Leveraging pleat folds and soft compliant elements in inflatable fabric beams

Inflatable fabric beams (IFBs) integrating pleat folds can generate complex motion by modifying the pleat characteristics (e.g., dimensions, orientations). However, the capability of the IFB to return to the folded configuration relies upon the elasticity of the fabrics, requiring additional pressure inputs or complementary mechanisms. Using soft compliant elements (SCEs) assembled onto pleat folds is an appealing approach to improving the IFB elasticity and providing a range of spatial configurations when pressurized. This study introduces an actuator comprising an IFB with pleat folds and SCEs. By methodologically assembling the SCEs onto the pleat folds, we constrain the IFB unfolding to achieve out-of-plane motion at 5 kPa. Besides, the proposed actuator can generate angular displacement by regulating the input pressure (> 5 kPa). A matrix-based representation and model are proposed to analyze the actuator motion. We experimentally study the actuator's angular displacement by modifying SCE shapes, fold dimensions, and assembly distances of SCEs. Moreover, we analyze the effects of incorporating two SCEs onto a pleat fold. Our results show that the actuator motion can be tuned by integrating SCEs with different stiffness and varying the pleat fold dimensions. In addition, we demonstrate that the integration of two SCEs onto the pleat fold permits the actuator to return to its folded configuration when depressurized. In order to demonstrate the versatility of the proposed actuator, we devise and conduct experiments showcasing the implementation of a planar serial manipulator and a soft gripper with two grasping modalities.

Restoration of sensory information via bionic hands

Individuals who have lost the use of their hands because of amputation or spinal cord injury can use prosthetic hands to restore their independence. A dexterous prosthesis requires the acquisition of control signals that drive the movements of the robotic hand, and the transmission of sensory signals to convey information to the user about the consequences of these movements. In this Review, we describe non-invasive and invasive technologies for conveying artificial sensory feedback through bionic hands, and evaluate the technologies' long-term prospects.

Multichannel haptic feedback unlocks prosthetic hand dexterity

Loss of tactile sensations is a major roadblock preventing upper limb-absent people from multitasking or using the full dexterity of their prosthetic hands. With current myoelectric prosthetic hands, limb-absent people can only control one grasp function at a time even though modern artificial hands are mechanically capable of individual control of all five digits. In this paper, we investigated whether people could precisely control the grip forces applied to two different objects grasped simultaneously with a dexterous artificial hand. Toward that end, we developed a novel multichannel wearable soft robotic armband to convey artificial sensations of touch to the robotic hand users. Multiple channels of haptic feedback enabled subjects to successfully grasp and transport two objects simultaneously with the dexterous artificial hand without breaking or dropping them, even when their vision of both objects was obstructed. Simultaneous transport of the objects provided a significant time savings to perform the deliveries in comparison to a one-at-a-time approach. This paper demonstrated that subjects were able to integrate multiple channels of haptic feedback into their motor control strategies to perform a complex simultaneous object grasp control task with an artificial limb, which could serve as a paradigm shift in the way prosthetic hands are operated.

Biomimetic Prosthetic Hand Enabled by Liquid Crystal Elastomer Tendons

As one of the most important prosthetic implants for amputees, current commercially available prosthetic hands are still too bulky, heavy, expensive, complex and inefficient. Here, we present a study that utilizes the artificial tendon to drive the motion of fingers in a biomimetic prosthetic hand. The artificial tendon is realized by combining liquid crystal elastomer (LCE) and liquid metal (LM) heating element. A joule heating-induced temperature increase in the LCE tendon leads to linear contraction, which drives the fingers of the biomimetic prosthetic hand to bend in a way similar to the human hand. The responses of the LCE tendon to joule heating, including temperature increase, contraction strain and contraction stress, are characterized. The strategies of achieving a constant contraction stress in an LCE tendon and accelerating the cooling for faster actuation are also explored. This biomimetic prosthetic hand is demonstrated to be able to perform complex tasks including making different hand gestures, holding objects of different sizes and shapes, and carrying weights. The results can find applications in not only prosthetics, but also robots and soft machines.

