ADVANCED FUNCTIONAL MATERIALS
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2024
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IF 18.5
Bin Li,Ruiqing Ge,Wenwen Du,Zhenning Wang,Tao Peng,Ruojiang Wang,Yu Chang,Tingrui Pan
Woodwork is involved in a variety of interactions with humans through physical contact, which may reveal valuable information if the tactile data can be unnoticeably extracted. In this work, an intelligent iontronic wood (iWood) device, along with its seamlessly integrated architecture into the woodwork, enabled by the iontronic sensing principle, is implemented. Notably, the tactile sensing structure is generated at the iontronic interface between ionic and conductive woods. In particular, the ionic wood is established by infusing an ionic liquid into the wood, followed by immobilizing it via chemical bonding, presenting both prominent ionic conductivity and excellent stability under pressure. By formatting the woods into identical strips, the high-density tactile sensing array can be simply formed by a braiding process for a scalable interwoven structure. As a result, the iWood device has offered a high sensitivity over a broad detection of 0.5 MPa and an array of 40 × 90 units covering an area up to 3600 cm 2 . The iWood device is showcased as an interactive human interface, demonstrating its potential as a smart desktop capable of gesture and object recognition, a health-tracking chair for real-time ballistocardiograph monitoring, and an embedded intelligent floor for weight management and gait analysis.
研究领域:
材料科学
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生物医学工程
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人机交互
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产品关联
DOI
高影响因子
Energy Technology
·
2021
·Vol. 9
·期 7
·2100166
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IF 3.631
Zhiqi Zhao,Qiujin Li,Yu Dong,Jixian Gong,Zheng Li,Xiran Qiao,Jianfei Zhang
Nowadays, flexible piezoresistive sensors have drawn considerable attention in e-skin, motion monitoring devices, etc. Wearability is an important nature of various flexible sensors. Herein, a sensitive flexible piezoresistive pressure sensor with gold nanowires (AuNWs) combined textile with high sensitivity and durability is presented. The knitted cotton fabric is used as the matrix for loading conductive material AuNWs to fabricate the wearable pressure sensors as clothing components. Cotton fabric can be easily transformed into conductive textile due to impregnation and combination with AuNWs. This AuNWs/textile material is demonstrated to be an appropriate flexible sensor to monitor various human motions, such as finger pressing, joints bending, and foot status. A smart glove is integrated with this AuNWs/textile as the sensing block for gesture expression and recognition, signal reading, and transmission. Besides the common gesture with finger movement combination, e.g., numbers, the simple AuNWs/textile-based smart glove can also serve for expressing some emoji symbol and be considered as a human–machine interface for some gesture emoji used in internet social platform. This AuNWs/textile is expected to be used as a practical wearable sensor with great potential for extensive applications, including human–machine interface, healthcare monitoring, and the Internet of Things construction.
研究领域:
材料科学
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生物医学工程
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电子皮肤
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产品关联
DOI
高影响因子
IEEE Systems Man and Cybernetics Magazine
·
2024
·Vol. 10
·期 1
·28-40
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IF 1.9
Shumi Zhao,Liwen Xie,Yang Song,Yan Tang,Zhijun Li,Peng Shi,Cheng Chen,Jianwei Liu
Robots want to collaborate with humans or mimic human actions, needing various flexible sensors. Flexible skin electrodes are used as human–robot interfaces (HRIs), providing an opportunity for sensing interactions between robot and user. However, traditional electrodes with low skin adhesion prevent their applications in human-assisted robots, especially sweat on the skin surface, resulting in them slipping and even falling off. Thus, sodium casein (SC) is used for improving polyacrylamide (PAAM) hydrogel to fabricate PAAM-SC-conductive hydrogel with excellent conductivity and mechanical properties. The strong interaction of PAAM-SC improves its adhesion, which has an elongation at a break of roughly 3,000%. Additionally, it exhibits extremely low resistance (< 5kΩ), which can be used for electromyography (EMG) sensing. Herein, flexible skin electrodes with four-layer structures are designed. To fabricate flexible skin electrodes for hand gesture recognition, a 3D printer is employed to pattern high-performance Ag wires with structurally soft and stretchable filamentary serpentines to connect an external circuit and the PAAM-SC-conductive hydrogel. Based on the Transformer network model analysis, the classification results in cross validation are more than 85%. Notably, the PAAM-SC hydrogel as a strain sensor attached to a robotic finger can quickly respond to robotic finger movements. We might anticipate that our strategy will improve the harmonized integration between flexible electronics and human skin for smart HRIs, and when a corobot is equipped with the PAAM-SC-conductive hydrogel, the robots can interact and collaborate with humans seamlessly through active perception and matching.
