, respectively, highlighting the predominant elongation in the y-axis resulting from pressure actuation. The soft muscle model featured a single chamber constructed from silicone rubber, and the visually illustrated and detailed geometrical parameters played a critical role in its functionality, allowing systematic manipulation to meet specific application requirements.Discussion: The simulation and experimental results provided compelling evidence of the soft muscle design’s adaptability, controllability, and effectiveness, thus establishing a solid foundation for further advancements in ankle rehabilitation and soft robotics. Incorporating this soft muscle into rehabilitation protocols holds significant promise for enhancing ankle mobility and overall ambulatory function, offering new opportunities to tailor rehabilitation interventions and improve motor function restoration

A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application

Patients with severe CNS injuries struggle primarily with their sensorimotor function and communication with the outside world. There is an urgent need for advanced neural rehabilitation and intelligent interaction technology to provide help for patients with nerve injuries. Recent studies have established the brain-computer interface (BCI) in order to provide patients with appropriate interaction methods or more intelligent rehabilitation training. This paper reviews the most recent research on brain-computer-interface-based non-invasive rehabilitation systems. Various endogenous and exogenous methods, advantages, limitations, and challenges are discussed and proposed. In addition, the paper discusses the communication between the various brain-computer interface modes used between severely paralyzed and locked patients and the surrounding environment, particularly the brain-computer interaction system utilizing exogenous (induced) EEG signals (such as P300 and SSVEP). This discussion reveals with an examination of the interface for collecting EEG signals, EEG components, and signal postprocessing. Furthermore, the paper describes the development of natural interaction strategies, with a focus on signal acquisition, data processing, pattern recognition algorithms, and control techniques

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

Abstract 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 $$1.04 \times 10^{-11}$$ 1.04 × 10 - 11 . The turtle is designed to enhance the robot interaction with living creatures by mimicking their limbs’ flexibility and the way of their motion

Modeling of Soft Pneumatic Actuators with Different Orientation Angles Using Echo State Networks for Irregular Time Series Data

Modeling of soft robotics systems proves to be an extremely difficult task, due to the large deformation of the soft materials used to make such robots. Reliable and accurate models are necessary for the control task of these soft robots. In this paper, a data-driven approach using machine learning is presented to model the kinematics of Soft Pneumatic Actuators (SPAs). An Echo State Network (ESN) architecture is used to predict the SPA’s tip position in 3 axes. Initially, data from actual 3D printed SPAs is obtained to build a training dataset for the network. Irregular-intervals pressure inputs are used to drive the SPA in different actuation sequences. The network is then iteratively trained and optimized. The demonstrated method is shown to successfully model the complex non-linear behavior of the SPA, using only the control input without any feedback sensory data as additional input to the network. In addition, the ability of the network to estimate the kinematics of SPAs with different orientation angles θ is achieved. The ESN is compared to a Long Short-Term Memory (LSTM) network that is trained on the interpolated experimental data. Both networks are then tested on Finite Element Analysis (FEA) data for other θ angle SPAs not included in the training data. This methodology could offer a general approach to modeling SPAs with varying design parameters

Effects of wall thickness variation on hydrogen embrittlement susceptibility of additively manufactured 316L stainless steel with lattice auxetic structures

Abstract In the present study, the hydrogen embrittlement (HE) susceptibility of an additively manufactured (AM) 316L stainless steel (SS) was investigated. The materials were fabricated in the form of a lattice auxetic structure with three different strut thicknesses, 0.6, 1, and 1.4 mm, by the laser powder bed fusion technique at a volumetric energy of 70 J·mm⁻³. The effect of H charging on the strength and ductility of the lattice structures was evaluated by conducting tensile testing of the H-charged specimens at a slow strain rate of 4 × 10⁻⁵ s⁻¹. Hydrogen was introduced to the specimens via electrochemical charging in an NaOH aqueous solution for 24 h at 80 °C before the tensile testing. The microstructure evolution of the H-charged materials was studied using the electron backscattered diffraction (EBSD) technique. The study revealed that the auxetic structures of the AM 316L-SS exhibited a slight reduction in mechanical properties after H charging. The tensile strength was slightly decreased regardless of the thickness. However, the ductility was significantly reduced with increasing thickness. For instance, the strength and uniform elongation of the auxetic structure of the 0.6 mm thick strut were 340 MPa and 17.4% before H charging, and 320 MPa and 16.7% after H charging, respectively. The corresponding values of the counterpart’s 1.4 mm thick strut were 550 MPa and 29% before H charging, and 523 MPa and 23.9% after H charging, respectively. The fractography of the fracture surfaces showed the impact of H charging, as cleavage fracture was a striking feature in H-charged materials. Furthermore, the mechanical twins were enhanced during tensile straining of the H-charged high-thickness material

Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control

Nature and biological creatures are some of the main sources of inspiration for humans. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, with a focus on the underwater application frontier

Workspace Analysis and Path Planning of a Novel Robot Configuration with a 9-DOF Serial-Parallel Hybrid Manipulator (SPHM)

The development of serial or parallel manipulator robots is constantly increasing due to the need for faster productivity and higher accuracy. Therefore, researchers have turned to combining both mechanisms, sharing the advantage from serial to parallel or vice versa. This paper proposes a new configuration design for a serial-parallel hybrid manipulator (SPHM) using the industrial robotic KUKA Kr6 R900 and 3-DOF parallel spherical mechanism. The Kr6 R900 has six degrees of freedom (6-DOF) divided into three joints for translation (x, y, z) and another three joints for orientation (A, B, C) of the end-effector and the 3-DOF parallel spherical mechanism with three paired links. On the contrary, each limb of the parallel spherical mechanism consists of revolute–revolute–spherical joints (3-RRS). This mechanism allows translation movement along the Z-axis and orientation movements about the X- and Y- axes. The new hybrid will enrich the serial manipulator in movement flexibility and expand the workspace for serial and parallel manipulator robots. In addition, a complete conceptual design is presented in detail for the new robot configuration with a schematic and experimental setup. Then, a comprehensive mathematical model was derived and solved. The forward, inverse kinematics, and workspace analyses were derived using the graphical solution. Additionally, the new hybrid manipulator was tested for path planning. Moreover, an experimental setup was prepared to test the selected path. Finally, the new robot configuration can enlarge the workspace of both manipulators and the selected path matched to the experimental test