ABSTRACT This exploratory study investigated motivations for using fantasy, monster, and animal-shaped sex toys through qualitative analysis of public online forum discussions. Despite growing commercial availability of these products, research on non-human sex toys remains notably absent from scholarly literature. Using thematic analysis, we identified four primary motivational themes: Seeking Novelty (pursuit of novel tactile sensations), Valuing Aesthetics Over Verisimilitude (preference for artistic design over anatomical realism), Finding Pleasure in the Taboo (arousal from perceived socially forbidden elements), and Paraphilic Harm Reduction (ethical expression of zoophilic interests). These findings extend previous research on sex toy motivations beyond conventional ‘fun’ and ‘novelty’ factors to include aesthetic considerations and harm-reduction frameworks. The preference for non-anatomical designs aligns with emerging evidence that realistic features do not predict sex toy popularity. Notably, the harm reduction theme parallels recent findings on sex doll ownership that challenge assumptions about increased risk behaviours. This study provides initial insights into a previously unexamined aspect of sexual expression and suggests these products may serve beneficial purposes beyond mere novelty. These results have important harm reduction implications for clinicians, policy makers, and front line staff who deal with human sexuality topics.

Bioinspired flexible piezoresistive sensor with cross-gradient architecture for high-performance tactile sensing.

Traditional heterostructures, bound by covalent bonds, are limited to materials with similar lattice structures. Utilizing van der Waals (vdW) forces to assemble low-dimensional materials allows for the integration of diverse materials, overcoming lattice-matching and processing constraints, and enabling the creation of versatile vdW-material-based composites. A transition metal dichalcogenide two-dimensional (2D) material, TaS2, has undergone extensive research in various fields but challenges are encountered in the enhancement of its thermoelectric performance. Herein, one-dimensional (1D) silver nanowires (Ag NWs) have been integrated with 2D TaS2via vdW forces, to form 1D/2D vdW-material-based composites. With further addition of polymer binder, PEDOT:PSS, a flexible 1D/2D film was developed. The power factor was enhanced by nearly a factor of 5 due to the bridging effect. The tensile strength was tripled due to the bricks and mortar structure. About 20 nW power was generated by a six-legged module at a temperature difference of 30 K. Demonstrations of the composite in tactile, respiration, and strain sensors showed significant promise for assisting the visually impaired with language support and enabling real-time measurements of respiratory rates and physiological conditions for health monitoring. This study underscores the vast potential of 1D/2D vdW composite films for applications in wearable nanogenerators, sensors, and beyond.

By integrating a VGG network and leveraging a synergistic triboelectric–piezoresistive mechanism, the dual-modal flexible tactile sensor achieves a material recognition accuracy of 98.77% in complex environments.

Tactile sensors enabling human-like behavior to identify surface microstructures are essential for humanoid robots to interact precisely with complex environments. Most existing approaches use materials responding to dynamic forces and rely on machine learning methods to distinguish various types of surface microstructures. Quantitatively profiling the surface microstructures is significant but challenging, especially under the requirement of eliminating external bulky motion-control systems. Here, a quantitative tactile surface profiling strategy is presented through time-domain analysis of the signal of a piezoelectric twin-film architecture. The architecture uses two parallel piezoelectric films with a fixed interlayer distance, generating twin voltage signals with a time delay, which is inversely proportional to the scanning speed, and consequently removes the need for motion control. The microstructure heights correlate with the peak voltages, whereas widths and edge profiles are derived from the temporal analysis of distinct signal features. Tactile and in situ measurement of surface microstructures is demonstrated with high accuracy (>99.2%) over a broad height range of 1-1000µm. Furthermore, in-line quality inspection during additive manufacturing is realized by quantitatively profiling the surface microstructures. This work will drive innovations in tactile technologies that emulate and potentially surpass human capabilities and advance in situ surface characterization methods.

