Fast response pressure sensors based on PEDOT:PSS/melamine foam for deep learning assisted human sitting posture monitoring

The increasing demand for health monitoring, electronic skins, and human–computer interaction has accelerated the development of high-performance, flexible pressure sensors. Among various sensing technologies, piezoresistive sensors offer advantages such as simple fabrication, low power consumption, and broad detection ranges. However, traditional piezoresistive materials, including metals and semiconductors, are inherently stiff and brittle, limiting their integration into wearable electronics and health monitoring. To overcome these limitations, this work reports piezoresistive flexible pressure sensor array based on poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS)/melamine foam (PMF), which were fabricated via a scalable ultrasonic impregnation technique. The prepared flexible pressure sensors showed exceptional performances including ultrafast response/recovery times (375 ms / 165 ms), broad detection range (0–80 kPa), and robust stability over 1000 compression cycles. Furthermore, the developed 4 × 4 piezoresistive flexible pressure sensor array (41 cm × 36 cm) was successfully applied for human sitting posture monitoring and captured spatially resolved pressure distribution profiles characteristic of five common sitting postures. With the assistance of a deep learning algorithm, the pressure monitoring system achieved 99.20% classification accuracy by processing signals from the sensor array. This integrated approach overcomes critical limitations of conventional posture monitoring technologies, offering a cost-effective, non-intrusive solution for preventing musculoskeletal disorders through real-time haptic feedback.