Whenever we touch a surface with our fingers, we perceive distinct tactile properties that are based on the underlying dynamics of the interaction. However, little is known about how the brain aggregates the sensory information from these dynamics to form abstract representations of textures. Earlier studies in surface perception all used general surface descriptors measured in controlled conditions instead of considering the unique dynamics of specific interactions, reducing the comprehensiveness and interpretability of the results. Here, we present an interpretable modeling method that predicts the perceptual similarity of surfaces by comparing probability distributions of features calculated from short time windows of specific physical signals (finger motion, contact force, fingernail acceleration) elicited during unconstrained finger-surface interactions. The results show that our method can predict the similarity judgments of individual participants with a maximum Spearman's correlation of 0.7. Furthermore, we found evidence that different participants weight interaction features differently when judging surface similarity. Our findings provide new perspectives on human texture perception during active touch, and our approach could benefit haptic surface assessment, robotic tactile perception, and haptic rendering.

Pressing the fingertips into surfaces causes skin deformations that enable humans to grip objects and sense their physical properties. This process involves intricate finger geometry, non-uniform tissue properties, and moisture, complicating the underlying contact mechanics. Here we explore the initial contact evolution of dry and hydrated fingers to isolate the roles of governing physical factors. Two participants gradually pressed an index finger on a glass surface under three moisture conditions: dry, water-hydrated, and glycerin-hydrated. Gross and real contact area were optically measured over time, revealing that glycerin hydration produced strikingly higher real contact area, while gross contact area was similar for all conditions. To elucidate the causes for this phenomenon, we investigated the combined effects of tissue elasticity, skin-surface friction, and fingerprint ridges on contact area using simulation. Our analyses show the dominant influence of elastic modulus over friction and an unusual contact phenomenon, which we call friction-induced hinging.

Wearable tactile displays can create the illusion of touching real textures by applying vibrations to the finger as it moves across a virtual surface. There are many possible methods of modulating this vibratory content with finger movement, each potentially best suited to different texture length scales. Using a vibrotactile haptic ring paired with finger position tracking, here we explore the advantages of three vibration modulation schemes that scale the frequency or amplitude of applied vibrations as a function of finger velocity. Ongoing psychophysical experiments will characterize trade-offs between ease of control and perceived texture realism for frequencies associated with both coarse and fine textures.

One may notice a relatively wide range of tactile sensations even when touching the same hard, flat surface in similar ways. Little is known about the reasons for this variability, so we decided to investigate how the perceptual intensity of light stickiness relates to the physical interaction between the skin and the surface. We conducted a psychophysical experiment in which nine participants actively pressed their finger on a flat glass plate with a normal force close to 1.5 N and detached it after a few seconds. A custom-designed apparatus recorded the contact force vector and the finger contact area during each interaction as well as pre- and post-trial finger moisture. After detaching their finger, participants judged the stickiness of the glass using a nine-point scale. We explored how sixteen physical variables derived from the recorded data correlate with each other and with the stickiness judgments of each participant. These analyses indicate that stickiness perception mainly depends on the pre-detachment pressing duration, the time taken for the finger to detach, and the impulse in the normal direction after the normal force changes sign; finger-surface adhesion seems to build with pressing time, causing a larger normal impulse during detachment and thus a more intense stickiness sensation. We additionally found a strong between-subjects correlation between maximum real contact area and peak pull-off force, as well as between finger moisture and impulse.

Realistic display of tactile textures on touch screens is a big step forward for haptic technology to reach a wide range of consumers utilizing electronic devices on a daily basis. Since the texture topography cannot be rendered explicitly by electrovibration on touch screens, it is important to understand how we perceive the virtual textures displayed by friction modulation via electrovibration. We investigated the roughness perception of real gratings made of plexiglass and virtual gratings displayed by electrovibration through a touch screen for comparison. In particular, we conducted two psychophysical experiments with ten participants to investigate the effect of spatial period and the normal force applied by finger on roughness perception of real and virtual gratings in macro size. We also recorded the contact forces acting on the participants' finger during the experiments. The results showed that the roughness perception of real and virtual gratings are different. We argue that this difference can be explained by the amount of fingerpad penetration into the gratings. For real gratings, penetration increased tangential forces acting on the finger, whereas for virtual ones where skin penetration is absent, tangential forces decreased with spatial period. Supporting our claim, we also found that increasing normal force increases the perceived roughness of real gratings while it causes an opposite effect for the virtual gratings. These results are consistent with the tangential force profiles recorded for both real and virtual gratings. In particular, the rate of change in tangential force (DFT/dt) as a function of spatial period and normal force followed trends similar to those obtained for the roughness estimates of real and virtual gratings, suggesting that it is a better indicator of the perceived roughness than the tangential force magnitude.

Masking has been used to study human perception of tactile stimuli, including those created on haptic touch screens. Earlier studies have investigated the effect of in-site masking on tactile perception of electrovibration. In this study, we investigated whether it is possible to change the detection threshold of electrovibration at fingertip of index finger via remote masking, i.e. by applying a (mechanical) vibrotactile stimulus on the proximal phalanx of the same finger. The masking stimuli were generated by a voice coil (Haptuator). For eight participants, we first measured the detection thresholds for electrovibration at the fingertip and for vibrotactile stimuli at the proximal phalanx. Then, the vibrations on the skin were measured at four different locations on the index finger of subjects to investigate how the mechanical masking stimulus propagated as the masking level was varied. Finally, electrovibration thresholds were measured in the presence of vibrotactile masking stimuli. Our results show that vibrotactile masking stimuli generated sub-threshold vibrations around fingertip and, hence, probably did not mechanically interfere with the electrovibration stimulus. However, there was a clear psychophysical masking effect due to central neural processes. Electrovibration absolute threshold increased approximately 0.19 dB for each dB increase in the masking level.