ABSTRACT The rapid advancement of underwater vehicles and the Internet of Underwater Things (IoUT) necessitates core sensing components capable of withstanding high‐pressure, low‐visibility, and high‐humidity environments. Although tactile perception mechanisms present a promising alternative to traditional underwater sensing, existing reviews lack a systematic analysis of the interdisciplinary integration of triboelectric nanogenerators (TENGs). This review addresses this gap by providing a comprehensive analysis of the latest developments in TENG‐based underwater tactile sensors, with a focus on their self‐powered operation, material versatility, and bio‐inspired design innovations. Our survey encompasses triboelectric principles, waterproofing strategies, bionic structures, material properties, and signal processing. Notably, we emphasize the transformative potential of TENGs in achieving zero‐power‐consumption and high‐sensitivity sensing—key to overcoming challenges in long‐term energy autonomy and adaptability to extreme marine conditions. The application potential in underwater mobile equipment, wearable devices, and monitoring networks is elucidated, alongside a discussion of technical challenges and future trends. This work ultimately establishes a foundational framework for next‐generation underwater perception systems by advocating for the synergy of TENG technology with artificial intelligence and sustainable material science.

Abstract Achieving human‐like tactile and pain perception is crucial for intelligent robot systems. However, current sensor technologies often fail to simultaneously detect both stimuli or require structurally complex designs. In this study, a highly sensitive tactile‐pain dual‐function sensor enabled by pollen‐derived biochar materials is presented. The biochar particles are synthesized and filled in an elastic nanofiber membrane to serve as the sensitive layer of a pressure sensor. Owing to the unique sea urchin‐like microstructure of the biochar particles, this sensor shows relatively moderate resistance change under low pressure but significantly sharper response upon needle prick or excessively high pressure, thereby distinguishing the low‐threshold tactile sensations and high‐threshold pain sensations. Furthermore, this dual‐function sensor achieves a maximum sensitivity of 105.6 kPa −1 , and can operate over a wide pressure range (0.4 Pa–3000 kPa). By integrating a 4 × 4 array of these sensors onto a dexterous robotic hand, the intelligent capabilities of object shape recognition and self‐protection upon harmful tasks, significantly enhancing the efficiency and safety of robotic grasping operations are demonstrated.

Electrospinning is a versatile technique for fabricating triboelectric materials. Although carbonization can significantly improve the electrical conductivity of fiber membranes, their application as triboelectric layers remains underexplored. In this work, a copper-silver (CuAg) alloy-doped carbon nanofibers (CuAg@CNFs) membrane was designed and employed as a triboelectric layer to enhance the accuracy and sensitivity of self-powered tactile sensors based on triboelectric nanogenerators (TENGs) for material identification. The CuAg@CNFs membrane, obtained by electrospinning and subsequent thermal conversion, exhibits a three-dimensional conductive network with in situ-generated alloy nanoparticles. Such a structural configuration promotes efficient charge migration across the interface, thereby enhancing electrical output. The fabricated CuAg@CNFs based-TENG delivers an output voltage of 4.3 V and a charge density of 40 nC m-2, maintaining stable operation over repeated cycles. By correlating triboelectric signals with material surface characteristics, an intelligent sensing framework integrating a convolutional neural network (CNN) was constructed. The system achieved a recognition accuracy of 99.6% across ten materials and maintained high discriminative capability in complex environments. During real-time operation, the recognition accuracy for four types of material categories (aluminum, board, glass, and plastic) reached 100, 93, 99, and 97.5%, respectively. This study demonstrates a feasible strategy for constructing high-performance self-powered sensing systems through the synergistic combination of material design and machine learning algorithms.

Self-initiated actions often generate sensory signals perceived to be less intense than identical signals generated externally. This phenomenon, known as sensory attenuation, is particularly robust for nonpainful tactile sensations. For pain, however, even if the stimulation is self-generated and predictable, it remains painful, albeit sometimes slightly less intense. This difference may reflect the functional divergence between pain and nonpainful sensations, with the sense of agency playing a central role in this distinction. Across 2 experiments involving 61 pain-free adults, we investigated the attenuation of self-induced pain and nonpainful sensations across different stimulation modalities, contexts, and agency levels. We found that self-induced attenuation depended on stimulation modality rather than intensity, with significant reductions for modalities involving strong motoric components and high spatiotemporal alignment (eg, mechanical pressure), in line with the internal forward model. Individuals' trait agency played a pivotal role, with stronger agency associated with enhanced attenuation of nonpainful sensations and mild pain, but reduced attenuation of intense pain. Sex differences also emerged with stronger attenuation effects in men, who also reported higher levels of agency. This study is the first to show that trait-level agency differentially modulates attenuation for painful and nonpainful sensations and the first to explore sex differences. By comparing pain with nonpainful touch, we proposed that self-induced sensations are not attenuated uniformly but shaped by evolutionary priorities such that socially or playfully mediated sensations are more readily suppressed, while high-threat sensations like pain resist qualitative suppression to preserve their protective function.

