Bioinspired Gradient-Modulus Iontronic Sensors with Drift-Suppressed Stability for Biomechanical Monitoring

In biomechanical sensing, achieving flexible sensors with a broad detection range, ultrahigh sensitivity, and long-term stability remains a major challenge. Inspired by the gradient-modulus structure of human skin, we fabricated a bioinspired gradient-modulus iontronic sensor (GMIS) by integrating a microstructured ionic gel with a glass fiber-reinforced matrix. This design expanded the sensing range and stability, enabling real-time monitoring of multiple physiological signals. Experimental results demonstrated that GMIS maintained ultrahigh sensitivity (2904 kPa –1 ) over a wide pressure range (∼3 MPa), effectively doubling that of the uniform counterpart. Glass fiber reinforcement enhanced the matrix hydrogen bonding network, effectively reducing viscoelastic-crew-inducedviscoelastic creep-induced drift from 62.28% in the uniform counterpart to 11.8% under dynamic loading. Moreover, the sensor withstood over 3000 loading cycles at 3 MPa. Combined with a convolutional neural network algorithm, the plantar pressure sensing system achieved a Pearson correlation coefficient exceeding 0.91 between measured and predicted values during walking and running. This work establishes a modulus-gradient design strategy for wearable biomechanical sensors, integrating material innovation with biomechanical analysis for musculoskeletal rehabilitation and health monitoring.