Cellulose nanocrystalline hydrogel based on a choline chloride deep eutectic solvent as wearable strain sensor for human motion

Wang, Huiqiang; Li, Jiachen; Yu, Xin; Yan, Guoliang; Tang, Xing; Sun, Yong; Zeng, Xianhai

doi:10.1016/j.carbpol.2020.117443

Cited by 68 publications

(34 citation statements)

References 52 publications

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“…In the x-axis direction, the number of the recognition points can reach to 20000. And in the previous work [12][13][14]26], the number can be less than 3000, which means that by this method, we can generate a recognition map over 10 times compared with the traditional single-correlation motion system. As an example, for different positions in x and y, the planes would be quite different, and when the x position is in about 550 cm and y position is in about 20 cm, the intensity of the conjunction would be around the max value.…”

Section: Resultsmentioning

confidence: 99%

“…It would be challenging to use only the rich detail information of RGB to model spatiotemporal channels and to estimate the real 3D spatial movements, such as those along the direction of view (perpendicular to the image plane), for which there is a lack of certain recognition ability. Under the circumstance that various environmental factors are relatively complex ring scenes and the rich detailed information of RGB is not distinguishable for human actions, taking the depth information in the scene becomes a popular idea of the human action recognition method [13]. Earlier the depth information in the acquired scenes was captured by laser sensors.…”

Section: Introductionmentioning

confidence: 99%

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[Retracted] Feature Recognition of Human Motion Behavior Based on Depth Sequence Analysis

Zhao

2021

Complexity

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The current research on still image recognition has been very successful, but the study of action recognition for video classes is still a challenging topic. In this work, we propose a random projection-based human action recognition algorithm to address the lack of depth information in color information (RGB video frames) that is not easily affected by environmental factors such as illumination and the lack of ability to recognize actions along the direction of view. A network structure is designed to take the obvious advantage of long- and short-term memory networks for controlling and remembering long sequences of historical information. The network structure in this paper is constituted by multiple memory units. At the same time, this paper constructs the spatial features, temporal features, and depth features of the three recognition stream outputs into a feature matrix, whose feature matrix is divided into multiple temporal segments according to the temporal dimension, then inputs them into the network layer in order, and achieves the fusion of the feature matrix in this paper according to their correlation characteristics on the temporal axis. Here, we proposed the concept of random batch projection operators. This basically uses as much sublimitation information as possible to improve projection accuracy by randomly selecting several subdependencies as projections defined during projection. A compressed sensing design of human motion acceleration data for low-power body area networks is proposed, and the basic idea and implementation process of compressed sensing theory for human motion data compression and reconstruction in wireless body area networks are introduced in detail.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

[Retracted] Feature Recognition of Human Motion Behavior Based on Depth Sequence Analysis

Zhao

2021

Complexity

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“…Based on the research mentioned above, it can be concluded that the development of cellulose‐based supramolecular hydrogels will be even more promising in the future. As one of the most prominent types of polymers employed in biomedical fields, cellulose‐based hydrogels have great applications potential for biomimetic materials including wound dressing, cell culture, tissue engineering, cosmetics and soft robotics 92–100 …”

Section: Discussionmentioning

confidence: 99%

Cellulose‐based hydrogels regulated by supramolecular chemistry

Zeng

Sun

et al. 2021

SusMat

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Supramolecular hydrogels based on cellulose attract increasing attention because of their novel structures and broad potential applications. In this review, hydrogels composed of cellulose are summarized according to category of supramolecular interactions in the networks including hydrogen bonds, electrostatic interactions, host‐guest interactions, and others. Supramolecular cellulose‐based hydrogels constructed by noncovalent bonding usually exhibit environmental friendliness, designing flexibility and diverse functions, and their properties are variable with incorporating different interactions in hydrogel networks. Moreover, with proper structures and networks, the supramolecular cellulose‐based hydrogels are adaptable in diverse fields of research and practical applications, such as self‐healing, shape memory, drug delivery, and some other renewable/sustainable materials. The future developments and challenges of the supramolecular hydrogels based on cellulose are discussed as well.

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“…Many materials for soft strain gauges have been developed, including Ag nanowire aerogels [32], stick-on hydrogel [33], cellulose nanocrystalline hydrogel [34], carbon black/ Ecoflex TM (Smooth-On, Inc., Macungie, PA, USA) composite [35], carbon nanotube/styrenebutadiene-styrene [36], as well as carbon black/silicone composite [19]. Herein, a carbon/silicone nanocomposite developed in our previous research [37] will be printed onto the conversion structure as strain gauges, owing to its sufficient sensitivity, good linearity, and excellent repeatability for a strain up to 50%, as well as its low cost and compatibility with silicone.…”

Section: Hysteresis Of the Materials For Strain Gaugementioning

confidence: 99%

Carbon/Silicone Nanocomposite-Enabled Soft Pressure Sensors with a Liquid-Filled Cell Structure Design for Low Pressure Measurement

Wang

Tao

2021

Sensors

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In the fields of humanoid robots, soft robotics, and wearable electronics, the development of artificial skins entails pressure sensors that are low in modulus, high in sensitivity, and minimal in hysteresis. However, few sensors in the literature can meet all the three requirements, especially in the low pressure range (<10 kPa). This article presents a design for such pressure sensors. The bioinspired liquid-filled cell-type structural design endows the sensor with appropriate softness (Young’s modulus < 230 kPa) and high sensitivity (highest at 0.7 kPa−1) to compression forces below 0.65 N (6.8 kPa). The low-end detection limit is ~0.0012 N (13 Pa), only triple the mass of a bee. Minimal resistance hysteresis of the pressure sensor is 7.7%. The low hysteresis is attributed to the study on the carbon/silicone nanocomposite, which reveals the effect of heat treatment on its mechanical and electromechanical hysteresis. Pressure measurement range and sensitivity of the sensor can be tuned by changing the structure and strain gauge parameters. This concept of sensor design, when combined with microfluidics technology, is expected to enable soft, stretchable, and highly precise touch-sensitive artificial skins.

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Cellulose nanocrystalline hydrogel based on a choline chloride deep eutectic solvent as wearable strain sensor for human motion

Cited by 68 publications

References 52 publications

[Retracted] Feature Recognition of Human Motion Behavior Based on Depth Sequence Analysis

[Retracted] Feature Recognition of Human Motion Behavior Based on Depth Sequence Analysis

Cellulose‐based hydrogels regulated by supramolecular chemistry

Carbon/Silicone Nanocomposite-Enabled Soft Pressure Sensors with a Liquid-Filled Cell Structure Design for Low Pressure Measurement

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