Moisture-wicking Janus-structure electronic knitted fabric for multimodal wearable mechanical sensing

Abstract

Multimodal mechanical sensors that can recognize bending direction and exhibit excellent wearable performance are crucial for the fields of physical exercise and healthcare. This study fabricated a knitted multimodal sensor with porous and wetting gradients using hydrophobic core-spun yarns and hydrophilic CNT/WPU conductive yarns in plain stitch and partial tuck stitch. The electronic fabric demonstrated reliable strain sensing unaffected by compression disturbances and displayed a selective response to directional bending. The sensor exhibits a 50% sensing range with a GFmax of −4.41 during strain deformation detection. In terms of bending detection, one side achieves a 10% sensing range (−51.68°) with a GFmax of −6.89, while the other side achieves a 20% sensing range (73.72°) with a GFmax of 8.64. Encouragingly, deep learning incorporated with the sensor achieves an impressive recognition rate of 98.16% for mixed signals with different force levels. Furthermore, it possesses excellent wearable properties such as breathability, moisture permeability, perspiration remove, quick-drying and washability, suitable for applications like activity monitoring, medical rehabilitation evaluation, and gesture recognition. This work presents a promising pathway for the advancement of next-generation multifunctional electronic textiles.