Highly Stretchable and Durable Thermoplastic Poly(ether–ester) Fibrous Membrane for Constructing a Deep Learning-Assisted Knee Deformity Diagnosis System

Abstract

Conventional foot pressure sensors suffer from measurement inaccuracy, wearing discomfort, and frequent calibration, which greatly hinder their long-term practical application. Herein, we develop a tannic acid (TA)-enhanced thermoplastic poly(ether–ester) elastomer/polypyrrole hybrid membrane (TPEE–PPy–TA) with high stretchability and excellent durability as a foot pressure insole for deep learning algorithms assisted effective detection of knee deformities. Specifically, the TPEE fibrous substrate is primarily synthesized through a precisely controlled electrospinning process. Then, the in-situ polymerization of pyrrole on TPEE substrate is conducted using FeCl₃ as an oxidant and TA as a dopant. The incorporation of TA can dramatically enhance the stretchability of TPEE–PPy hybrid membrane. This enhancement is attributed to abundant phenolic hydroxyl groups of TA, which synergistically interact with both PPy chains and Fe³⁺ ions to form multifunctional interfacial networks. The stretchable and conductive membrane-based flexible sensor demonstrates outstanding pressure-sensing performance with broad detection range, fast response/recovery time, and excellent cyclic stability under 10 N loading. Beyond accurately monitoring various human motions and effectively transmitting haptic-based Morse code signals, our pressure monitoring system achieves 98.0% diagnostic accuracy for knee valgus/varus deformities through deep learning analysis of flexion signals when integrated into a foot pressure insole. This work establishes a new paradigm for smart textiles in wearable medical diagnostics by synergistically combining material innovation with AI-assisted health monitoring technology.