An innovative in vitro system unveils IGF1R signaling regulating Merkel cell generation.

Tactile perception of the skin is a key factor for consumers when evaluating skincare products, yet conventional sensory assessments are subjective, costly and often lack clear physical interpretations. This study aims to bridge this gap by developing a tactile sensor that quantifies physical parameters relevant to skin feel and combines these measurements with sensory evaluation. A tactile sensor with a stainless-steel probe replicating a human fingerprint was developed to measure physical parameters-specifically, vibration and friction-during controlled rubbing on the cheek. Simultaneously, blinded sensory evaluations were performed by assessors rating six attributes: smooth-rough, moisturized-dry, soft-hard (surface), soft-hard (base), elastic-not elastic and oily-not oily. Multiple regression analyses were conducted using vibration features and friction coefficients as independent variables and sensory evaluation scores as dependent variables. Regression analysis revealed that perceived smoothness (smooth-rough) was predicted by amplitudes of high-frequency vibration (R2 = 0.708; adjusted R2 = 0.676). Moistness (moisturized-dry) was best predicted by a combination of high-frequency vibration amplitude and friction coefficients (R2 = 0.584; adjusted R2 = 0.538). No significant regression models were obtained for the other sensory attributes. These findings highlight the potential of objective, instrument-based tactile measurements to elucidate the physical basis of sensory evaluation terms in skincare. This approach may enhance the training of sensory evaluation panels and improve the consistency and reliability of product assessment, ultimately supporting more effective product development.

Slips and falls are a major cause of workplace injuries, often exacerbated by worn shoe outsoles. Tread wear leads to increased under-shoe fluid pressures and increased slip risk. Frustrated total internal reflection (FTIR) technology offers a cost-effective approach for assessing the slip risk for worn shoes. However, current FTIR-based image analysis methods are not fully automated, and existing fluid pressure models have not been applied to the complex geometries that form on actual worn shoes. This study aimed to advance the use of FTIR for assessing shoe slip risk by: (1) assessing the accuracy of a U-Net network (a convolution neural network) in automatically identifying contact regions from FTIR images, and (2) investigating the association between model-predicted fluid pressures of the identified worn regions and slip outcome, coefficient of friction (COF) and experimentally measured peak fluid pressures. Fifty-five participants wearing worn slip-resistant shoes completed walking trials, including unexpected exposure to a slippery surface. Experimental peak fluid pressures were recorded using an array of fluid pressure sensors embedded in the floor and slip outcome was determined from heel kinematics. The COF was measured with a mechanical slip testing device. The shoes from the participants were scanned with a FTIR device. The U-Net was able to predict contact regions that overlapped with the ground truth contact regions by 80%. Higher predicted peak fluid pressures were associated with higher experimentally measured peak fluid pressures (R2 = 0.22), lower COF values (R2 = 0.50), and increased slip risk (p = 0.007). In conclusion, this study demonstrates the feasibility of using FTIR technology combined with convolutional neural networks and hydrodynamic modelling to automate the evaluation of slip risk due to the shoe’s worn condition.

Osseoperception refers to the mechanosensory feedback generated through dental implants despite the absence of the periodontal ligament (PDL). This phenomenon plays a key role in patient adaptation, proprioception, and long-term success of implant-supported prostheses. While often overshadowed by osseointegration, osseoperception provides essential insights into implant functionality and neurosensory integration. This review aims to explore the biological mechanisms of osseoperception, highlight the influence of peri-implant mechanoreceptors, muscles, mucosa, and temporomandibular joint in contributing to it, and describe the clinical implications, including methods for evaluating active and passive tactile sensibility. The review further integrates recent advances and proposes future directions for enhancing implant-mediated sensory feedback.

