A sensitive flexible pressure sensor based on MXene/GOQDs/MS aerogel for machine learning powered human sitting posture recognition

Pressure sensors are widely used in human health monitoring, human-machine interaction, motion detection, intelligent robots and Internet of Things. In this work, we report a sensitive flexible pressure sensor based on MXene/GOQDs aerogel with melamine sponge as the supporting framework by infusion and freeze-drying technique. The prepared resistive pressure sensor exhibited sensitivity of 4.384 % kPa⁻¹ (ΔR/R₀/ΔP), response/recovery time (246 ms/461 ms), wide pressure detection range (1 kPa to 80 kPa), excellent repeatability (2500 cycles), and stability. The performance of the pressure sensor based on MXene/GOQDs aerogel was significantly improved compared to the pure MXene-based pressure sensor, with a 2.44-fold improvement in sensitivity. Additionally, a 4 × 4 pressure sensor array was prepared and combined with an analogue to digital converter (ADC) signal processing circuit to achieve simultaneous data acquisition across 16 channels, and the data obtained was displayed and read using upper-level computer software. The prepared pressure sensor array was applied for human sitting posture recognition with the help of the support vector machine (SVM) algorithm, achieving an accuracy rate of 100 %. This study highlights the great potential of MXene/GOQDs aerogel in developing highly sensitive, fast response and intelligent flexible pressure sensors.