研究领域:
生物医学工程
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机器人学
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产品关联
DOI
高影响因子
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
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2024
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IF 11.2
Wen Li,Shunxin Wu,Meicun Kang,Xiaobo Zhang,Xiyang Zhong,Hao Qiao,Jinghan Chen,Ping Wang,Luqi Tao
As the Internet of Things advances, gesture recognition emerges as a prominent domain in human-machine interaction (HMI). However, interactive wearables based on conductive hydrogels for individuals with single-arm functionality or disabilities remain underexplored. Here, we devised a wearable one-handed keyboard with gesture recognition, employing machine learning algorithms and hydrogel-based mechanical sensors to boost productivity. PCG (PAM/CMC/rGO) hydrogels are composed of polyacrylamide (PAM), sodium carboxymethyl cellulose (CMC), and reduced graphene oxide (rGO), which function as a strain, pressure sensor, and electrode material. The PAM chains offer the gel's elasticity by covalent cross-linking, while the biocompatible CMC improves the dispersion of rGO and promotes electromechanical properties. Integrating rGO sheets into the polymer matrix facilitates cross-linking and generates supplementary conductive pathways, thereby augmenting the gel system's elasticity, sensitivity, and durability. Our hydrogel sensors include high sensitivity (gage factor (GF) = 8.18, 395.6 %–551.96 %) and superior pressure sensing capabilities (Sensitivity ( S ) = 0.3116 kPa –1 , 0–9.82 kPa). Furthermore, we developed a wearable keyboard with up to 98.13 % accuracy using convolutional neural networks and a custom data acquisition system. This study establishes the groundwork for creating multifunctional gel sensors for intelligent machines, wearable devices, and brain-computer interfaces.
研究领域:
生物医学工程
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材料科学
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人工智能
✓ 已验证
产品关联
DOI
高影响因子
Advanced Sensor Research
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2024
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IF 0
Yixin Xu,Lianjun Deng,Yuyao Lu,Jianhuan Zhang,Zhouyi Xu,Kaichen Xu,Chentao Zhang
Epidermal electronics that can monitor physiological signals such as surface electromyogram (sEMG) signals attract widespread attentions in personalized healthcare, human–machine interfaces (HMI) and virtual/augmented reality (AR/VR). However, conventional electromyographic electrodes suffer from skin discomfort, susceptibility to motion artifact interference, and short service lifetime. Here, an organohydrogel-based sEMG electrode endows with high conductivity, low modulus and long-term stability is developed by doping partially reduced graphene oxide (pRGO) into highly cross-linked organohydrogel network. The as-fabricated polyacrylamide/sodium alginate/tannic acid/partially reduced graphene oxide (PAM/SA/TA/pRGO) organohydrogel possesses farewell conductivity (4.22 S m −1 ) while preserving tissue-like compliance (Young's modulus ≈32 KPa), excellent stretchability (≈600%), high adhesion as well as superior anti-drying properties. In addition, a stretchable sEMG electrode for long-term reliable service is fabricated via immobilizing the organohydrogel electrodes onto a flexible very high bond (VHB) substrate. As a result, the integrated electrodes show high signal-to-noise ratio (SNR) (35.15 db) comparable to that of the commercial electrodes. Furthermore, with assistance of deep learning, the proposed sEMG electrodes obtain high identification accuracy of 97.11% in distinguishing sophisticated gestures. This system can be further exploited for real-time tele-operations and offers broad prospects in human–machine immersive interactive application.
