Multifunctional PVA/SA-based hydrogels integrating high stretchability, conductivity, and antibacterial activity for human-machine interactive flexible sensors

Flexible sensor plays an important role in human-machine interactive research, and the growing demand for flexible sensors underscores the need to address key hydrogel limitations: poor mechanical properties, high hysteresis, low conductivity, limited fatigue resistance, and inadequate antibacterial performance. This study utilized polyvinyl alcohol, chitosan, and sodium alginate as matrices for double-network hydrogels, capitalizing on their inherent renewability and biocompatibility. By optimizing the ternary solvent system composed of ionic liquid, glycerol, and water, the mechanical and electrical properties of the hydrogels were substantially improved. The presence of multiple hydrogen and ionic bonds conferred high mechanical performance to PVA-SA-CS-rGO/PPy-CNT (polyvinyl alcohol‑sodium alginate-chitosan-reduced graphene oxide/polypyrrole‑carbon nanotube) hydrogels, achieving a tensile strain of 1491 %, a tensile strength of 1.793 MPa, and a modulus of 309.3 kPa. Furthermore, PVA-SA-CS-rGO/PPy-CNT hydrogels displayed excellent antibacterial properties, electrical conductivity, processability, and antifreeze capabilities. The flexible hydrogel sensors could effectively detect strain or pressure, and exhibit high sensitivity over a wide range (GF = 1.49 in 0–176 %; GF = 2.76 in 176 %–415 %; GF = 1.77 in 415 %–600 %), reliably recognizing human movements and physiological signals. Furthermore, we designed a micro low-power acquisition device and accompanying software employing 4 different algorithms for model training. Herein, a multi-layer perceptron (MLP) algorithm-driven human-machine interface was developed and experimentally validated on a Mecanum-wheel robotic platform. Through gesture-to-action mapping, this system demonstrates integrated advancements in hydrogel-enabled sensing and interactive control architectures. This study demonstrates significant potential for developing cost-effective and highly adaptable hydrogel sensors, while offering critical insights into the integration of hydrogel sensors with human-machine interaction technologies.