Measuring contact area in a sliding human finger-pad contact

Closed-Loop Control of Electroadhesion Using Current Regulation

Electroadhesion displays provide controllable friction between the fingertip and screen. However, the change of contact condition causes variability in the produced friction. In this paper, we demonstrate a novel method for closed-loop control using current regulation to improve the precision of the electroadhesion force regardless of contact conditions. The current sensor obtains static current (when the finger is stationary) and dynamic current (when the finger is sliding). The static current is used to estimate the apparent contact area. The estimated contact area modulates the driving voltage along with the dynamic current. To verify the proposed method, we measured electroadhesion forces under open-loop control and closed-loop control. The benefit of using this closed-loop control is shown by comparing the relative static error of open-loop control and closed-loop control. The relative error reductions achieved over 34 % (max 112 %) for four changing contact conditions.

Effect of Relative Humidity on Transfer of Aerosol-Deposited Artificial and Human Saliva from Surfaces to Artificial Finger-Pads

Surface to hand transfer of viruses represents a potential mechanism for human exposure. An experimental process for evaluating the touch transfer of aerosol-deposited material is described based on controlling surface, tribological, and soft matter components of the transfer process. A range of high-touch surfaces were evaluated. Under standardized touch parameters (15 N, 1 s), relative humidity (RH) of the atmosphere around the contact transfer event significantly influenced transfer of material to the finger-pad. At RH < 40%, transfer from all surfaces was <10%. Transfer efficiency increased markedly as RH increased, reaching a maximum of approximately 50%. The quantity of material transferred at specific RHs above 40% was also dependent on roughness of the surface material and the properties of the aerosol-deposited material. Smooth surfaces, such as melamine and stainless steel, generated higher transfer efficiencies compared to those with textured roughness, such as ABS pinseal and KYDEX® plastics. Pooled human saliva was transferred at a lower rate compared to artificial saliva, indicating the role of rheological properties. The artificial saliva data were modeled by non-linear regression and the impact of environmental humidity and temperature were evaluated within a Quantitative Microbial Risk Assessment model using SARS-CoV-2 as an example. This illustrated that the trade-off between transfer efficiency and virus survival may lead to the highest risks of fomite transmissions in indoor environments with higher humidity.

Skin wetness detection thresholds and wetness magnitude estimations of the human index fingerpad and their modulation by moisture temperature

Humans often experience wet stimuli using their hands, yet we know little on how sensitive our fingers are to wetness and the mechanisms underlying this sensory function. We therefore aimed to quantify the minimum amount of water required to detect wetness on the human index fingerpad, the wetness detection threshold, and assess its modulation by temperature. Eight blinded participants (24.0 ± 5.2 yr; 23.3 ± 3.5 body mass index) used their index fingerpad to statically touch stimuli varying in volume (0, 10, 20, 30, 40, or 50 mL) and temperature (25, 29, 33, or 37°C). During and after contact, participants rated wetness and thermal sensations using a modified yes/no task and a visual analog scale. The wetness detection threshold at a moisture temperature akin to human skin (33°C) was 24.7 ± 3.48 mL. This threshold shifted depending on moisture temperature (R = 0.746), with cooler temperatures reducing (18.7 ± 3.94 mL at 29°C) and warmer temperatures increasing (27.0 ± 3.04 mL at 37°C) thresholds. When normalized over contact area, the wetness detection threshold at 33°C corresponded to 1.926 × 10⁻⁴ mL·mm⁻² [95% confidence interval (CI): 1.873 × 10⁻⁴, 1.979 × 10⁻⁴ mL·mm⁻²]. Threshold differences were reflected by magnitude estimation data, which were analyzed using linear regression to show that both volume and moisture temperature can predict magnitude estimations of wetness (R = 0.949; R = 0.179). Our results indicate high sensitivity to wetness in the human index fingerpad, which can be modulated by moisture temperature. These findings are relevant for the design of products with wetness management properties.

NEW & NOTEWORTHY The perception of wetness is a fundamental sensory experience which underpins many aspects of life, from homeostasis to enjoyable experiences. Although previous research has highlighted the importance of cold sensations in human wetness perception, the maximum sensitivity of our wetness sensing system remains to be established. This research presents a novel methodology, which for the first time, has quantified the high sensitivity of the human index fingerpad to wetness and its modulation by moisture temperature.

