Towards Knitted Textile Electromechanical Systems

John Martins, Abigail Hou, Brandon Tendilla, Noah Tannas, Rishit Garg, Wenchi Liu, Ben Kim, Michael Miller, Alejandro Goldstein, Elizabeth McLaughlin, Nivedita Arora

E-textiles and wearable sensing technologies enable flexible, customizable interfaces for human-computer interaction, with capacitive sensing offering precise touch and pressure detection. While machine knitting provides scalable, mechanically tunable structures ideal for such sensors, few studies develop or characterize insulated conductive yarns engineered for knitting's complex structural geometry and high flexure strain. In this work, we present a yarn dip-coating process, driven by an adjusted dip-coating fluid dynamics model, that enables scalable, machine knittable fabrication of capacitive tactile pressure sensing arrays. We establish optimal dip-coating parameters and concentrations of thermoplastic polyurethane (TPU) dissolved in dimethylformamide (DMF) to create knitting-optimized coatings (~630 um thickness). These fabricated yarns are shown to maintain electromechanical characteristics with minimal deviation after knitting and washing, thus allowing the creation of knitted pressure sensors through multi-layered structures. This process demonstrates that machine knitting with insulated yarns is a viable and reliable manufacturing approach to integrate sensing functionality into wearable textiles.