ABSTRACT Replicating the natural ability to perceive softness in skin‐inspired tactile sensors is vital for the advancement of robotic manipulation and object classification. Humans sense softness through the activation of specific skin receptors, which are sensitive to pressure and lateral strain. Current electronic skins (eSkin) mimic this dual functionality by detecting both normal pressure and lateral strain. However, these sensors are challenging to fabricate and often have large spatial footprints, limiting their integration into high‐density arrays. To overcome these challenges, this work presents an all‐elastomer sensor for tactile detection of softness, combining a parallel‐plate capacitor structure with a serpentine piezoresistive strain sensor in a vertically stacked design. Conductive carbon structures, digitally laser patterned and embedded in a styrene‐ethylene‐butylene‐styrene (SEBS) thermoplastic elastomer, serve as robust and modifiable electrodes. The device displays the ability to differentiate moduli between 74 kPa and 1.49 MPa. We conduct a parametric study to evaluate the effects of object dimensions, materials choices, and design parameters on sensor performance. Importantly, we investigate the sensor performance when mounted onto a soft substrate, analogous to the human fingertip or robotic digit. Overall, this work highlights the potential of z‐directionally stacked sensing components with tunable properties to realize compact, multimodal devices.

This review delves into the cutting-edge advancements in the bioinspired flexible tactile sensors and their transformative role in enabling smart soft robots with embodied intelligence. Drawing inspiration from the multifunctionality of human skin, tactile sensors are desired to include similar mechanoreceptor, proprioception, and environmental responsiveness. This review begins by outlining fundamental design principles that mimic the hierarchical structure and distributed sensing networks of human skin. The biomimetic design and sensing principles of different flexible tactile sensors are then explained and compared, including pressure, temperature, and strain sensors. The state-of-the-art manufacturing methods, including direct ink writing, fused deposition modeling, digital light processing and material jet printing, are also introduced. By summarizing typical applications of these tactile sensors in smart soft robots, delicate object manipulation, human-robot collaboration, medical prosthetics, and adaptive locomotion are primarily discussed. Finally, it is promising to integrate innovations in fatigue-resistant elastomers, nanometer-scale 3-dimensional manufacturing, and artificial intelligence as potential elements to create next-generation of tactile sensors in the near future. By bridging biomimetic design, soft materials and robotics, this review aims to equip researchers and engineers with the knowledge to develop the tactile systems that push the boundaries of autonomy, safety, and interaction in soft robotics.

Currently, triboelectric nanogenerator (TENG)-based tactile sensors demonstrate considerable effectiveness in material type recognition. However, challenges remain regarding the stability of triboelectric materials and low precision when applied to the recognition of material surface roughness. To address these issues, the present study focuses on the preparation of a template of unconventional micro-nanostructure using recycled polylactic acid (PLA) materials. By meticulously designing and fabricating polydimethylsiloxane (PDMS)-based elastic triboelectric materials with well-defined concave-convex structures by the template method, a suitable micro-nanoarchitecture was chosen to enhance the triboelectric effect and improve sensing accuracy. To be precise, enhancing the roughness recognition accuracy of the tactile sensor through a triboelectric material surface structure management strategy was developed. Among the various concave-convex structures, the TENG device with a specific micro-nanostructure surface (roughness: 0.18 μm and maximum depth: 0.78 μm) exhibited the highest output voltage and charge density, reaching values of 4.9 V and 3.9 μC/m2, respectively. More importantly, the mapping relationship between the strain field distribution (or signal waveform characteristics) and the surface characteristics of the contacting material becomes clearer and more accurate with the establishment of special micro-nanostructures on the triboelectric material surface, thereby improving the recognition accuracy of the material surface roughness. Hence, by integrating deep machine learning and triboelectric effects, and combining signal collecting, data processing, and display modules, a material sensing system integrating high-precision TENG sensors was developed. It can monitor the different roughnesses of the object surface in real time in the natural environment, approximately 93% (0.027 mm), 78% (0.10 mm), and 82% (0.12 mm). Finally, this strategy can provide robots with richer and more accurate sensing capabilities.