Simulating finger-tip force using two common contact models: Hunt-Crossley and elastic foundation

Musculoskeletal models of the hand rarely include fingerpad contact mechanics, thereby limiting our ability to simulate and examine hand-object interactions. The objective of this study was to evaluate whether two common contact models (Hunt-Crossley and Elastic Foundation) can accurately represent the fingerpad. Two musculoskeletal models of the index finger were created by adding fingerpad contact geometry using either the Hunt-Crossley or Elastic Foundation contact models. Key contact parameters (target force, contact area, and stiffness) were then systematically varied through 432 forward dynamic simulations to examine how these parameters influenced estimation of finger-tip forces. Across all simulations, variation in target force, contact area, and stiffness parameters impacted the computation time required to complete the simulations and the accuracy of the predicted finger-tip force. Computation time was over three times longer in simulations with high versus low values of contact area and stiffness in both contact models. For both contact models, larger contact area and stiffness values resulted in simulations that more closely predicted target force. However, across all simulations, the Hunt-Crossley model produced a greater proportion of accurate finger-tip force simulations than the Elastic Foundation model, suggesting that the Hunt-Crossley contact model may be preferable for modeling the fingerpad. Overall, our study demonstrates how the Hunt-Crossley and Elastic Foundation contact models behave in low-force biomechanical scenarios, such as those experienced during hand-object manipulation, and provides a foundation for incorporating contact mechanics into musculoskeletal models of the hand.

Finger Pad Topography beyond Fingerprints: Understanding the Heterogeneity Effect of Finger Topography for Human-Machine Interface Modeling

With the rapid development of haptic devices, there is an increasing demand to understand finger pad topography under different conditions, especially for investigation of the human-machine interface in surface haptic devices. An accurate description of finger pad topography across scales is essential for the study of the interfaces and could be used to predict the real area of contact and friction force, both of which correlate closely with human tactile perception. However, there has been limited work reporting the heterogeneous topography of finger pads across scales. In this work, we propose a detailed heterogeneous finger topography model based on the surface roughness power spectrum. The analysis showed a significant difference between the topography on ridges and valleys of the fingerprint and that the real contact area estimation could be different by a factor of 3. In addition, a spatial-spectral analysis method is developed to effectively compare topography response to different condition changes. This paper provides insights into finger topography for advanced human-machine interaction interfaces.

Bacterial transfer to fingertips during sequential surface contacts with and without gloves

Bacterial transmission from contaminated surfaces via hand contact plays a critical role in disease spread. However, the fomite-to-finger transfer efficiency of microorganisms during multiple sequential surface contacts with and without gloves has not been formerly investigated. We measured the quantity of Escherichia coli on fingertips of participants after 1-8 sequential contacts with inoculated plastic coupons with and without nitrile gloves. A Bayesian approach was used to develop a mechanistic model of pathogen accretion to examine finger loading as a function of the difference between E coli on surfaces and fingers. We used the model to determine the coefficient of transfer efficiency (λ), and influence of swabbing efficiency and finger area. Results showed that λ for bare skin was higher (49%, 95% CI = 32%-72%) than for gloved hands (30%, CI = 17%-49%). Microbial load tended toward a dynamic equilibrium after four and six contacts for gloved hands and bare skin, respectively. Individual differences between volunteers' hands had a negligible effect compared with use of gloves (P < .01). Gloves reduced loading by 4.7% (CI = -12%-21%) over bare skin contacts, while 20% of participants accrued more microorganisms on gloved hands. This was due to poor fitting, which created a larger finger surface area than bare hands.

Effect of Material Hardness on Friction Between a Bare Finger and Dry and Lubricated Artificial Skin

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 TiO₂, 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.

A study on the effect of fingerprints in a wet system

In this paper, we study the influence of the fingerprint and sweat on the fingerprint on the friction between the hand and an object. When sweat contacts a finger or an object, it is sometimes easy to pick up the object. In particular, we can see this phenomenon when grasping a thin object such as paper and vinyl. The reason for this phenomenon is the increase of friction force, and this paper physically analyzes this natural phenomenon. To this end, we investigate the cause of the friction force between a solid and liquid to calculate the friction force when water is present within the fingerprint. To support the theoretical analysis, we conduct experiments to measure the friction force by making a finger-shaped silicon specimen. By comparing the theoretical and experimental results, we defined the change of friction force if there was water in the fingerprint. Through this study, it is possible to analyze the role of the fingerprint and sweat on the finger, and thereby explain the friction change depending on the amount of sweat.

Imaging the 3-D Deformation of the Finger Pad When Interacting with Compliant Materials

We need to understand the physics of how the skin of the finger pad deforms, and their tie to perception, to accurately reproduce a sense of compliance, or 'softness,' in tactile displays. Contact interactions with compliant materials are distinct from those with rigid surfaces where the skin flattens completely. To capture unique patterns in skin deformation over a range of compliances, we developed a stereo imaging technique to visualize the skin through optically clear stimuli. Accompanying algorithms serve to locate and track points marked with ink on the skin, correct for light refraction through stimuli, and estimate aspects of contact between skin and stimulus surfaces. The method achieves a 3-D spatial resolution of 60-120 microns and temporal resolution of 30 frames per second. With human subjects, we measured the skin's deformation over a range of compliances (61-266 kPa), displacements (0-4 mm), and velocities (1- 15 mm/s). The results indicate that the method can differentiate patterns of skin deformation between compliances, as defined by metrics including surface penetration depth, retention of geometric shape, and force per gross contact area. Observations of biomechanical cues of this sort are key to understanding the perceptual encoding of compliance.