Wearable soft robots can be effective tools for rehabilitation due to their inherent safety and compliance. Challenges, however, exist regarding the development of suitable on-body actuation methods. Furthermore, the ...
Wearable soft robots can be effective tools for rehabilitation due to their inherent safety and compliance. Challenges, however, exist regarding the development of suitable on-body actuation methods. Furthermore, the majority of existing soft wearable devices are not accessible and easy to use for those with physical disabilities. This paper presents the design, fabrication, and characterization of a soft robotic wrist orthosis to achieve flexion and extension for continuous passive motion therapy. First, we developed bending textile pneumatic actuators that could be mechanically programmed to conform to the target joint's anatomy when mounted on the body. The textile pneumatic actuators achieved up to 2.24 Nm of torque at 124 kP $a$ . We then embedded the textile pneumatic actuators into a soft wrist orthosis that we designed to ensure it was easy to don/doff without assistance. To determine the operating pressures and range of motion achievable by our soft robotic wrist orthosis, we conducted a device evaluation study with three healthy individuals. Our device achieved over 100 degrees of flexion/extension assistance at operating pressures below 90 kPa. This work takes the first steps towards developing a wearable soft robotic device that can deliver passive therapy at home without the need for a physical therapist or assistant.
In tissue engineering, the mechanical properties of the extracellular matrix (ECM) or scaffolds have increasingly been considered to impact therapeutic efficacy by regulating cell behaviors, including differentiation,...
In tissue engineering, the mechanical properties of the extracellular matrix (ECM) or scaffolds have increasingly been considered to impact therapeutic efficacy by regulating cell behaviors, including differentiation, proliferation, migration, and adhesion. However, the understanding of how cells sense, integrate, and convert the mechanical cues from the ECM cues into biochemical signals to control certain cell behaviors is still elusive, especially in 3D, which more closely mimics the natural microenvironment than 2D systems. This review highlights the key differences between 2 and 3D in the contexts of mechanoregulative cell behaviors such as cell adhesion, spreading, migration, and force transmission. Furthermore, critical designing factors that needs to be considered for the fabrication of 3D tissue engineering scaffolds is discussed: stiffness, viscoelasticity, degradability, and the immobilization of biomolecules. Although mechanotransduction in 3D is actively being studied, understanding cellular mechanotransduction in 3D and designing of mechanoregulative 3D scaffolds still presents several challenges, including varying mechanical properties depending on different tissues, dynamic mechanical environments, and integration of multimodal cues. Interdisciplinary methodologies encompassing material engineering, cell biology, and mechanicalengineering would serve to mitigate these challenges and augment our understanding of mechanoregulation governing cellular behaviors, thus fostering advancements in biomedical applications in the future.
A tremendous range of design tasks in materials, physics, and biology can be formulated as finding the optimum of an objective function depending on many parameters without knowing its closed-form expression or the de...
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Damping typically results in attenuation of vibrations and elastic wave propagation in mechanical systems. Contrary to this conventional understanding, we demonstrate experimentally and explain theoretically the reviv...
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Damping typically results in attenuation of vibrations and elastic wave propagation in mechanical systems. Contrary to this conventional understanding, we demonstrate experimentally and explain theoretically the revival of an elastic wave transmitted through a periodic metastructure when a weak non-Hermitian defect (damping mechanism) induces violation of time-reversal symmetry. Damping alters the nature of the system’s resonant modes, instigating interference in the scattering field. This leads to transmission revival, revealing the presence of hidden modes, which are otherwise masked by the symmetry. Our findings offer an approach for designing dissipation-driven switches and controllers and nondestructive structural health-monitoring systems.
In this article, a series of tetra-functional quinoxaline-based benzoxazine/ monofunctional benzoxazine (P-a) blending resins were prepared. Differential scanning calorimeter (DSC), dynamic mechanical analyzer (DMA) a...
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Predicting the grasp stability before lifting an object, to be detailed, whether a gripped object will move with respect to the gripper, gives more time to modify unstable grasps compared to after-lift slip detection....
Predicting the grasp stability before lifting an object, to be detailed, whether a gripped object will move with respect to the gripper, gives more time to modify unstable grasps compared to after-lift slip detection. Recently, deep learning relying on visual and tactile information becomes increasingly popular. However, how to combine visual and tactile data effectively is still under research. In this paper, we propose to fuse visual and tactile data by introducing self attention (SA) mechanisms for predicting grasp stability. In our experiments, we use tactile sensors (uSkin) and camera sensor (Spresense). An image of the object, not collected immediately before or during grasping, is used, as it might be more readily available. Dataset collection is done by grasping and lifting 1050 times on 35 daily objects in total with various forces and grasping positions. As a result, the predicted accuracy improves over 9% compared to previous attention-based visual-tactile fusion research. Furthermore, our analysis reveals that the introduction of self-attention mechanisms enables more effective and widespread feature extraction for both visual and tactile data.
Lightweighting has been a key goal for engineers and designers, with lattice structures widely explored as the building blocks for structural components. Cellular structure-inspired lattice truss frame designs made of...
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Since the surge of data in materialsscience research and the advancement in machine learning methods, an increasing number of researchers are introducing machine learning techniques into the next generation of materi...
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In this work we develop a stochastic algorithm to integrate the Cahn-Hilliard equations. The algorithm is based on Gillespie's stochastic simulation algorithm, also known as kinetic Monte Carlo. The deterministic ...
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Carbon nanotubes (CNTs) are considered as promising nanofiber reinforcing materials for resin-based composites own to their excellent mechanical properties. However, uneven distribution and poor alignment of CNTs hind...
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