Human wetness perception of fabrics under dynamic skin contact
Source abstract
Abstract
This experiment studied textile (surface texture, thickness) and non-textile (local skin temperature changes, stickiness sensation and fabric-to-skin pressure) parameters affecting skin wetness perception under dynamic interactions. Changes in fabric texture sensation between WET and DRY states and their effect on pleasantness were also studied. The surface texture of eight fabric samples, selected for their different structures, was determined from surface roughness measurements using the Kawabata Evaluation System. Sixteen participants assessed fabric wetness perception, at high pressure and low pressure conditions, stickiness, texture and pleasantness sensation on the ventral forearm. Differences in wetness perception (p < 0.05) were not determined by texture properties and/or texture sensation. Stickiness sensation and local skin temperature drop were determined as predictors of wetness perception (r 2 = 0.89), and although thickness did not correlate with wetness perception directly, when combined with stickiness sensation it provided a similar predictive power (r 2 = 0.86). Greater (p < 0.05) wetness perception responses at high pressure were observed compared with low pressure. Texture sensation affected pleasantness in DRY (r 2 = 0.89) and WET (r 2 = 0.93). In WET, pleasantness was significantly reduced (p < 0.05) compared to DRY, likely due to the concomitant increase in texture sensation (p < 0.05). In summary, under dynamic conditions, changes in stickiness sensation and wetness perception could not be attributed to fabric texture properties (i.e. surface roughness) measured by the Kawabata Evaluation System. In dynamic conditions thickness or skin temperature drop can predict fabric wetness perception only when including stickiness sensation data.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Textile materials and evaluations · Color perception and design · Visual perception and processing mechanisms
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Environmental Ergonomics Research Centre, Loughborough University, UK
adidas FUTURE Sport Science, Herzogenaurach, Germany
Performance Textiles and Clothing Research Group, University of Leeds, UK
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