Phytic Acid/MXene@Polyurethane Sponge - Based Flexible Pressure Sensor with Assistance of MC-GRU model for Motion Posture Recognition

With the continuous advancement of intelligent sensing technology, the growing demand for flexible electronic products has created valuable opportunities for the development of flexible pressure sensors. In this work, a polyurethane (PU) sponge was employed as a flexible substrate, where a coupling strategy was utilized to achieve surface modification of two-dimensional MXene nanosheets with phytic acid (PA), and a PA/MXene@PU sponge(PMP) sensor was successfully constructed through a self-assembly process. As a flame retardant and binder, PA effectively enhances the conductivity and mechanical properties of PMP. This sensor demonstrates high sensitivity (16.71 kPa⁻ ¹), a wide detection range (0-175 kPa), and stability exceeding 8000 cycles. It can effectively detect responses triggered by water droplets falling from a height of 2 cm and 20 mg NaCl aqueous solution impacts (0.01 N). Additionally, its excellent flame retardancy enables self-extinguishing within 20 seconds after ignition. Additionally, this paper integrates PMP with a gated recurrent unit convolutional neural network (MC-GRU) to achieve recognition and classification of six joints—ankles, wrists, fingers, throat, knees, and elbows—with a classification success rate of up to 99.83%. The results demonstrate the immense potential of PMP sponge sensors in physiological signal detection and human motion monitoring. This work establishes a solid foundation for the intelligent development of flexible pressure sensors in motion posture analysis while providing insights into the design of safe and environmentally friendly flexible sensors.