Search Results (146)

Tactile maps are widely recognized as useful tools for mobility training and the rehabilitation of visually impaired individuals. However, current tactile maps lack real-time versatility and are limited because of high manufacturing and design costs. In this study, we introduce a device (i.e., ClaySight) that enhances the creation of automatic tactile map generation, as well as a model for wearable devices that use low-cost laser imaging, detection, and ranging (LiDAR,) used to improve the immediate spatial knowledge of visually impaired individuals. Our system uses LiDAR sensors to (1) produce affordable, low-latency tactile maps, (2) function as a day-to-day wayfinding aid, and (3) provide interactivity using a wearable device. The system comprises a dynamic mapping and scanning algorithm and an interactive handheld 3D-printed device that houses the hardware. Our algorithm accommodates user specifications to dynamically interact with objects in the surrounding area and create map models that can be represented with haptic feedback or alternative tactile systems. Using economical components and open-source software, the ClaySight system has significant potential to enhance independence and quality of life for the visually impaired. Full article

Over the past few years, life expectancy has increased significantly. However, elderly individuals living independently often require assistance due to mobility issues, symptoms of dementia, or other health-related challenges. In these situations, high-quality elderly care systems for the aging population require innovative approaches to guarantee Quality of Service (QoS) and Quality of Experience (QoE). Traditional remote elderly care methods face several challenges, including high latency and poor service quality, which affect their transparency and stability. This paper proposes an Edge Computational Intelligence (ECI)-based haptic-driven ECI-TeleCaring system for the remote caring and monitoring of elderly people. It utilizes a Software-Defined Network (SDN) and Mobile Edge Computing (MEC) to reduce latency and enhance responsiveness. Dual Long Short-Term Memory (LSTM) models are deployed at the edge to enable real-time location-aware activity prediction to ensure QoS and QoE. The results from the simulation demonstrate that the proposed system is proficient in managing the transmission of data in real time without and with an activity recognition and location-aware model by communication latency under 2.5 ms (more than 60%) and from 11∼12 ms (60∼95%) for 10 to 1000 data packets, respectively. The results also show that the proposed system ensures a trade-off between the transparency and stability of the system from the QoS and QoE perspectives. Moreover, the proposed system serves as a testbed for implementing, investigating, and managing elder telecaring services for QoS/QoE provisioning. It facilitates real-time monitoring of the deployed technological parameters along with network delay and packet loss, and it oversees data exchange between the master domain (human operator) and slave domain (telerobot). Full article

Cardiac ablation (CA) is an interventional electrophysiological procedure used to disrupt arrhythmic substrates in the myocardium by inducing localized scarring. Current CA training relies on the master–apprentice model. In different fields of medicine including CA, virtual and physical simulators have proven to enhance, and even outperform, conventional training modalities while providing a risk-free learning environment. Despite the benefits, high costs and operational difficulties limit the widespread use of interventional simulators. Our previous research introduced a low-cost CA simulator using a 3D-printed biatrial cardiac model, successfully recording ten ablation lesions on the phantom myocardium. In this work, we present and evaluate an enhanced version: compared to the previous version, the cardiac phantom’s electrical behavior and ablation settings were optimized to produce consistent lesions, while 3D-printed components improved the haptic and radiographic properties of the simulator. Seven cardiologists compared the experimental simulator’s performance to the leading commercial system from Heartroid in a 24-question survey on a 5-point Likert scale. The four following areas of fidelity were considered: catheter entry, anatomical correctness, radiographic appearance, and mapping and ablation. The experimental simulator significantly outperformed the commercial system (p < 0.01), particularly in radiographic appearance (p < 0.01). The results show the potential for the experimental simulator in routine CA training. Full article

