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A tactile image sensor employing a camera is capable of obtaining rich tactile information through image sequences with high spatial resolution. There have been many studies on the tactile image sensors from more than 30 years ago, and, recently, they have been applied in the field of robotics. Tactile image sensors can be classified into three typical categories according to the method of conversion from physical contact to light signals: Light conductive plate-based, marker displacement- based, and reflective membrane-based sensors. Other important elements of the sensor, such as the optical system, image sensor, and post-image analysis algorithm, have been developed. In this work, the literature is surveyed, and an overview of tactile image sensors employing a camera is provided with a focus on the sensing principle, typical design, and variation in the sensor configuration.

The artificial tactile sensory system (ATSS) contributes to tactile sensation in human–machine interaction. However, it is been a challenge for them serving as the function comparable to the human tactile perception system (HTPS). The bioinspiration from human system is an optimal solution.Biomechanisms of the HTPS are systematically interpreted to inspire the development of ATSSs.Current biomimetic strategies and technologies in the sensing, transmitting, and processing components of ATSSs are addressed as an integral system. The sense of touch events, achieved by artificial tactile sensory systems (ATSSs), is a milestone in the progress of human–machine interactions. However, it has been a challenge for ATSSs to serve functions comparable with the human tactile perception system (HTPS). The biomimetic strategies and technologies inspired by HTPS are considered an optimal solution to this challenge. Recent studies have reported bioinspired strategies for improving specific aspects of ATSS performance, such as feature collection, signal conversion, and information computation. Here, we present a systematic interpretation of biomechanisms for HTPSs, and correspondingly, address biomimetic strategies and technologies contributing to ATSSs as an integral system. This review will benefit the development and application of ATSSs in the future.

The emulation of human multisensory functions to construct artificial perception systems is an intriguing challenge for developing humanoid robotics and cross‐modal human–machine interfaces. Inspired by human multisensory signal generation and neuroplasticity‐based signal processing, here, an artificial perceptual neuro array with visual‐tactile sensing, processing, learning, and memory is demonstrated. The neuromorphic bimodal perception array compactly combines an artificial photoelectric synapse network and an integrated mechanoluminescent layer, endowing individual and synergistic plastic modulation of optical and mechanical information, including short‐term memory, long‐term memory, paired pulse facilitation, and “learning‐experience” behavior. Sequential or superimposed visual and tactile stimuli inputs can efficiently simulate the associative learning process of “Pavlov's dog”. The fusion of visual and tactile modulation enables enhanced memory of the stimulation image during the learning process. A machine‐learning algorithm is coupled with an artificial neural network for pattern recognition, achieving a recognition accuracy of 70% for bimodal training, which is higher than that obtained by unimodal training. In addition, the artificial perceptual neuron has a low energy consumption of ∼20 pJ. With its mechanical compliance and simple architecture, the neuromorphic bimodal perception array has promising applications in large‐scale cross‐modal interactions and high‐throughput intelligent perceptions. Artificial visual‐tactile perceptual arrays for enhanced memory and neuromorphic computations have promising applications in the field of human‐computer interaction. This work combines mechanoluminescence materials with optoelectronic synapses, which enable tactile and visual perception, learning and memory individually and in concert. With its mechanical compliance and simple structure, this array holds promise for large‐scale cross‐modal interaction and high‐throughput intelligent perception.

Deducing the input signal for a tactile display to present the target surface (i.e., solving the inverse problem for tactile displays) is challenging. We proposed the encoding and presentation (EP) method in our prior work, where we encoded the target surface by scanning it using an array of piezoelectric devices (encoding) and then drove the piezoelectric devices using the obtained signals to display the surface (presentation). The EP method reproduced the target texture with an accuracy of over 80% for the five samples tested, which we refer to as replicability. Machine learning is a promising method for solving inverse problems. In this study, we designed a neural network to connect the subjective evaluation of tactile sensation and the input signals to a display; these signals are described as time-domain waveforms. First, participants were asked to touch the surface presented by the mechano-tactile display based on the encoded data from the EP method. Then, the participants recorded the similarity of the surface compared to five material samples, which were used as the input. The encoded data for the material samples were used as the output to create a dataset of 500 vectors. By training a multilayer perceptron with the dataset, we deduced new inputs for the display. The results indicate that using machine learning for fine tuning leads to significantly better accuracy in deducing the input compared to that achieved using the EP method alone. The proposed method is therefore considered a good solution for the inverse problem for tactile displays.

With the rise of the ‘her economy’, the influence of women’s consumer demand on furniture design is becoming increasingly important. The purpose of this study was to explore the relationship between female consumers’ visual and tactile perceptions of different wardrobe furniture materials and their psychological and sensory cognition. Based on the theory of Kansei engineering, a questionnaire was designed using a semantic differential scale and a seven-point Likert scale. Female participants were invited to rate 8 sets of perceptual vocabulary for 13 representative wardrobe furniture material samples through visual and tactile perception. SPSS 27 software was used to conduct reliability and validity tests, cluster analysis, and factor analysis on the experimental data. Cluster analysis categorized the materials into three types: natural flexible materials, patterned solid wood materials, and modern materials. Factor analysis identified two key dimensions: tactile perception and visual perception. These dimensions were used to analyze the differences in sensory cognition among the three material types in female consumers. This experiment provided theoretical support for the study of female consumers’ perceptual perception of wardrobe furniture materials, and at the same time provided rational references for designers to optimise the choice of materials in wardrobe furniture design based on the emotional needs of female users.

