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Textile‐based wearable electronics combined with nanomaterials are ideal devices that have good electrical and thermal conductivity, and flexibility. With a metal conductivity and metalloid flexibility, 2D titanium carbide MXene is excellent enough for producing intelligent textiles. Here, a wrapping forming method is provided to fabricate MXene textile strain (MTS) sensors with high gauge factor (GF) of 715.94 as high as strain of 200%. Periodic cycling indicated that the MTS wrapped yarn is stable, which can track changes of facial expressions precisely as the small deformation. Weaving MTS yarns into fabric as glove and sensing belt can recognize sign language and record middle and large motions of human body, respectively. On the other hand, walking postures and electric heating are accurately detected by coating MXene dispersions on elastic and breathable spacer fabric as piezoresistive insoles, which is especially beneficial to the elderly and patients with foot diseases. Therefore, a unique strategy is proposed for full scale human motions monitoring by fabricating MXene helical yarns served as sensitive strain sensors, weft rib fabric that detected the in‐plane deformations and spacer fabric piezoresistive insole behaved as pressure sensors to monitor the step patterns so that suiting for wearable versatile sensing system.

In this paper, a multilevel fuzzy comprehensive evaluation (FCE) model consisting of tactile comfort and four primary handle characteristics (FPHCs) is developed. The physiological perceptions of 30 home textile fabrics were predicted, to verify the practicability of the FCE model and the reliability of the objective measurement based on the self-developed Quick-Intelligent Handle Evaluation System (QIHES). Moreover, comparisons between the FCE model and subjective evaluation of the FPHCs and total handle value (THV) were investigated. The results showed that the values of the coefficients of determination ( R2) and the slopes of linear correlation functions were approximate to 1, which revealed that the results of the FCE model and subjective evaluation were highly consistent, and the FCE model established was accurate. In addition, the performance of the soft fabrics depends on the combined effect of the properties of three directions. It has been confirmed that the fullness, stiffness and roughness are important factors that affect THV together. Thus, the FCE method based on the QIHES measurement was demonstrated to be effective and reliable, could be applied for assessing tactile comfort and estimating human feel when touching textiles and soft materials.

The main content of this paper is to objectively characterize the tactile comfort of fabric through the ring-shaped style tester. It mainly explains the objective tactile comfort of knitted fabric through the curve parameters measured by the ring-shaped style tester and structural parameter thickness. In this paper, by adopting the methods of correlation analysis and cluster analysis, the curve parameters, including slope in the linear segments of the left-hand part of the curve ( K1), the right-hand area of the curve ( A2), the distance between the abrupt point and the peak point ( X), the linearity of the left-hand curve ( L) and the ratio of the left-hand area to the right-hand area of the curve ( C), are used. In order to verify its effectiveness, the results of subjective evaluation are compared and analyzed with the objective clustering. The experimental results show that the subjective judgment has good correlation with the objective clustering. This indicates that the curve parameters obtained through the ring-shaped style tester and structural parameters can be used to effectively represent the tactile comfort performance of fabrics.

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