研究领域:
生物医学工程
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柔性电子学
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人机交互
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信号处理
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DOI
Journal of Materials Chemistry A
·
2024
·Vol. 12
·期 44
·30298-30308
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IF 10.7
Fan Chen,Xian Song,Jingjing Fu,Jiaheng Liang,Junhua Zhou,Jiehua Cai,Yufei Zhang,Mengjia Zhu,Yichun Ding,Jinxing Jiang,Zijian Chen,Youchao Qi,Zhihao Zhou,Qiyao Huang,Yingying Zhang,Zijian Zheng
Self-powered human motion electronic skins (E-skins) hold significant potential for intelligent sports, healthcare, and human–machine interactions. However, the limited permeability to air and moisture, along with poor stretchability, impedes the wearing comfort, long-term application, and skin compliance of self-powered E-skins. Here, we present an all-fibrous, permeable, adhesive, and intrinsically stretchable electronic skin (PASE-skin). The PASE-skin employs core-sheath fiber mats, liquid-metal-fiber mats, and acrylic fiber mats as the triboelectric layer, electrode layer, and skin adhesive layer, respectively, to achieve an all-fibrous and intrinsically stretchable structure. Such a material and structural design simultaneously offer exceptional stretchability, minimal residual strain, textile-like breathability, skin adhesion, biocompatibility, and good sensing performance. The core-sheath structure increases the stretchability of the triboelectric layer threefold, from 200% to 600%. The liquid-metal-fiber mat electrode maintains stable conductivity even under extreme strains (900%) and numerous stretching cycles (10 000 times at 100% strain). The E-skin generates significant triboelectric outputs and maintains stable sensing performance up to 450% strain. Consequently, we have developed a 5-channel human motion sensing system based on PASE-skin, capable of real-time sign language recognition assisted by signal processing and machine learning algorithms. The PASE-skin is poised to make a substantial impact on the development of self-powered human motion E-skins and offers novel insights into the field of sign language recognition.
研究领域:
材料科学
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生物医学工程
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人工智能
✓ 已验证
DOI
高影响因子
Advanced Materials Technologies
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2024
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IF 6.4
Qiuping Wu,Duixin Ma,Xingyu Tao,Fengxia Wu,Guanglin You,Bingzhen Wang,Jianping Sun,Shaohong Shi
Modern materials with unique structures and functions are inspired by nature. However, nature's craftsmanship is beyond the reach of traditional handmade techniques. 3D printing technology creates the possibility of creating bionic structures. In this study, inspired by the ability of spiders to sense the capture of prey through the vibration of their webs, a spider-web-like, highly sensitive hydrogel sensor is designed and printed. The hydrogel is made of eco-friendly green polyvinyl alcohol cross-linked with microcrystalline cellulose. Surprisingly, the 3D-printed hydrogel sensor can manipulate the sensitivity by changing the angle and strain range of the structure. Accordingly, the Gauge factor (GF) of the 3D-printed hydrogel ( θ = 60°) is up to 58.23, which is 23.9 times higher than that of the non-3D-printed hydrogel sensor (GF = 2.43). The GF of the 3D-printed hydrogel at other angles still remained high at 24.74 ( θ = 90°) and 12.31 ( θ = 120°), respectively. It can be seen that the 3D-printed hydrogel sensor has advanced performance. In addition, an intelligent gesture recognition system for human–computer interaction is constructed using 3D-printed hydrogel sensors, which offers potential prospects for helping people communicate.
