Bioinspired Stretchable Fiber-Based Sensor toward Intelligent Human–Machine Interactions

IF 8.3 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY ACS Applied Materials & Interfaces Pub Date : 2022-05-09 DOI:10.1021/acsami.2c05823
Tianliang Li*, Yifei Su, Fayin Chen, Han Zheng, Wei Meng, Zemin Liu, Qingsong Ai, Quan Liu*, Yuegang Tan* and Zude Zhou*, 
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引用次数: 11

Abstract

Wearable integrated sensing devices with flexible electronic elements exhibit enormous potential in human–machine interfaces (HMI), but they have limitations such as complex structures, poor waterproofness, and electromagnetic interference. Herein, inspired by the profile of Lindernia nummularifolia (LN), a bionic stretchable optical strain (BSOS) sensor composed of an LN-shaped optical fiber incorporated with a stretchable substrate is developed for intelligent HMI. Such a sensor enables large strain and bending angle measurements with temperature self-compensation by the intensity difference of two fiber Bragg gratings’ (FBGs’) center wavelength. Such configurations enable an excellent tensile strain range of up to 80%, moreover, leading to ultrasensitivity, durability (≥20,000 cycles), and waterproofness. The sensor is also capable of measuring different human activities and achieving HMI control, including immersive virtual reality, robot remote interactive control, and personal hands-free communication. Combined with the machine learning technique, gesture classification can be achieved using muscle activity signals captured from the BSOS sensor, which can be employed to obtain the motion intention of the prosthetic. These merits effectively indicate its potential as a solution for medical care HMI and show promise in smart medical and rehabilitation medicine.

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面向智能人机交互的仿生可拉伸纤维传感器
具有柔性电子元件的可穿戴式集成传感设备在人机界面(HMI)方面显示出巨大的潜力,但存在结构复杂、防水性差、电磁干扰等局限性。本文以林荫树(Lindernia numarifolia, LN)的外形为灵感,开发了一种由LN形光纤与可拉伸衬底结合而成的仿生可拉伸光学应变(BSOS)传感器,用于智能人机界面。这种传感器可以实现大应变和弯曲角测量,并通过两个光纤布拉格光栅(fbg)中心波长的强度差进行温度自补偿。这样的配置可以实现高达80%的优异拉伸应变范围,此外,还可以实现超灵敏度、耐用性(≥20,000次循环)和防水性。该传感器还能够测量不同的人类活动并实现HMI控制,包括沉浸式虚拟现实,机器人远程交互控制和个人免提通信。结合机器学习技术,利用BSOS传感器捕捉到的肌肉活动信号进行手势分类,从而获得假肢的运动意图。这些优点有效地表明了它作为医疗保健HMI解决方案的潜力,并在智能医疗和康复医学方面显示出前景。
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来源期刊
ACS Applied Materials & Interfaces
ACS Applied Materials & Interfaces 工程技术-材料科学:综合
CiteScore
16.00
自引率
6.30%
发文量
4978
审稿时长
1.8 months
期刊介绍: ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.
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