Abstract
Stimuli used in previous reported studies were mostly tailor-made embossed surfaces. Validation of neural signal coding mechanism to address the touch smoothness in daily life was seldom reported. In this study, 20 types of fabrics were chosen as stimuli. Their physical surface profiles were measured by Fabric Touch Tester. Afterwards three different neural signal coding mechanisms of SA1 and PC fibers were applied and modified to predict the perceived neural responses. The predicted values were compared to subjective smoothness sensations obtained through psychological measurement. The results show that it is essential to in detail characterize the unevenness elements on the surfaces of stimuli. The integrated impacts from the unevenness elements with different intensities and frequencies demonstrate better prediction capacities among the examined neural coding mechanisms. On the basis of the findings, a neuropsychological prediction model of fabrics was built. Another 32 types of fabrics were measured and used to validate the model. Strong correlation between the predicted and subjective sensory results was observed (F=0.808, p<0.001).
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Liao, X., Li, Y., Hu, J. et al. Investigation of Neuropsychological Mechanism of Fabric Smoothness Sensation. Fibers Polym 20, 1069–1076 (2019). https://doi.org/10.1007/s12221-019-8592-x
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DOI: https://doi.org/10.1007/s12221-019-8592-x