The quantitative characterization of tactile perception, which is crucial in the design of tactile devices, requires the tested samples to have individually and precisely controlled properties associated with the senses. In this work, we microfabricated such tactile samples and then quantitatively characterized tactile perception with a focus on roughness and dryness. In the roughness perception experiments, the tactile samples had a stripe pattern with ridge and groove widths that were individually controlled. The experimental results revealed that the feeling of roughness was more dominated by the width of the groove than that of the ridge and that conventionally used roughness parameters such as Sa and Sq were not sufficient for predicting roughness perception. In the dryness perception experiments, the tactile samples had a micropattern formed by dry etching and an array of squares. The experimental results revealed that dry perception had different properties when the feature sizes were below and above 30 µm, which may have been due to the effect of adhesion on friction. The proposed tactile samples were suitable for the quantitative and precise characterization of tactile perception.

This study proposes a tactile estimation method of molded plastic plates based on human tactile perception characteristics. Plastic plates are often used in consumer products. The tactile evaluation plays an important role in product development. However, physical quantities not taking into account human tactile perception have been employed in previous tactile estimation procedures. Hence, in this study, we adopted the vibrational thresholds of the mechanoreceptive units—FA I, FA II, SA I and SA II—for stimuli detection and developed a tactile estimation method for plastic plates that clarified the mechanoreceptive units related to tactile sensation. The developed tactile sensor consists of a base and a silicone rubber pad that contains strain gauges in it. We detected vibration during touch by the sensor and calculated the estimation of the firing values of the cutaneous mechanoreceptors, which are the essential data obtained by humans during tactile perception, in comparison to the amplitude spectrum of the vibration with the threshold amplitude of each mechanoreceptive unit. Simultaneously, we calculated the relationship between the normal and tangential forces recorded while the sensor ran over the samples. As a result of stepwise linear regression analysis using these values as explanatory variables, the evaluation scores for Soft were successfully estimated using the firing value of FA II and the relationship between normal/tangential forces, and the evaluation scores for Rough were estimated using the SA I firing value.

Tactile perception is inherently dynamic, relying on active manual exploration to extract information about motion and surface properties. Spatiotemporal inputs facilitate tactile motion perception by conveying information both direction and speed perception. Although previous studies have examined these features separately, the interactions between spatial and temporal features in shaping perceptual outcomes remain poorly understood. To address this gap, we conducted two psychophysical experiments in which tactile motion stimuli, varying in direction, speed and spatial frequency (wavelength), were delivered to the distal fingerpad of healthy participants, and then requested the participants to report their feedback directly. In Experiment I, we found that the anisotropic distortion of directional perceptual bias is quadrant-dependent, while variations in speed did not alter this general pattern. Experiment II revealed a dissociation between spatial and temporal contributions to perception. Spatial frequency primarily determined the overall pattern of perceptual bias, reflecting the structural properties of the stimulus. In contrast, speed modulates its dynamic expression by influencing the amplitude and phase of deviations. Additional psychometric function analyses indicated that tactile speed perception arises from a combination of linear and nonlinear processes. Collectively, these findings elucidate how the brain integrates spatiotemporal cues to construct a coherent tactile motion representation, thereby accounting for the systematic directional distortions and nonlinear speed estimation.

The grating orientation discrimination task (GOT) is a sensitive and reliable measure of tactile spatial resolution, or acuity. We used the GOT in three experiments to investigate the effects of hand posture and hand visibility on spatial acuity. Participant sex and experimental design were also manipulated. Healthy adult participants received brief touches to their index fingertips of grated, domed objects. Their task was to decide whether the gratings ran 'along' or 'across' their finger. Measures of the smallest grating width for which participants could reliably discriminate between orientations were recorded as threshold. Experiment 1 evaluated the effect of two- versus one-interval discrimination, hand used and participant sex. Experiments 2 and 3 evaluated the effects of hand visibility (visible or covered) and hand posture (in front or to the side). Females were better than males; the two-interval task resulted in lower thresholds than the one-interval task; and left and right hand thresholds were not significantly different. Most importantly, while hand visibility did not have a significant effect on the task, thresholds were affected by hand posture—worse when the hand was oriented to the side of the body than in front. These results replicate previously reported effects of sex (or finger size), but failed to replicate the so-called ‘visual enhancement of touch’ (VET) effect. We also report a meta-analysis of 27 VET studies, finding a significant effect of ‘non-informative’ vision on tactile perception. Our novel finding is that hand posture affects tactile acuity.

Background/Objectives: Research on pleasant tactile perception has primarily focused on C-tactile fibers found in hairy skin, with the forearm and face as common study sites. Recent findings of these fibers in hairless skin, such as the palms, have sparked interest in tactile stimulation on the hands. While studies have examined comfort and brain activity in passive touch, active touch remains underexplored. This study aimed to investigate differences in pleasant sensation and brain activity during active touch with stress balls of varying hardness. Methods: Forty healthy women participated. Using functional magnetic resonance imaging (fMRI), brain activity was measured as participants alternated between gripping stress balls of soft, medium, and hard hardness and resting without a ball. Participants rated hardness and comfort on a 9-point scale. Results: Soft stress balls were perceived as soft and comfortable, activating the thalamus and left insular cortex while reducing activity in the right insular cortex. Medium stress balls elicited similar perceptions and thalamic activation but with reduced right insular cortex activity. Hard stress balls caused discomfort, activating the insular cortex, thalamus, and amygdala while reducing anterior cingulate cortex activity. Conclusions: Soft stress balls may reduce aversive stimuli through perceived comfort, while hard stress balls may induce discomfort and are unlikely to alleviate stress.