ABSTRACT
Shape display devices composed of actuation pixels enable dynamic rendering of surface morphological features, which have important roles in virtual reality and metaverse applications. The traditional pin-array solution produces sidestep-like structures between neighboring pins and normally relies on high-density pins to obtain curved surfaces. It remains a challenge to achieve continuous curved surfaces using a small number of actuated units. To address the challenge, we resort to the concept of surface continuity in computational geometry and develop a C0-continuity shape display device with trichamber fiber-reinforced soft actuators. Each trichamber unit produces three-dimensional (3D) deformation consisting of elongation, pitch, and yaw rotation, thus ensuring rendered surface continuity using low-resolution actuation units. Inspired by human tactile discrimination threshold on height and angle gradients between adjacent units, we proposed the mathematical criteria of C0-continuity shape display and compared the maximal number of distinguishable shapes using the proposed device in comparison with typical pin-array. We then established a shape control model considering the nonlinearity of soft materials to characterize and control the soft device to display C0-continuity shapes. Experimental results showed that the proposed device with nine trichamber units could render typical sets of distinguishable C0-continuity shape sequence changes. We envision that the concept of C0-continuity shape display with 3D deformation capability could improve the fidelity of the rendered shapes in many metaverse scenarios such as touching human organs in medical palpation simulations.
ABSTRACT
Pneumatic tactile displays dynamically customize surface morphological features with reconfigurable arrays of independently addressable actuators. However, their ability to render detailed tactile patterns or fine textures is limited by the low spatial resolution. For pneumatic tactile displays, the high-density integration of pneumatic actuators within a small space (fingertip) poses a significant challenge in terms of pneumatic circuit wiring. In contrast to the structure with a single-layer layout of pipes, we propose a multi-layered stacked microfluidic pipe structure that allows for a higher density of actuators and retains their independent actuation capabilities. Based on the proposed structure, we developed a soft microfluidic tactile display with a spatial resolution of 1.25 mm. The device consists of a 5 × 5 array of independently addressable microactuators, driven by pneumatic pressure, each of which enables independent actuation of the surface film and continuous control of the height. At a relative pressure of 1000 mbar, the actuator produced a perceptible out-of-plane deformation of 0.145 mm and a force of 17.7 mN. User studies showed that subjects can easily distinguish eight tactile patterns with 96% accuracy.
ABSTRACT
OBJECTIVE: Respiratory regulation is critical for patients with respiratory dysfunction. Clinically used ventilators can lead to long-term dependence and injury. Extracorporeal assistance approaches such as iron-lung devices provide a noninvasive alternative, however, artificial actuator counterparts have not achieved marvelous biomimetic ventilation as human respiratory muscles. Here, we propose a bionic soft exoskeleton robot that can achieve extracorporeal closed-loop respiratory regulation by emulating natural human breath. METHODS: For inspiration, a soft vacuum chamber is actuated to produce negative thoracic pressure and thus expand lung volume by pulling the rib cage up and outward through use of external negative pressure. For expiration, a soft origami array under positive pressure pushes the abdominal muscles inward and the diaphragm upward. To achieve in vitro measurement of respiratory profile, we describe a wireless respiratory monitoring device to measure respiratory profiles with high accuracy, validated by quantitative comparisons with spirometer as gold-standard reference. By constructing a human-robot coupled respiratory mechanical model, a model-based proportional controller is designed for continuous tracking of the target respiratory profile. RESULTS: In experiments with ten healthy participants and ten patients with respiratory difficulty, the robot can adjust its assistive forces in real time and drive human-robot coupling respiratory system to track the target profile. CONCLUSION: The biomimetic robot can achieve extracorporeal closed-loop respiratory regulation for a diverse population. SIGNIFICANCE: The soft robot has important potential to assist respiration for people with respiratory difficulty, whether in a hospital or a home setting.
ABSTRACT
The assessment of multi-person group collaboration has garnered increasing attention in recent years. However, it remains uncertain whether haptic information can be effectively utilized to measure teamwork behavior. This study seeks to evaluate teamwork competency within four-person groups and differentiate the contributions of individual members through a haptic collaborative task. To achieve this, we propose a paradigm in which four crews collaboratively manipulate a simulated boat to row along a target curve in a shared haptic-enabled virtual environment. We define eight features related to boat trajectory and synchronization among the four crews' paddling movements, which serve as indicators of teamwork competency. These features are then integrated into a comprehensive feature, and its correlation with self-reported teamwork competency is analyzed. The results demonstrate a strong positive correlation (r>0.8) between the comprehensive feature and teamwork competency. Additionally, we extract two kinesthetic features that represent the paddling movement preferences of each crew member, enabling us to distinguish their contributions within the group. These two features of the crews with the highest and the lowest contribution in each group were significantly different. This work demonstrates the feasibility of kinesthetic features in evaluating teamwork behavior during multi-person haptic collaboration tasks.