Assessing the accumulated stickiness magnitude from fabric-skin friction: effect of wetness level of various fabrics

Abstract

Increasing skin wetness tends to increase fabric-skin adhesion and friction, resulting in wear discomfort or skin injuries. Here, the magnitude estimation approach was used to assess the stickiness sensation perceived in fabrics. Seven fabric types were wetted by putting onto wet 'skin' surface and dried for different durations to achieve different wetness levels, simulating wearing conditions during the recovery period after sweating. Results showed that the relationship between magnitude estimates of stickiness and amount of water present in fabric demonstrated a power function. The exponents and constant from power regression show the growth rate of stickiness sensation with moisture intensity and the perceived stickiness under fixed stimulus intensity, respectively. A novel parameter, accumulated stickiness magnitude (ASM), describing how much discomfort a wetted fabric offered throughout the drying period, was developed. Thin cotton fabrics (fabric W01 and W03), having higher saturation level after contacting with wetted skin surface, arouse stronger stickiness feeling and their ASM is remarkably higher. The difference in stickiness estimates is due to the difference in chemical composition and surface geometry. This study suggests us the way to predict perceived stickiness in fabrics with different wetness levels which is useful for applications like sportswear, intimate apparel or healthcare products.

Keywords: adhesion; fabric; friction; magnitude estimate; stickiness sensation; wet skin.

Figure 1.

Magnified images of the test fabrics.

Figure 2.

Schematic diagram showing the set-up for subjective stickiness assessment with the use of BMS.

Figure 3.

Set-up for applying fixed amount of water to the ‘skin’ (i.e. plastic card).

Figure 4.

Plots of amount of water present in fabric at different evaporation time. Error bars denote one standard deviation of uncertainty. The colour of data points denotes the saturation value of the fabric. The solid line shows that the points are fitted with linear function, whereas the dash line shows the extrapolation from the trend line. The x-intercept is the projected TDT.

Figure 5.

Normalized magnitude estimates of stickiness perceived in fabrics against evaporation time. Each data point represents the average response from 20 assessors. Error bars denote one standard deviation of uncertainty. The solid line shows that the points are fitted with linear function, whereas the dash line shows the extrapolation from the trend line. The green circles show the perceived stickiness at TDT (i.e. when fabric is dry). The grey area denotes the degree of discomfort that the wearer has suffered before the fabric becomes dry.

Figure 6.

Magnitude estimates of stickiness as a function of amount of water present in the fabric. The green line shows the linear function for data points, whereas the red line shows the power function.

Figure 7.

Log–log plots showing normalized magnitude estimates of stickiness (ψ) against moisture stimuli (φ). Error bars denote one standard deviation of uncertainty. The solid line shows that the points are fitted with linear function, whereas the dash line shows the extrapolation from the trend line. The yellow circles show the perceived stickiness at 10% WAC, whereas the green circles show the perceived stickiness at 100% WAC.