Sensory words may facilitate certain haptic exploratory procedures in facial cosmetics

Augmenting perceived stickiness of physical objects through tactile feedback after finger lift-off

Haptic Augmented Reality (HAR) is a method that actively modulates the perceived haptics of physical objects by presenting additional haptic feedback using a haptic display. However, most of the proposed HAR research focuses on modifying the hardness, softness, roughness, smoothness, friction, and surface shape of physical objects. In this paper, we propose an approach to augment the perceived stickiness of a physical object by presenting additional tactile feedback at a particular time after the finger lifts off from the physical object using a thin and soft tactile display suitable for HAR. To demonstrate this concept, we constructed a thin and soft tactile display using a Dielectric Elastomer Actuator suitable for HAR. We then conducted two experiments to validate the effectiveness of the proposed approach. In Experiment 1, we showed that the developed tactile display can augment the perceived stickiness of physical objects by presenting additional tactile feedback at appropriate times. In Experiment 2, we investigated the stickiness experience obtained by our proposed approach and showed that the realism of the stickiness experience and the harmony between the physical object and the additional tactile feedback are affected by the frequency and presentation timing of the tactile feedback. Our proposed approach is expected to contribute to the development of new applications not only in HAR, but also in Virtual Reality, Mixed Reality, and other domains using haptic displays.

Talk to us about your skin: The relationship between spoken language and haptic exploratory procedures

OBJECTIVE

To enhance satisfaction, the cosmetics industry needs to clearly understand consumers' descriptions of their key tactile preferences. It is difficult for researchers to understand verbal descriptions from people whose native language is different from their own. Previous research has implied that some sensory words with the same lexical meanings have been observed in different haptic exploratory procedures (HEPs). Therefore, our study aims to investigate and understand the key tactile perceptions of people from five different countries based on their descriptions and their HEPs.

METHODS

In Experiment 1, 1545 participants living in the US, Japan, China, Italy, and Thailand described their major tactile perceptions as efficacy in skincare, and we analysed the frequency of each word used in their answers. In Experiment 2, we confirmed the task to observe HEPs for Chinese, Italian, and Thai participants. A total of 24 participants in China, 33 participants in Italy, and 30 participants in Thailand freely explored their faces with their hands and answered which side more closely matched the major tactile adjectives. Experts classified the observed HEPs into six classifications within two categories and three contact area sizes and investigated the cultural differences.

RESULTS

More than 2% of the Chinese, Italian, Thai, US, and Japanese participants described 33, 20, 29, 22, and 18 words, respectively, as efficacy in skincare. Verified words that described the major tactile perceptions in each native language had the same meanings as moistness, firmness, softness, smoothness, and so on. We could confirm the HEPs of these major feelings for the participants from each culture. Chinese and Thai participants' HEPs for moistness or softness were observed with a pressing movement. Conversely, Italian participants' HEPs for moistness or softness were observed with a rubbing movement.

CONCLUSION

This study showed that words with the same lexical meanings evoked different HEPs. The results imply that different HEPs can provide different physical stimuli on the skin. Therefore, it is important to survey both objects and HEPs to better understand the tactile experience.

Surface shape alters perceived material softness

When a human strokes the surface of an object with his/her finger, the surface shape influences the perceived softness of the object. This study introduced a curved surface softness illusion, which alters the perception of material softness. When a surface with curvature is felt by sliding a finger over it, it feels softer than a flat surface made of the same material. In contrast, a rugged surface is perceived as harder. This illusion indicates that, in addition to mechanical hardness, humans judge an object's softness based on its surface shape.

Skin quality sensor to evaluate vibration and friction generated when sliding over skins

OBJECTIVE

The mechanical condition and tactile evaluation of skin are essential for the development of skin care products. Most of the existing commercial instruments and studies aim to evaluate the skin surface by pressing it for hardness or by using imaging sensors, but there have been few instrumental measurements employing rubbing motion. Here, we have developed a sensor specialized for tactile sensation and the contact phenomenon during skin rubbing.

METHODS

The developed sensor has three features: It can measure body parts including cheeks and arms, automate the rubbing motion of the probe and measure vibration and friction simultaneously. It is hand-held, with metal probes that rub the skin surface while rotating under a motor drive; it has an accelerometer and a force sensor beneath the probe measuring vibration and friction forces. To evaluate the validity of the sensor's measurements, artificial skin models were measured using the developed sensor and commercially available sensors and the results were compared. The relationship between the sensor output, surface roughness measurement and sensory evaluation was also investigated. Additionally, we evaluated the inter-rater reliability when measuring actual skin.

RESULTS

The measurements of five artificial skin models with different surface shapes showed a high correlation (r = 0.99) between the vibration intensity values evaluated by the developed sensor and those measured by a tri-axial acceleration sensor attached to a fingernail. The correlation coefficient between the vibration intensity values and surface roughness was r = 0.91, and the correlation with the sensory evaluation score of roughness was r = 0.99. The friction coefficients measured by the developed sensor and the force plate had r = 0.93, based on measurements of five artificial skin models with different friction conditions. The inter-rater correlation coefficients between the three participants of the developed sensor were as high as 0.92 and 0.94 for the vibration and friction measurements respectively.

CONCLUSION

The vibration intensities and friction coefficients from the sensor were highly correlated with those of the conventional sensor. The inter-rater reliability was also high. The developed sensor can be useful for tactile evaluation in skin-care product development.

Skin Sensory Assessors Highly Agree on the Appraisal of Skin Smoothness and Elasticity but Fairly on Softness and Moisturization

We tested the reliability of sensory evaluations of tactile sensation on bare skin and investigated the reliability among evaluation attributes by trained and untrained assessors. Two trained professional panelists and two untrained researchers evaluated skin in terms of several attributes: smooth–rough, elastic–not elastic, soft–hard (surface), soft–hard (base), moisturized–dry. Twenty-two women aged 25–57 years were evaluated, and the sensory evaluation was repeated twice. Correlation coefficients and intraclass correlation coefficients (ICCs) were used to examine intra- and inter-assessor reliability. The sensory evaluation and physical quantities acquired by commercial and non-commercial instruments were moderately correlated. Smooth–rough and elastic–not elastic showed high or moderate inter-assessor reliabilities with mean correlation coefficients between panelists of 0.81 and 0.58, respectively. Further, the ICC (2,1) values were 0.64 and 0.51, respectively, and the ICC (2,2) values were 0.77 and 0.67, respectively. Conversely, the reliabilities of soft–hard (surface), soft–hard (base), and moisturized–dry were low; the mean correlation coefficients between the panelists were 0.36, 0.23, and 0.22; the ICC (2,1) values were 0.27, 0.23, and 0.17; and the ICC (2,2) values were 0.42, 0.29, and 0.26, respectively. Reliability differed between attributes. We found no meaningful differences between the trained and untrained panelists regarding intra- or inter-assessor reliability.