Bioinspired Programmable Cilia Array for Enhanced Tactile Perception

Abstract

Flexible pressure sensors, as key components for enhancing the dimensionality of machine learning perception, demonstrate significant application potential in the Internet of Everything framework, enabling intelligent connectivity through Human-Machine Interfaces. However, the balance between sensitivity and load range remains a critical challenge that limits sensor performance. In this study, inspired by the step-by-step contact sensing principle of cochlear cilia, a programmable multi-scale ciliary structure triboelectric material is developed using a flow casting method. The flexible pressure sensor constructed using this triboelectric structural material achieves both a wide sensing range of 100 kPa and a high sensitivity of 12.692 kPa^-1. Compared to single-scale microstructure sensors, the sensing range is increased by 67.1%, while the sensitivity is enhanced by 182.7%. Furthermore, the sensor maintains high stability after more than 25,000 testing cycles. Based on this, an intelligent sensing ring was developed, which enables real-time gesture recognition and grip force sensing through the perception of finger motion states, achieving sensing accuracies of up to 98.6% and 97.6%, respectively. This research addresses the challenge of achieving compatibility between a wide stress range and high sensitivity in sensors, providing a promising manufacturing strategy for high-performance sensors based on Internet of Everything systems.