Biomimetic Gradient Fibrous Aerogel Pressure Sensor Featuring Ultrawide Sensitive Range and Extraordinary Pressure Resolution for Machine Learning Enabled Posture Recognition

Abstract

Achieving human skin-like sensitivity and wide-range pressure detection remains a significant challenge in the development of wearable pressure sensors. In this study, we engineered and fabricated a fibrous polyimide fiber (PIF)/carbon nanotube (CNT) composite aerogel with a gradient structure using a layer-by-layer freeze casting technique, aiming to overcome the limitations of traditional pressure sensors. Finite element analysis (FEA) reveals that this innovative gradient structure mimics the unique microstructure of human skin, enabling the sensor to detect a broad spectrum of pressure stimuli, ranging from subtle pressures as low as 10 Pa to intense pressures up to 1.58 MPa with exceptional sensitivity. Moreover, the sensor exhibits extraordinary pressure resolution across the entire pressure range, particularly at 1 MPa (0.001%). Additionally, the sensor demonstrates remarkable thermal stability, operating reliably across a wide temperature range from − 150 to 200 °C, making it suitable for extreme environments such as deep space exploration. When integrated with machine learning algorithms, the sensor shows great potential for real-time physiological monitoring, fitness tracking, and motion recognition. The proposed gradient fibrous pressure sensor, with its high sensitivity and resolution over a wide pressure range, paves the way for new opportunities in human–machine interaction.

Keywords

Fibrous aerogel / Gradient structure / Ultrawide sensitive range / Machine learning / Posture recognition

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Funding

National Natural Science Foundation of China(52373093)

Natural Science Foundation of Henan Province(242300421062)

Central Plains Youth Top notch Talent Program of Henan Province

111 project(D18023)

RIGHTS & PERMISSIONS

Donghua University, Shanghai, China