Skin interstitial fluid (ISF) is an emerging source of biomarkers for disease diagnosis and prognosis. Microneedle (MN) patch has been identified as an ideal platform to extract ISF from the skin due to its pain-free and easy-to-administrated properties. However, long sampling time is still a serious problem which impedes timely metabolic analysis. In this study, a swellable MN patch that can rapidly extract ISF is developed. The MN patch is made of methacrylated hyaluronic acid (MeHA) and further crosslinked through UV irradiation. Owing to the supreme water affinity of MeHA, this MN patch can extract sufficient ISF in a short time without the assistance of extra devices, which remarkably facilitates timely metabolic analysis. Due to covalent crosslinked network, the MN patch maintains the structure integrity in the swelling hydrated state without leaving residues in skin after usage. More importantly, the extracted ISF metabolites can be efficiently recovered from MN patch by centrifugation for the subsequent offline analysis of metabolites such as glucose and cholesterol. Given the recent trend of easy-to-use point-of-care devices for personal healthcare monitoring, this study opens a new avenue for the development of MN-based microdevices for sampling ISF and minimally invasive metabolic detection.

The behaviors of the animals or embodied agents are characterized by the dynamic coupling between the brain, the body, and the environment. This implies that control, which is conventionally thought to be handled by the brain or a controller, can partially be outsourced to the physical body and the interaction with the environment. This idea has been demonstrated in a number of recently constructed robots, in particular from the field of “soft robotics”. Soft robots are made of a soft material introducing high-dimensionality, non-linearity, and elasticity, which often makes the robots difficult to control. Biological systems such as the octopus are mastering their complex bodies in highly sophisticated manners by capitalizing on their body dynamics. We will demonstrate that the structure of the octopus arm cannot only be exploited for generating behavior but also, in a sense, as a computational resource. By using a soft robotic arm inspired by the octopus we show in a number of experiments how control is partially incorporated into the physical arm's dynamics and how the arm's dynamics can be exploited to approximate non-linear dynamical systems and embed non-linear limit cycles. Future application scenarios as well as the implications of the results for the octopus biology are also discussed.

Biological tentacles, such as octopus arms, have entirely flexible structures and virtually infinite degrees of freedom (DOF) that allow for elongation, shortening and bending at any point along the arm length. The amazing dexterity of biological tentacles has driven the growing implementation of continuum manipulators in robotic systems. This paper presents a pneumatic manipulator inspired by biological continuum structures in some of their key features and functions, such as continuum morphology, intrinsic compliance and stereotyped motions with hyper redundant DOF. The kinematics and dynamics of the manipulator are formulated and identified, and a hierarchical controller taking inspiration from the structure of an octopus nervous system is used to relate desired stereotyped motions to individual actuator inputs. Simulations and experiments are carried out to validate the model and prototype where good agreement was found between the two.

Continuum robots exhibit promising adaptability and dexterity for soft manipulation due to their intrinsic compliance. However, this compliance may lead to challenges in modeling as well as positioning and loading. In this paper, a virtual work-based static model is established to describe the deformation and mechanics of continuum robots with a generic rod-driven structure, taking the geometric constraint of the drive rods into account. Following this, this paper presents a novel variable stiffness mechanism powered by a set of embedded Shape Memory Alloy (SMA) springs, which can make the drive rods become ‘locked’ on the body structure with different configurations. The resulting effects of variable stiffness are then presented in the static model by introducing tensions of the SMA and friction on the rods. Compared with conventional models, there is no need to predefine the actuation forces of the drive rods; instead, actuation displacements are used in this new mechanism system with stiffness being regulated. As a result, the phenomenon that the continuum robot can exhibit an S-shaped curve when subject to single-directional forces is observed and analyzed. Simulations and experiments demonstrated that the presented mechanism has stiffness variation of over 287% and further demonstrated that the mechanism and its model are achievable with good accuracy, such that the ratio of positioning error is less than 2.23% at the robot end-effector to the robot length.

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Continuum robots are suitable for operating in unstructured environments owing to their intrinsic compliance. This paper presents a novel tendon-driven continuum robot equipped with two modules and a compliant backbone formed by helical springs. Each module is driven by four parallel arranged tendons to implement a redundant actuation system that guarantees dexterous motions of the robot. A position feedback controller for the continuum robot is then developed, and a quadratic programming algorithm is incorporated into the controller to achieve a smooth configuration of the robot. Experiments results show that the control method has good trajectory tracking performance against external disturbances.

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Octopus arms, as well as elephant trunks, squid tentacles, and vertebrate tongues are termed muscularhydrostats. In such structures, the volume of the organ remains constant during their motions, enabling diverse, complex, and highly controlled movements without the support of a skeleton. Such flexible structures show major advantages over articulated arms that have a rigid skeleton and joints. These advantages have been attracting roboticists aiming to apply these material properties to soft robot controls. In this paper, we show that the muscular-hydrostat system itself has the computational capacity to achieve a complex nonlinear computation. By using a 3D dynamic simulator of the system inspired by the octopus, we actually demonstrate that the system is capable of emulating complex nonlinear dynamical systems by exploiting its elastic body dynamics as a computational resource. In addition, we systematically analyze its computational power in terms of memory capacity, and show that the system has an intrinsic and characteristic short term memory profile. Finally, the implications for soft robot control and future application scenarios are discussed.