When grasping objects, we rely on our sense of touch to adjust our grip and react against external perturbations. Less than 200 ms after an unexpected event, the sensorimotor system is able to process tactile information to deduce the frictional strength of the contact and to react accordingly. Given that roughly 1,300 afferents innervate the fingertips, it is unclear how the nervous system can process such a large influx of data in a sufficiently short time span. In this study, we measured the deformation of the skin during the initial stages of incipient sliding for a wide range of frictional conditions. We show that the dominant patterns of deformation are sufficient to estimate the distance between the frictional force and the frictional strength of the contact. From these stereotypical patterns, a classifier can predict if an object is about to slide during the initial stages of incipient slip. The prediction is robust to the actual value of the interfacial friction, showing sensory invariance. These results suggest the existence of a possible compact set of bases that we call Eigenstrains. These Eigenstrains are a potential mechanism to rapidly decode the margin from full slip from the tactile information contained in the deformation of the skin. Our findings suggest that only 6 of these Eigenstrains are necessary to classify whether the object is firmly stuck to the fingers or is close to slipping away. These findings give clues about the tactile regulation of grasp and the insights are directly applicable to the design of robotic grippers and prosthetics that rapidly react to external perturbations.@en

The contact between the fingertip and an object is formed by a collection of micro-scale junctions, which collectively constitute the real contact area. This real area of contact is only a fraction of the apparent area of contact and is directly linked to the frictional strength of the contact (i.e., the lateral force at which the finger starts sliding). As a consequence, a measure of this area of real contact can help probe into the mechanism behind the friction of skin on glass. In this article, we present two methods to measure the variations of contact area;one that improves upon a tried-and-true fingertip imaging technique to provide ground truth, and the other that relies on the absorption and reflection of acoustic energy. To achieve precise measurements, the ultrasonic method exploits a recently developed model of the interaction that incorporates the non-linearity of squeeze film levitation. The two methods are in good agreement (= 0.94) over a large range of normal forces and vibration amplitudes. Since the real area of contact fundamentally underlies fingertip friction, the methods described in the article have importance for studying human grasping, understanding friction perception, and controlling surface-haptic devices.

@en

Ultrasonic surface-haptic touchscreens produce compelling tactile sensations directly on the users' fingertips. The tactile sensations stem from the modulation of friction produced by acoustic radiation pressure, which reduces the contact between the skin and the glass plate. During this process, some of the vibrations are partly absorbed by the tissues, resulting in a conspicuous change in the vibration amplitude of the plate upon contact with the finger, which manifests as a net change in the system mechanical impedance. In this study, we leverage the observable change of impedance to estimate the acoustic levitation and the frictional force. The self-sensing method utilizes a model of the first principles governing the physical interaction between the plate and the skin, which relies on multi-scale contact theory. The model accurately describes the experimental influence of the amplitude on the observed impedance (i.e., the amount of energy absorbed and reflected) and can be used to estimate the friction coefficient (R2=0.93). These results provide additional evidence of the partial levitation mechanism at play in ultrasonic friction-modulation. This finding can be useful for designing energy-efficient devices and provide design suggestions for using ultrasonic impedance for self-sensing friction forces.

@en