Underwater, Multifunctional Superhydrophobic Sensor for Human Motion Detection

Ni, Yimeng; Huang, Jianying; Li, Shuhui; Wang, Xiaoqin; Liu, Lexin; Wang, Mengyao; Chen, Zhong; Li, Xiao; Lai, Yuekun

doi:10.1021/acsami.0c19704

Cited by 74 publications

(42 citation statements)

References 51 publications

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“…e change of the impedance of the tag antenna and the change of the signal propagation path will cause the corresponding change of the signal received by the RFID reader and writer. is change is used by the RFID action detection system to represent specific actions [11]. e common underlying channel parameters are analyzed and explained in detail as follows:…”

Section: Rfid Action Sensing Channel Parametersmentioning

confidence: 99%

“…In formula (11), x, y, and z are the positions of the centroid of the visual image of the sprint movement, and ψ V is the switching deflection angle of the sprint movement area. To sum up, the analysis realizes the analysis of the visual characteristics of the error movement in sprint and provides the data basis for the next three-dimensional visual comparison.…”

Section: Analysis Of the Visual Characteristics Of Sprint Mistakesmentioning

confidence: 99%

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Research on Real-Time Detection of Sprint Error Based on Visual Features and Internet of Things

Chen

2021

Security and Communication Networks

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The current sprint error detection methods do not consider the analysis of the visual characteristics of sprint error, which leads to low detection accuracy, long detection time, and poor detection stability. To overcome this defect, inspired by Internet of Things technology, a real-time sprint error detection method based on visual characteristics is proposed. Based on the basic principle of RFID action perception, the original phase data is preprocessed, the channel parameters are selected, and the tag layout is optimized to form the action-oriented feature. Based on the three-dimensional visual features, the three-dimensional coordinate points of the sports field are determined, and the movement features of the sprint are extracted and formally described. Based on the analysis of the visual characteristics of sprint errors, the block pheromones of single frame sprint motion edge contour are obtained for clustering, and the sprint errors’ feature information is obtained and filtered. Sift technology is used to obtain the boundary contour line and implement the corner characteristics. The Hessian matrix of contour wave domain edge detection is used to calculate the contour wave domain matrix of the image and draw the contour curve of the image of sprint error action to realize the detection of sprint error action. The experimental results show that the proposed method has good stability and can effectively improve the detection accuracy and shorten the detection time.

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Section: Rfid Action Sensing Channel Parametersmentioning

confidence: 99%

Section: Analysis Of the Visual Characteristics Of Sprint Mistakesmentioning

confidence: 99%

Research on Real-Time Detection of Sprint Error Based on Visual Features and Internet of Things

Chen

2021

Security and Communication Networks

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“…When the composite is immersed into water, a layer of air bubbles forms at the interface of the composite (Figure S11), which, to a large extent, protects the conductive network from interference of water. The negligible resistance change may be caused by the water pressure or adsorption of water vapor …”

Section: Results and Discussionmentioning

confidence: 99%

Bioinspired Superhydrophobic and Durable Octadecanoic Acid/Ag Nanoparticle-Decorated Rubber Composites for High-Performance Strain Sensors

Wang

Xia

Wang

et al. 2021

ACS Sustainable Chem. Eng.

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Electrically conductive elastomer composites (CECs) show potential applications in wearable strain sensing. However, it remains a great challenge to develop a facile and versatile method to prepare multifunctional CEC strain sensors integrating superhydrophobicity, high electrical conductivity, strong interfacial adhesion, and excellent durability. Inspired by the surface superhydrophobicity of taro leaves, herein, a highly conductive and fluorine-free superhydrophobic CEC is fabricated by a novel "ion reduction and simultaneous molecule phase separation" method. Octadecanoic acid (OCA) with low surface energy can not only impart the CEC with superhydrophobic property and corrosive resistance but also greatly enhance the interfacial interaction between AgNPs. The obtained CEC shows high conductivity (21.9 S/cm) and superhydrophobicity (with a contact angle of 152.6°). The superhydrophobic CEC with excellent corrosion resistance can be used as strain sensors and shows large working strain and sensitivity (with a gauge factor of 61.8 at the strain range of 80−120%) and excellent cycle stability. Also, it can detect human motions in both ambient and underwater conditions, showing promising applications in underwater wearable electronics.

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“…Soft materials featured with anti-corrosion and flexibility are considered as a promising candidate, enabling piezoresistive [13][14][15], capacitive [16,17] and piezoelectric [7,18] mechanism for underwater sensing. Since the water environment may adversely affect the conductivity of the sensors, some strategies have been developed to tackle this problem, including superhydrophobic sealing [19][20][21][22][23], and polymer encapsulation [24][25][26]. Among them, the superhydrophobic sealing method heavily relies on the micro-nano-structures [15,19], where the long-term stability may experience unfavourable wettability failure.…”

Section: Introductionmentioning

confidence: 99%

Bioinspired Adaptive, Elastic, and Conductive Graphene Structured Thin-Films Achieving High-Efficiency Underwater Detection and Vibration Perception

et al. 2022

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Underwater exploration has been an attractive topic for understanding the very nature of the lakes and even deep oceans. In recent years, extensive efforts have been devoted to developing functional materials and their integrated devices for underwater information capturing. However, there still remains a great challenge for water depth detection and vibration monitoring in a high-efficient, controllable, and scalable way. Inspired by the lateral line of fish that can sensitively sense the water depth and environmental stimuli, an ultrathin, elastic, and adaptive underwater sensor based on Ecoflex matrix with embedded assembled graphene sheets is fabricated. The graphene structured thin film is endowed with favourable adaptive and morphable features, which can conformally adhere to the structural surface and transform to a bulged state driven by water pressure. Owing to the introduction of the graphene-based layer, the integrated sensing system can actively detect the water depth with a wide range of 0.3–1.8 m. Furthermore, similar to the fish, the mechanical stimuli from land (e.g. knocking, stomping) and water (e.g. wind blowing, raining, fishing) can also be sensitively captured in real time. This graphene structured thin-film system is expected to demonstrate significant potentials in underwater monitoring, communication, and risk avoidance.

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Underwater, Multifunctional Superhydrophobic Sensor for Human Motion Detection

Cited by 74 publications

References 51 publications

Research on Real-Time Detection of Sprint Error Based on Visual Features and Internet of Things

Research on Real-Time Detection of Sprint Error Based on Visual Features and Internet of Things

Bioinspired Superhydrophobic and Durable Octadecanoic Acid/Ag Nanoparticle-Decorated Rubber Composites for High-Performance Strain Sensors

Bioinspired Adaptive, Elastic, and Conductive Graphene Structured Thin-Films Achieving High-Efficiency Underwater Detection and Vibration Perception

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