Interventional radiologists mainly rely on visual feedback via imaging modalities to steer a needle toward a tumor during biopsy and ablation procedures. In the case of CT-guided procedures, there is a risk of exposure to hazardous X-ray-based ionizing radiation. Therefore, CT scans are usually not used continuously, which increases the chances of a misplacement of the needle and the need for reinsertion, leading to more tissue trauma. Interventionalists also encounter haptic feedback via needle–tissue interaction forces while steering a needle. These forces are useful but insufficient to clearly perceive and identify deep-tissue structures such as tumors. The objective of this paper was to investigate the effect of enhanced force feedback for sensing interaction forces and guiding the needle when applied individually and simultaneously during a virtual CT-guided needle insertion task. We also compared the enhanced haptic feedback to enhanced visual feedback. We hypothesized that enhancing the haptic feedback limits the time needed to reach the target accurately and reduces the number of CT scans, as the interventionalist depends more on real-time enhanced haptic feedback. To test the hypothesis, a simulation environment was developed to virtually steer a needle in five degrees of freedom (DoF) to reach a tumor target embedded in a liver model. Twelve participants performed in the experiment with different feedback conditions where we measured their performance in terms of the following: targeting accuracy, trajectory tracking, number of CT scans required, and the time needed to finish the task. The results suggest that the combination of enhanced haptic feedback for guidance and sensing needle–tissue interaction forces significantly reduce the number of scans and the duration required to finish the task by 32.1% and 46.9%, respectively, when compared to nonenhanced haptic feedback. The other feedback modalities significantly reduced the duration to finish the task by around 30% compared to nonenhanced haptic feedback. Full article

Pumping stations have undergone significant modernization and digitalization in recent decades. However, traditional virtual inspections often prioritize the visual experience and fail to effectively represent the haptic physical properties of devices during inspections, resulting in poor immersion and interactivity. This paper presents a novel virtual inspection system for pumping stations, incorporating virtual reality interaction and haptic force feedback technology to enhance immersion and realism. The system leverages a 3D model, crafted in 3Ds Max, to provide immersive visualizations. Multimodal feedback is achieved through a combination of haptic force feedback provided by a haptic device and visual information delivered by a VR headset. The system’s data platform integrates with external databases using Unity3D to display relevant information. The system provides immersive 3D visualizations and realistic force feedback during simulated inspections. We compared this system to a traditional virtual inspection method that demonstrated statistically significant improvements in task completion rates and a reduction in failure rates when using the multimodal feedback approach. This innovative approach holds the potential to enhance inspection safety, efficiency, and effectiveness in the pumping station industry. Full article

Dielectric elastomer actuators (DEAs) have gained significant attention due to their potential in soft robotics and adaptive structures. However, their performance is often limited by their in-plane strain distribution and limited mechanical stability. We introduce a novel design utilizing fiber reinforcement to address these challenges. The fiber reinforcement provides enhanced mechanical integrity and improved strain distribution, enabling efficient energy conversion and out-of-plane displacement. We discuss an analytical model and the fabrication process, including material selection, to realize fiber-reinforced DEAs. Numerical simulations and experimental results demonstrate the performance of the fiber-reinforced equibiaxial DEAs and characterize their displacement and force capabilities. Actuators with four and eight fibers are fabricated with 100 μm and 200 μm dielectric thicknesses. A maximal out-of-plane displacement of 500 μm is reached, with a force of 0.18 N, showing promise for the development of haptic devices. Full article

In recent years, tasks regarding autonomous mobility favoredthe use of legged robots rather than wheeled ones thanks to their higher mobility on rough and uneven terrains. This comes at the cost of more complex motion planners and controllers to ensure robot stability and balance. However, in the case of quadrupedal robots, balancing is simpler than it is for bipeds thanks to their larger support polygons. Until a few years ago, most scientists and engineers addressed the quadrupedal locomotion problem with model-based approaches, which require a great deal of modeling expertise. A new trend is the use of data-driven methods, which seem to be quite promising and have shown great results. These methods do not require any modeling effort, but they suffer from computational limitations dictated by the hardware resources used. However, only the design phase of these algorithms requires large computing resources (controller training); their execution in the operational phase (deployment), takes place in real time on common processors. Moreover, adaptive feet capable of sensing terrain profile information have been designed and have shown great performance. Still, no dynamic locomotion control method has been specifically designed to leverage the advantages and supplementary information provided by this type of adaptive feet. In this work, we investigate the use and evaluate the performance of different end-to-end control policies trained via reinforcement learning algorithms specifically designed and trained to work on quadrupedal robots equipped with passive adaptive feet for their dynamic locomotion control over a diverse set of terrains. We examine how the addition of the haptic perception of the terrain affects the locomotion performance. Full article