Texture Discrimination with a Soft Biomimetic Finger Using a Flexible Neuromorphic Tactile Sensor Array That Provides Sensory Feedback

The compliant nature of soft fingers allows for safe and dexterous manipulation of objects by humans in an unstructured environment. A soft prosthetic finger design with tactile sensing capabilities for texture discrimination and subsequent sensory stimulation has the potential to create a more natural experience for an amputee. In this work, a pneumatically actuated soft biomimetic finger is integrated with a textile neuromorphic tactile sensor array for a texture discrimination task. The tactile sensor outputs were converted into neuromorphic spike trains, which emulate the firing pattern of biological mechanoreceptors. Spike-based features from each taxel compressed the information and were then used as inputs for the support vector machine classifier to differentiate the textures. Our soft biomimetic finger with neuromorphic encoding was able to achieve an average overall classification accuracy of 99.57% over 16 independent parameters when tested on 13 standardized textured surfaces. The 16 parameters were the combination of 4 angles of flexion of the soft finger and 4 speeds of palpation. To aid in the perception of more natural objects and their manipulation, subjects were provided with transcutaneous electrical nerve stimulation to convey a subset of four textures with varied textural information. Three able-bodied subjects successfully distinguished two or three textures with the applied stimuli. This work paves the way for a more human-like prosthesis through a soft biomimetic finger with texture discrimination capabilities using neuromorphic techniques that provide sensory feedback; furthermore, texture feedback has the potential to enhance user experience when interacting with their surroundings.

Soft Pneumatic Actuator for Rendering Anal Sphincter Tone

Sphincter tone examination, as part of digital rectal examination (DRE), can provide essential information to support the early detection of colorectal cancer. Mastering DRE skills for junior doctors is always challenging due to the lack of real training cases. In this article, we developed a soft pneumatic active actuator,made of a compound of silicone rubber materials, to mimic human sphincter muscles and simulate various anal sphincter tones for the purpose of training. Different pumping actuation (syringe and bellows) and driving mechanisms (linear, stepper, and servo motor) were implemented and compared for their effect on the rendered tones. A further comparison was made with a previous prototype based on a cable-driven mechanism. Both quantitative and qualitative assessments were conducted to evaluate the performance of each mechanism. A differential pressure sensor was used to measure applied pressure on a catheter balloon placed inside the sphincter, comparing the readings with anorectal manometry data obtained from real patients. Qualitative feedback was gathered through a user study with ten colorectal expert practitioners. Four questions were asked targeting reaction/response time, pressure level, pressure quality, and similarity to a real case. The results show the capacity and limitation of each mechanism, with the one based on a servo motor and a bellows being the most favourably rated.

An Adaptive Socket Attaches onto Residual Limb Using Smart Polymers for Upper Limb Prosthesis

A major challenge for upper limb amputees is discomfort due to improper socket fit on the residual limb during daily use of their prosthesis. Our work introduces the implementation of soft robotic actuators into a prosthetic socket. The soft actuators are a type of electrically-powered actuator. The actuator is driven through changes in internal temperature causing actuation due to vapor pressure, which results in high and reliable force outputs. A regression fit was generated to model how the smart polymer's temperature relates to force output, and the model was cross-validated based on training data collected from each actuator. A proportional integral (PI) controller regulated the force exerted by the actuators based off of tactile and temperature feedback. Results showed that a socket system can be integrated with smart polymers and sensors, and demonstrated the ability to control two actuators and reach desired forces from set temperatures.

Systematic Analysis of a Military Wearable Device Based on a Multi-Level Fusion Framework: Research Directions

With the development of the Internet of Battlefield Things (IoBT), soldiers have become key nodes of information collection and resource control on the battlefield. It has become a trend to develop wearable devices with diverse functions for the military. However, although densely deployed wearable sensors provide a platform for comprehensively monitoring the status of soldiers, wearable technology based on multi-source fusion lacks a generalized research system to highlight the advantages of heterogeneous sensor networks and information fusion. Therefore, this paper proposes a multi-level fusion framework (MLFF) based on Body Sensor Networks (BSNs) of soldiers, and describes a model of the deployment of heterogeneous sensor networks. The proposed framework covers multiple types of information at a single node, including behaviors, physiology, emotions, fatigue, environments, and locations, so as to enable Soldier-BSNs to obtain sufficient evidence, decision-making ability, and information resilience under resource constraints. In addition, we systematically discuss the problems and solutions of each unit according to the frame structure to identify research directions for the development of wearable devices for the military.