Underwater tactile force sensing is crucial for achieving nondestructive and stable object manipulation in ocean robotics, especially in deep-sea environments where traditional vision-based methods are not available due to extreme darkness. However, deep-sea high hydrostatic pressure (>10 MPa) brings in serious interferences on tactile force measurements (<0.01 MPa), leading to few available deep-sea tactile sensors. To solve this problem, this paper develops a biomimetic deep-sea three-dimensional force sensor (3D-DSFS) inspired by the excellent adaptability of deep-sea organisms, where an open lattice sensing layer was developed by flexible 3D printing to balance internal and external pressures of sensors, allowing it to withstand extreme deep-sea hydrostatic pressures. Also, mimicking the hierarchical architecture of human skin, a stratified magnetoelastic sensor was developed for 3D force monitoring. In laboratory pressure-chamber tests, the results demonstrate that the 3D-DSFS is robust to hydrostatic pressures (signals drift <5% within 0-100 MPa) and can reliably detect static and dynamic 3D forces (average error <5%). Integrated into an underwater robotic gripper operating in about 100-m real-world deep-sea environments, the 3D-DSFS can still reliably monitor 3D forces. The 3D-DSFS was used for real-time robotic grasping control, achieving nondestructive and antislippage grasping (unlike sensorless grippers causing damage or slippage). With excellent deep-sea adaptability and accurate 3D force sensing, the 3D-DSFS is anticipated to improve deep-sea robotic operations for ocean engineering fields.

BackgroundIn hip arthroscopic surgery, probing the acetabular labrum with an arthroscopic probe prior to treatment is considered important for determining the appropriate treatment area. However, there have been only a few reports that have quantitatively evaluated this process. These studies have shown that by quantitatively measuring the reactive force of the labrum during probing, a significant decrease in reactive force is observed when the continuity between the labrum and the adjacent acetabular bone is disrupted. Furthermore, they have demonstrated that the reactive force can recover following repair. Nevertheless, it remains unclear whether the intrinsic mechanical properties of the labrum itself influence the probing measurements.ObjectiveHere, we investigated the relationship between two parameters by the probing force of the labrum in cadaveric tissue and its mechanical properties using a tensile testing machine.MethodsTwelve specimens of the pelvis and proximal femur were obtained. The donors included three men and five women who had a mean age of 64.1 years at the time of death. All specimens were screened radiographically to confirm the absence of osseous abnormality. Each specimen was mounted with a special device and each femur was dislocated in order to simulate hip arthroscopy.Labrum resistance was measured by the probing device. Then, the labrum was excised in segments measuring 15–25 mm in length. The stiffness and the elastic modulus of the specimens were measured by an in-house tensile test device. Spearman’s rank correlations were calculated between the probing force and the mechanical properties of the acetabular labrum.ResultsThe stiffness and the tensile elastic modulus showed a moderate correlation with the probing force (R=0.74; stiffness, R=0.65; tensile elastic modulus).DiscussionsIt is important to keep in mind that the tactile sensation transmitted to the hand during labral probing, which reflects the resistance force of the labrum, may also be influenced by the mechanical properties of the labrum itself.

In the realm of sensing, piezoionic systems have emerged as innovative tools for perceiving tactile sensations through mechanical-to-ionic transduction, mimicking biological signal production and transmission. To date, the biomimetic transduction mechanism and strategies for engineering the transduction efficiency remain not fully understood and underutilized. This review provides the fundamentals of mechanical-to-ionic transduction for efficient self-powered sensing, identifying the most crucial structural and operating parameters governing the generation of a transient signal output with respect to the migration and redistribution of ions upon mechanical stimulation. It also examines the recent strategies for efficiently converting mechanical keystrokes into electrical signals through performance-driven structural design, thereby maximizing piezoionic voltage generation. This involves engineering ion transport and fluid flow through porosity, microphase separation, conductive pathways and structural gradients. With respect to piezoionic effect-based applications, this review highlights the promising potential of polymeric, ionic materials in soft wearable electronics, ionic skins, tissue engineering, biointerfaces and energy harvesting.

In the current study, the surface characteristics and deformation behavior of raw and washed denim fabrics were investigated using Tactile Sensation Analyzer (TSA) which measures surface variations through sound analysis and determines out-of-plane deformation behavior during the deformation test phase. A total of 30 denim fabrics with various raw materials and production parameters were examined. Two different denim washing processes were applied to the raw denim fabrics, one involving cellulase enzyme and the other combined with pumice stones. The effects of washing on structural properties, surface characteristics, deformation, elasticity, hysteresis, plasticity, and tactile comfort were analyzed. The results indicated that denim washing significantly increased the thickness and decreased the magnitude of micro-surface variations across all tested samples, and most fabrics exhibited a less rigid structure after washing. It was detected that enzyme washing has a moderate effect on fabric properties. Meanwhile, the combination of cellulase enzyme and pumice stones resulted in significant improvements in surface smoothness, fullness, unit mass, deformability, elasticity and total hand scores.