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Soft robotic gloves have attracted significant interest in hand rehabilitation in the past decade. However, current solutions are still heavy and lack finger-state monitoring and versatile treatment options. To address this, we present a lightweight soft robotic glove actuated by twisted string actuators (TSA) that provides whole-hand finger motion tracking. We have developed a virtual reality environment for hand rehabilitation training, allowing users to interact with various virtual objects. Fifteen small inertial measurement units are placed on the glove to predict finger joint angles and track whole-hand finger motion. We performed TSA experiments to identify design and control rules, by understanding how their response varies with input load and voltages. Grasping experiments were conducted to determine the grasping force and range of motion. Finally, we showcase an application of the rehabilitation glove in a Unity-based VR interface, which can actuate the operator's fingers to grasp different virtual objects. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Developing conductive hydrogel‐incorporated strain sensors with high gauge factor (GF) and toughness for wearable applications is challenging. Herein, a facile strategy to fabricate strong, tough polyacrylamide‐co‐acrylic acid [P(AAm‐co‐AAc)] hydrogels via the synergy of fiber and metal‐ligand bonds is proposed. Through the secondary equilibrium approach, the pristine P(AAm‐co‐AAc) gel network is reconstructed with fiber and carboxyl–Zr4+ (Zirconium ion) coordination bonds intertwined over the entire gel matrix, generating a synergistic reinforcement in mechanical properties. The resultant hydrogels display a maximum tensile strength of 8.50 MPa and a fracture energy of 2.75 kJ m−2, which is 1–2 orders of magnitude greater than the original P(AAm‐co‐AAc) gels. It is also experimentally approved that by selecting different natural fibers, multivalent metal ions, and synthetic macromolecules containing carboxyl groups, the proposed approach is effective and can be generalized to fabricate strong, tough gels. Additionally, the electrical properties of obtained gel are evaluated by fabricating it into a stretchable strain sensor for object identification or human motion detection. The results reveal a high GF of 5.07 under a strain smaller 55%. These hydrogels are expected to enable numerous applications in soft robotics or wearable healthcare. [ABSTRACT FROM AUTHOR]

Soft and continuously controllable grippers can be assembled from fluidic prestressed composite (FPC) actuators. Due to their highly deformable features, it is difficult to model such actuators for large deflections. This article proposes a new method for modeling large deflections of FPC actuators called the chained composite model (CCM) to characterize the quasi-static response to an applied fluid pressure and load. The CCM divides an FPC actuator into discrete elements and models each element by a small rotation model. The strain energy of each element and the work done by pressure and loads are computed using third-order displacement polynomials with unknown coefficients; then, the total energy is minimized to calculate stable shapes using the Rayleigh–Ritz method. This study provides a set of systematic design rules to help the robotics community create FPC actuators by understanding how their responses vary as a function of input forces and pressures for a number of modeling and design parameters. Composite actuators are fabricated and a soft gripper is developed to demonstrate the grasping ability of the FPC actuators. Pneumatic pressure and end loads are applied to the composite actuators, and their responses are measured. The modeled responses of the actuators are shown to be in agreement with the measured responses. [ABSTRACT FROM AUTHOR]