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Stretchable and Highly Sensitive Optical Strain Sensors for Human-Activity Monitoring and Healthcare

材料科学 可穿戴计算机 光电子学 光纤 包层(金属加工) 纳米技术 表面等离子共振 线性 弹性体 可穿戴技术 计算机科学 纳米颗粒 电子工程 复合材料 电信 工程类 嵌入式系统
作者
Jingjing Guo,Bingqian Zhou,Rui Zong,Longsheng Pan,Xuemei Li,Xinguang Yu,Changxi Yang,Lingjie Kong,Qionghai Dai
出处
期刊:ACS Applied Materials & Interfaces [American Chemical Society]
卷期号:11 (37): 33589-33598 被引量:139
标识
DOI:10.1021/acsami.9b09815
摘要

Flexible and stretchable strain sensors are essential to developing smart wearable devices for monitoring human activities. Such sensors have been extensively exploited with various conductive materials and structures, which, however, are normally in need of complex manufacturing processes and confronted with the challenge to achieve both large stretchability and high sensitivity. Here, we report a simple and low-cost optical strategy for the design of stretchable strain sensors which are capable of measuring large strains of 100% with a low detection limit (±0.09%), a fast responsivity (<12 ms), and high reproducibility (over 6000 cycles). The optical strain sensor (OS2) is fabricated by assembling plasmonic gold nanoparticles (GNPs) in stretchable elastomer-based optical fibers, where a core/cladding structure with step-index configuration is adopted for light confinement. The stretchable, GNP-incorporated optical fiber shows strong localized surface plasmon resonance effects that enable sensitive and reversible detection of strain deformations with high linearity and negligible hysteresis. The unique mechanical and sensing properties of the OS2 enable its assembling into clothing or mounting on skin surfaces for monitoring various human activities from physiological signals as subtle as wrist pulses to large motions of joint bending and hand gestures. We further apply the OS2 for quantitative analysis of motor disorders such as Parkinson's disease and demonstrate its compatibility in strong electromagnetic interference environments during functional magnetic resonance imaging, showing great promises for diagnostics and assessments of motor neuron diseases in clinics.
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