Both vision and touch contribute to the perception of real surfaces. Although there have been many studies on the individual contributions of each sense, it is still unclear how each modality's information is processed and integrated. To fill this gap, we investigated the similarity of visual and haptic perceptual spaces, as well as how well they each correlate with fingertip interaction metrics. Twenty participants interacted with ten different real surfaces from the Penn Haptic Texture Toolkit by either looking at or touching them and judged their similarity in pairs. By analyzing the resulting similarity ratings using non-metric multi-dimensional scaling (NMDS), we found that surfaces are similarly organized within the three-dimensional perceptual spaces of both modalities. Also, between-participant correlations were significantly higher in the haptic condition. In a separate experiment, we obtained the contact forces and accelerations acting on one finger interacting with each surface in a controlled way. We analyzed the collected fingertip interaction data in both the time and frequency domains. Our results suggest that the three perceptual dimensions for each modality can be represented by roughness/smoothness, hardness/softness, and friction, and that these dimensions can be estimated by surface vibration power, tap spectral centroid, and kinetic friction coefficient, respectively.

Future touch screen applications will include multiple tactile stimuli displayed simultaneously or consecutively to single finger or multiple fingers. These applications should be designed by considering human tactile masking mechanism since it is known that presenting one stimulus may interfere with the perception of the other. In this study, we investigate the effect of masking on the tactile perception of electrovibration displayed on touch screens. Through conducting psychophysical experiments with nine participants, we measured the masked thresholds of sinusoidal electrovibration bursts (125 Hz) under two masking conditions: simultaneous and pedestal. The masking signals were noise bursts, applied at five different sensation levels varying from 2 to 22 dB SL, also presented by electrovibration. For each participant, the thresholds were elevated as linear functions of masking levels for both masking types. We observed that the masking effectiveness was larger with pedestal masking than simultaneous masking. Moreover, in order to investigate the effect of tactile masking on our haptic perception of edge sharpness, we compared the perceived sharpness of edges separating two textured regions displayed with and without various types of masking stimuli. Our results suggest that sharpness perception depends on the local contrast between background and foreground stimuli, which varies as a function of masking amplitude and activation levels of frequency-dependent psychophysical channels.

In this study, we investigated the effect of input voltage waveform on our haptic perception of electrovibration on touch screens. Through psychophysical experiments performed with eight subjects, we first measured the detection thresholds of electrovibration stimuli generated by sinusoidal and square voltages at various fundamental frequencies. We observed that the subjects were more sensitive to stimuli generated by square wave voltage than sinusoidal one for frequencies lower than 60 Hz. Using Matlab simulations, we showed that the sensation difference of waveforms in low fundamental frequencies occurred due to the frequency-dependent electrical properties of human skin and human tactile sensitivity. To validate our simulations, we conducted a second experiment with another group of eight subjects. We first actuated the touch screen at the threshold voltages estimated in the first experiment and then measured the contact force and acceleration acting on the index fingers of the subjects moving on the screen with a constant speed. We analyzed the collected data in the frequency domain using the human vibrotactile sensitivity curve. The results suggested that Pacinian channel was the primary psychophysical channel in the detection of the electrovibration stimuli caused by all the square-wave inputs tested in this study. We also observed that the measured force and acceleration data were affected by finger speed in a complex manner suggesting that it may also affect our haptic perception accordingly.

In this study, we have investigated the human roughness perception of periodical textures on an electrostatic display by conducting psychophysical experiments with 10 subjects. To generate virtual textures, we used low frequency unipolar pulse waves in different waveform (sinusoidal, square, saw-tooth, triangle), and spacing. We modulated these waves with a 3kHz high frequency sinusoidal carrier signal to minimize perceptional differences due to the electrical filtering of human finger and eliminate low-frequency distortions. The subjects were asked to rate 40 different macro textures on a Likert scale of 1-7. We also collected the normal and tangential forces acting on the fingers of subjects during the experiment. The results of our user study showed that subjects perceived the square wave as the roughest while they perceived the other waveforms equally rough. The perceived roughness followed an inverted U-shaped curve as a function of groove width, but the peak point shifted to the left compared to the results of the earlier studies. Moreover, we found that the roughness perception of subjects is best correlated with the rate of change of the contact forces rather than themselves.

The perceived intensity of electro vibration can be altered by modulating the amplitude, frequency, and waveform of the input voltage signal applied to the conductive layer of a touchscreen. Even though the effect of the first two has been already investigated for sinusoidal signals, we are not aware of any detailed study investigating the effect of the waveform on our haptic perception in the domain of electrovibration. This paper investigates how input voltage waveform affects our haptic perception of electrovibration on touchscreens. We conducted absolute detection experiments using square wave and sinusoidal input signals at seven fundamental frequencies (15, 30, 60, 120, 240, 480 and 1920 Hz). Experimental results depicted the well-known U-shaped tactile sensitivity across frequencies. However, the sensory thresholds were lower for the square wave than the sinusoidal wave at fundamental frequencies less than 60 Hz while they were similar at higher frequencies. Using an equivalent circuit model of a finger-touchscreen system, we show that the sensation difference between the waveforms at low fundamental frequencies can be explained by frequency-dependent electrical properties of human skin and the differential sensitivity of mechanoreceptor channels to individual frequency components in the electrostatic force. As a matter of fact, when the electrostatic force waveforms are analyzed in the frequency domain based on human vibrotactile sensitivity data from the literature [15], the electrovibration stimuli caused by square-wave input signals at all the tested frequencies in this study are found to be detected by the Pacinian psychophysical channel.