Human perceptual and affective responses change dynamically when stimuli are experienced. In this study, we developed a method for modeling the causal structures of affective dynamics using time-series data. Using the temporal dominance of sensations method, perceptual and affective data were collected from individuals eating strawberries, and the resulting time-series data were mathematically represented using a vector auto-regression model. Multihierarchical and multidimensional causality structures that explain the temporal evolution of perceptual and affective responses were then established based on Granger causality and information criterion. The established model suggests how affective and preferential responses are triggered following exposure to stimuli. We also assessed the quantitative and semantic validity of the model.

For industrial purposes such as product design, texture displays should deliver a quality sense of touch to users. We have developed a vibrotactile texture display that uses real materials such as fabric, wood, and leather to enable the presentation of quality textures to users. By applying two types of vibrotactile stimuli to users’ finger pads through the materials, their fine and macro roughness sensations can be selectively modified while maintaining their original perceptual characteristics. This approach is effective for different types of textures such as paper, wood, leather, and cloth unless they possess strong damping properties that may attenuate the vibratory stimuli applied through them.

A human can judge the hardness of an object based on the damped natural vibration caused by tapping the surface of the object using a fingertip. In this study, we investigated the influence of the dynamic characteristics of vibrations on the hardness perceived by tapping. Subjectively reported hardness values were related to the dynamic stiffness of several objects. The dynamic stiffness, which characterizes the impulsive response of an object, was acquired across the 40–1,000 Hz frequency range for cuboids of 14 types of materials by administering a hammering test. We performed two psychophysical experiments—a ranking task and a magnitude-estimation tasks—wherein participants rated the perceived hardness of each block by tapping it with a finger. We found that the perceptual effect of dynamic stiffness depends on the frequency. Its effect displayed a peak around 300 Hz and decreased or disappeared at higher frequencies, at which human perceptual capabilities are limited. The acquired results help design hardness experienced by products.

In the last decade, temporal dominance of sensations (TDS) methods have proven to be potent approaches in the field of food sciences. Accordingly, thus far, methods for analyzing TDS curves, which are the major outputs of TDS methods, have been developed. This study proposes a method of bootstrap resampling for TDS tasks. The proposed method enables the production of random TDS curves to estimate the uncertainties, that is, the 95% confidence interval and standard error of the curves. Based on Monte Carlo simulation studies, the estimated uncertainties are considered valid and match those estimated by approximated normal distributions with the number of independent TDS tasks or samples being 50–100 or greater. The proposed resampling method enables researchers to apply statistical analyses and machine-learning approaches that require a large sample size of TDS curves.

Understanding the tribological phenomena when fingers slide over soft surfaces such as skin is important for many practical applications. Therefore, this article analyzed the coefficients of friction for a bare finger sliding over artificial skin with different hardness under dry and lubricated surface conditions. This article contrasts with previous research that predominantly analyzed the contact between skin and hard surfaces or probes. Under dry conditions, the coefficient of friction was constant for artificial skins that were harder than the finger pad, irrespective of the normal force of the finger. However, the coefficient of friction decreased with increasing normal force for softer artificial skins. When the surface of the artificial skin model was lubricated with mica, the coefficient of friction exhibited normal-force dependence only for soft artificial skins, similar to the observations under dry conditions. This effect was due to the deformation friction; thus, the coefficient of friction increased as the normal force increased. Conversely, when the model was lubricated with ${\mathrm{ TiO}}_2$, the coefficient of friction depended on the normal force for all hardness levels. These findings provide insights into the friction experienced during skin-skin or skin-soft material contact under dry and lubricated conditions that can easily occur in daily life. Thus, the results of this study can be useful for the development of skin care products or assistive robots involving human-robot contact.

Graphical Abstract A friction-variable touch panel is capable of presenting virtual bumps and holes on its flat surface through the control of the surface friction when a fingertip slides over it. To improve the presentation, we developed a friction model of a fingertip sliding over a sinusoidal surface with an amplitude of 0.5–2.5 mm and a spatial wavelength of 20–50 mm. When a metal ball rolls over a wavy surface with a low friction and contact area, the ratio of the horizontal force to the normal force is equal to the gradient of the surface (this is referred to as the ball bearing model) and is hardly affected by the normal load and rolling speed. In contrast, the profile of the force ratio of a sliding finger is substantially skewed and affected by the sliding direction and normal force exerted by the finger. To model this skewed force ratio, we formulated the asymmetric pressure distribution in the finger-surface contact area and used the effects of the adhesion friction to model the dependency of the force ratio on the normal force and sliding direction. The developed model of a bare finger with these features was found to sufficiently simulate the experimentally observed force ratios. The model can be easily applied to friction-variable touch panels and enables the achievement of a wide variety of haptic contents with macroscopically concave or convex surfaces.