Wearable one-handed keyboard using hydrogel-based mechanical sensors for human-machine interaction

As the Internet of Things advances, gesture recognition emerges as a prominent domain in humanmachine interaction (HMI). However, interactive wearables based on conductive hydrogels for individuals with single -arm functionality or disabilities remain underexplored. Here, we devised a wearable onehanded keyboard with gesture recognition, employing machine learning algorithms and hydrogel-based mechanical sensors to boost productivity. PCG (PAM/CMC/rGO) hydrogels are composed of polyacrylamide (PAM), sodium carboxymethyl cellulose (CMC), and reduced graphene oxide (rGO), which function as a strain, pressure sensor, and electrode material. The PAM chains offer the gel's elasticity by covalent crosslinking, while the biocompatible CMC improves the dispersion of rGO and promotes electromechanical properties. Integrating rGO sheets into the polymer matrix facilitates cross-linking and generates supplementary conductive pathways, thereby augmenting the gel system's elasticity, sensitivity, and durability. Our hydrogel sensors include high sensitivity (gage factor (GF) = 8.18, 395.6 %-551.96 %) and superior pressure sensing capabilities (Sensitivity ( S ) = 0.3116 kPa-1, 0-9.82 kPa). Furthermore, we developed a wearable keyboard with up to 98.13 % accuracy using convolutional neural networks and a custom data acquisition system. This study establishes the groundwork for creating multifunctional gel sensors for intelligent machines, wearable devices, and brain-computer interfaces. (c) 2024 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.