鉴定(生物学)
感知
灵敏度(控制系统)
计算机科学
人机交互
心理学
工程类
电子工程
生物
神经科学
植物
作者
Yue Huang,Shaoxiong Hu,Ying Li,Rui Wang,Yuchen Yang,Wei Zhu,Yuan Deng
标识
DOI:10.1038/s41528-025-00420-9
摘要
Flexible pressure sensors are essential for human–machine interfaces and wearable devices, requiring accurate detection of diverse motion signals. However, challenges arise from material compressibility and mechanical limitations, hindering the development of sensors with both high sensitivity and wide sensing ranges, as well as the demand-driven designability. Here, iontronic sensors exhibiting distinct characteristics are developed via a skin-inspired gradient strategy with programmable performance of ultrahigh sensitivity (37,347.98 kPa−1) to 151.6 kPa or overall high sensitivity (130.93–1400.49 kPa−1) up to 956.7 kPa, capable of detecting both subtle arterial pulses and large motions like plantar pressure. Furthermore, the merit of ultrahigh sensitivity enables pressure sensors to record handwriting precisely and distinguish individual features, facilitating effective extraction of connotative information, and has been demonstrated in the proposed human-interactive system assisted with machine learning for individual authentication. The work provides valuable insight into reverse engineering of pressure sensors, promising benefits for broad intelligence applications.
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