Haptic organs are common in nature and help animals to navigate environments where vision is not possible. Insects often use slender, lightweight, and flexible links as sensing antennae. These antennae have a muscle-endowed base that changes their orientation and an organ that senses the applied force and moment, enabling active sensing. Sensing antennae detect obstacles through contact during motion and even recognize objects. They can also push obstacles. In all these tasks, force control of the antenna is crucial. The objective of our research is to develop a haptic robotic system based on a sensing antenna, consisting of a very lightweight and slender flexible rod. In this context, the work presented here focuses on the force control of this device. To achieve this, (a) we develop a dynamic model of the antenna that moves under gravity and maintains point contact with an object, based on lumped-mass discretization of the rod; (b) we prove the robust stability property of the closed-loop system using the Routh stability criterion; and (c) based on this property, we design a robust force control system that performs efficiently regardless of the contact point with the object. We built a mechanical device replicating this sensing organ. It is a flexible link connected at one end to a 3D force–torque sensor, which is attached to a mechanical structure with two DC motors, providing azimuthal and elevation movements to the antenna. Our experiments in contact situations demonstrate the effectiveness of our control method. Full article

The rapid development of wearable technologies is increasing research interest in on-body robotics, where relocatable robots can serve as haptic interfaces, support healthcare measurements, or assist with daily activities. However, on-body mobile robotics poses challenges in aspects such as stable locomotion and control. This article proposes a novel small robot design for moving on human limbs that consists of an open grasping mechanism with a spring linkage, where one side holds a pivoting differential drive base (PDDB) with two spherical rollers, and the other side holds an actuated roller for grasping and stabilization. The spherical rollers maintain contact at three points on the limb, optimizing stability with a minimal number of rollers and integrating DC motors within. The PDDB wheels (spherical rollers) enable directional changes on limb surfaces. The combination of the open mechanism, the PDDB, and the spherical rollers allows adaptability to diameter variations along the limb. Furthermore, the mechanism can be easily put on or removed at any point along the limb, eliminating the need to slip the robot over the hand or foot. The kinematic model for the proposed mechanism has been developed. A cascade control strategy is proposed with an outer loop for stable grasping and an inner loop for trajectory adjustments using PDDB roller velocities. An on-limb robot prototype has been built to test its applicability to human arms. Simulation and experimental results validate the design. Full article

This review explores the historical and current significance of gestures as a universal form of communication with a focus on hand gestures in virtual reality applications. It highlights the evolution of gesture detection systems from the 1990s, which used computer algorithms to find patterns in static images, to the present day where advances in sensor technology, artificial intelligence, and computing power have enabled real-time gesture recognition. The paper emphasizes the role of hand gestures in virtual reality (VR), a field that creates immersive digital experiences through the Ma blending of 3D modeling, sound effects, and sensing technology. This review presents state-of-the-art hardware and software techniques used in hand gesture detection, primarily for VR applications. It discusses the challenges in hand gesture detection, classifies gestures as static and dynamic, and grades their detection difficulty. This paper also reviews the haptic devices used in VR and their advantages and challenges. It provides an overview of the process used in hand gesture acquisition, from inputs and pre-processing to pose detection, for both static and dynamic gestures. Full article

Soft robotics is a hot scientific topic in areas such as medicine and medical care, implantology, haptic technologies, and the design of various flexible structures. Integrated actuators (DEAP and MRE) are characterized by special functionality and a wider range of operations than when used individually. Such actuators can later be controlled with high voltages ranging from several to a dozen or so kV. Unfortunately, the production process of integrated actuators is multi-stage and therefore more complicated. Thus, at the stage of prototyping, microscopic errors often occur that cannot be detected using simple measurement methods. The result of such errors is actuator damage at the testing stage or in subsequent application. Unfortunately, due to high voltages, actuator damage usually leads to it catching fire, which is potentially dangerous. This work presents an approach that enables the prediction of actuator damage at the testing stage. The results of modeling damaged actuators, a modified safe testing method, and a complete supervising system for testing the actuator with protection are shown. The work is also enriched with a set of data from the analyzed damage to DEAP and MRE actuators, which may prove useful in other research on the actuators of soft robotics. Full article

