材料科学
压阻效应
灵敏度(控制系统)
声学
航程(航空)
生物医学工程
光电子学
人工智能
计算机视觉
触觉传感器
计算机科学
加速度计
噪音(视频)
作者
X-D Wu,Hang Yin,Yarong Zhou,Xuqiang Zhang,Yun Zhao,Jianbiao Chen,Jian Wang,Y Anita Li,Jiangtao Chen
标识
DOI:10.1021/acsami.6c11575
摘要
in the low-pressure regime while maintaining robust sensing performance across an extended working range (up to 390 kPa). Furthermore, it exhibits fast response and recovery times (31/34 ms) and superior long-term durability over 3000 loading-unloading cycles. This outstanding electromechanical performance enables comprehensive multiscale physiological monitoring, capable of capturing small pressure variations down to 1 kPa including respiratory patterns and arterial pulses, as well as high-load scenarios such as joint flexion and gait monitoring. Building upon these capabilities, a real-time cervical posture recognition system was implemented as a representative paradigm of intelligent health management. By integrating a logistic regression machine learning classifier, the system attained a classification accuracy of 98.5% on the test set. This work proposes a rational structural engineering strategy, providing a versatile and dependable sensing platform for next-generation intelligent health monitoring and human-machine interfaces.
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