Tactile perception of textile fabrics based on friction and brain activation

Abstract

Tactile perception plays a critical role in the interaction of humans and environment. It begins with the mechanical stimulation induced by friction and is processed in the somatosensory cortex. To quantify the tactile perceptions of textile fabrics, the mechanical properties of fabrics and the features extracted from the friction and vibration signals were correlated with the subjective sensation rated by questionnaires. Meanwhile, the technique of functional magnetic resonance imaging (fMRI) was used to identify the brain areas responsible for the tactile perception of textile fabrics. The results showed that during the tactile perception of textile fabrics, the coefficient of friction increased with the increasing normal load, indicating that the deformation mechanism of skin was relevant to the friction of skin against fabrics. The features of spectral centroid (SC), coefficient of friction, and diameter and critical buckling force of fiber had a strong correlation with the perceived fineness, slipperiness, and prickliness of fabrics, respectively. The postcentral gyrus, supramarginal gyrus, and precentral gyrus, with the corresponding functional regions of the primary somatosensory cortex (SI), secondary somatosensory cortex (SII), primary motor cortex (MI), and secondary motor cortex (MII), were involved with the perceptions of fabric textures. The fiber properties and fabric surface structures that caused the multidimensional feelings tended to induce the large area, intensity, and percent signal change (PSC) of brain activity. This study is meaning for evaluating the tactile stimulation of textile fabrics and understanding the cognitive mechanism in the tactile perception of textile fabrics.

Specific Fabric Properties Elicit Human Neuro and Electrophysiological Responses

“…Tactile sensation is a complex phenomenon that involves afferent pathways bringing sensory information into the brain, where the sensory cortex processes the information to generate perception. Most of the studies have focused on understanding this from the perspective of the brain in terms of areas that are involved in the process (Rajaei et al ., 2018; Wang et al ., 2016, 2019), how the sensory cortex perceives smoothness or roughness (Hoefer et al ., 2016; Tang, Zhang, et al ., 2022), how different fabric types can induce different brain activity (Rajaei et al ., 2018; Yuan, Yu, Wang, et al ., 2019) and how different textures elicit distinguishable activation patterns in the brain (Henderson et al ., 2022; Moungou et al ., 2015; Tang, Shu, et al ., 2022). In this study, we explored tactile sensation from the perspective of fabric properties.…”

Tactile perception of textile fabrics using event-related potentials and nonlinear methods

“…In Wang et al's study and our previous study, significant activations in the somatosensory areas in response to cutaneous prickling stimulation of fabric were also observed. 43,44 It promoted the neurotransmission which in turn enhanced the neuronal response properties and temporal processing, and appeared as the high P200 and P300 peak amplitude and fast latency. Previous studies also suggested that the surface with high surface roughness and friction induced large P300 peak amplitude and fast latency.…”

Experiment and modelling of texture and sliding direction dependence on finger friction behavior

“…Accordingly, the mechanical information at the skin-object interface is the essential source of obtaining tactile information, and quantifying the friction interaction at the interface plays a key role in understanding and encoding the tactile information. In order to clarify the correlation between interface friction and tactile perception, research on tactile friction has been increasingly important [1][2][3], as it can build a bridge between human sensation and tactile surface properties based on the mechanical information of interface friction. Such knowledge is critical in the development of haptic technology [4,5], functional prostheses [6], and intelligent robotics [7,8].…”

“…Theoretically, the area-force relation could be also predicted by the double-layer model. Based on the geometric relation of  of R>>d, the indentation depth d could be replaced by the contact area S in Eq (3)…”