In this study, we present a novel approach to derive hand poses from data input via a haptic controller, leveraging machine learning techniques. The input values received from the haptic controller correspond to the movement of five fingers, each assigned a value between 0.0 and 1.0 based on the applied pressure. The wide array of possible finger movements requires a substantial amount of motion capture data, making manual data integration difficult. This challenge is primary due to the need to process and incorporate large volumes of diverse movement information. To tackle this challenge, our proposed method automates the process by utilizing machine learning algorithms to convert haptic controller inputs into hand poses. This involves training a machine learning model using supervised learning, where hand poses are matched with their corresponding input values, and subsequently utilizing this trained model to generate hand poses in response to user input. In our experiments, we assessed the accuracy of the generated hand poses by analyzing the angles and positions of finger joints. As the quantity of training data increased, the margin of error decreased, resulting in generated poses that closely emulated real-world hand movements. Full article

Haptic feedback holds the potential to enhance the engagement and expressivity of future digital and electric musical instruments. This study investigates the impact of artificial vibration on the perceived quality of a silent electric cello. We developed a haptic cello prototype capable of rendering vibration signals of varying degree of congruence with the produced sound. Experienced cellists participated in an experiment comparing setups with and without vibrotactile feedback, rating them on preference, perceived power, liveliness, and feel. Results show nuanced effects, with added vibrations moderately enhancing feel and liveliness, and significantly increasing perceived power when using vibrations obtained from the pickup at the cello’s bridge. High uncertainty in our statistical model parameters underscores substantial individual differences in the participants responses, as commonly found in qualitative assessments, and highlights the importance of consistent feedback in the vibrotactile and auditory channels. Our findings contribute valuable insights to the intersection of haptics and music technology, paving the way for creating richer and more engaging experiences with future musical instruments. Full article

Damping involves the various frictional and other obstructive effects that attenuate free vibration. For a long time, people have mainly used it to make various dampers to reduce mechanical vibration and consume kinetic energy. It is widely used in fields such as aerospace, automotive, and consumer electronics. These dampers mainly act on mechanical structures. In recent years, with the rapid development of novel human–machine interaction methods and force/tactile feedback technology, the damper has begun to act on people, such as when a person interacts with a robot and their force is applied to a structure with damping. This type of damper requires variable damping, and the amount of variation is controlled by the magnitude of human action. This study used magnetorheological fluid (MRF) instead of traditional damping fluids, such as silicone oil, sesame oil, and mechanical oil. Magnetorheological fluid is a controllable fluid with magnetorheological effects, and its viscosity (hardness) can be changed by changing the nearby magnetic field. This study took the design of variable damping keyboard buttons with haptic feedback as an example to study the electromagnetic and dynamic models of variable dampers based on magnetorheological fluids. The experimental setup was designed and used to verify the haptic effectiveness of the scheme, which can be applied to the development of other haptic dampers that require variable damping. Full article

Emotion recognition from facial expressions is a challenging task due to the subtle and nuanced nature of facial expressions. Within the framework of Tactile Internet (TI), the integration of this technology has the capacity to completely transform real-time user interactions, by delivering customized emotional input. The influence of this technology is far-reaching, as it may be used in immersive virtual reality interactions and remote tele-care applications to identify emotional states in patients. In this paper, a novel emotion recognition algorithm is presented that integrates a Self-Attention (SA) module into the SlowR50 backbone (SlowR50-SA). The experiments on the DFEW and FERV39K datasets demonstrate that the proposed model achieves good performance in terms of both Unweighted Average Recall (UAR) and Weighted Average Recall (WAR) metrics, achieving a UAR (WAR) of 57.09% (69.87%) on the DFEW dataset, and UAR (WAR) of 39.48% (49.34%) on the FERV39K dataset. Notably, SlowR50-SA operates with only eight frames of input at low temporal resolution, highlighting its efficiency. Furthermore, the algorithm has the potential to be integrated into Tactile Internet applications, where it can be used to enhance the user experience by providing real-time emotion feedback. SlowR50-SA can also be used to enhance virtual reality experiences by providing personalized haptic feedback based on the user’s emotional state. It can also be used in remote tele-care applications to detect signs of stress, anxiety, or depression in patients. Full article