研究领域:
材料科学
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生物仿生学
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电子工程
✓ 已验证
产品关联
DOI
高影响因子
IEEE SENSORS JOURNAL
·
2024
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IF 4.3
Tianqing Liu,Yutao Rong,Gandong Zhou,Guangjian Zhang,Chen Su,Peipei Li,Xiaoqiang Yin,Gang Wang,Weiwei Wu,Lu Zhang
Wearable humidity sensors have attracted extensive interest because of their affordability, high sensitivity, portability, and ease of use in the rapidly developing fields of noncontact medical diagnostics, healthcare monitoring, and environmental sensing. However, achieving a high-performance and stable wearable humidity sensor for healthcare monitoring, such as respiration, is still challenging. In this work, we propose a simple direct-writing method for the in situ fabrication of wearable resistive-type humidity sensors based on Ti3C2Tx metal carbides/nitrides (MXene). The sensing performance of MXene/PP composite-based humidity sensors has been thoroughly investigated, including sensitivity (0.601%/%RH), response/recovery time (17/37 s), and stability (20 h under 84% RH). Moreover, we demonstrate that the proposed wearable humidity sensor can accurately recognize different breathing patterns and monitor human respiration in real time, enabling the evaluation of physiological conditions for early warning. In addition, it can easily monitor sleep quality and rapidly identify any issues with mask use. Even more, an MXene/PP composite-based humidity sensor matrix can be applied for noncontact gesture tracing. Therefore, this work provides a practical solution for the fabrication of wearable, high-performance humidity sensors for individualized healthcare monitoring in real time, which paves a solid path for the creation of personalized healthcare monitoring devices.
研究领域:
材料科学
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生物医学工程
·
传感技术
✓ 已验证
产品关联
DOI
高影响因子
CHEMICAL ENGINEERING JOURNAL
·
2024
·
IF 13.3
Mengru Geng,Xiaosen Pan,Jiaqi Zhao,Xiaojuan Wang,Ruiming Liu,Zijun Xu,Ning Ma,Meng Gao,Mingzhe Shao,Jie Li
Perovskite is proven to promote the surface dissociation of water molecules that are therefore applied in humidity-responsive electronics. However, inherent defects in crystals severely hinder structural stability and charge transfer which decline the performance of the devices. For this, we design a strategy to introduce Cs 2 SnCl 6 perovskite into the graphene oxide reduction system, during which the growth and optimization of perovskite crystals are achieved, accompanied by the formation of interface coordination with semi-reduced graphene oxide, obtaining stability and durability humidity-sensitive non-contact sensors. The results prove that the sensor exhibits low latency in response (0.8 s) and recovery (1.9 s), excellent sensitivity (6.5 × 10 6 ), and long-term stability (over 240 days). Additionally, distinguishable signals can be output easily in multiple different non-contact sensing applications and gesture recognition applications can be successfully implemented, which provides a possibility of human–computer interaction.
研究领域:
材料科学
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电子工程
·
传感器技术
✓ 已验证
产品关联
DOI
高影响因子
Nano Energy
·
2024
·
IF 16.8
Wei Guo,Zhongzheng Fu,Tianzhao Bu,Zhixin Wang,Han Fang,Sen Zhou,Jian Huang,Hao Wu
The highly flexible wearable device for human-machine interaction is a burgeoning technology that has garnered considerable attention among researchers. However, current wearable devices such as data gloves, wrist bands and exoskeleton devices require additional fixation aids, which interfere with the users’ movements and cause discomfort. Here, a flexible on-skin triboelectric sensor is developed for high-precision human-machine interaction, which is in the form of a thin film containing a soft substrate and two triboelectric layers with mismatched elastic modulus . The on-skin triboelectric sensors can be mounted on the forearm epidermis by their own adhesion, which is rarely perceptible and does not impede hand and wrist mobility. On the basis, the sensors can accurately measure the tiny deformations caused by muscle movement. Meanwhile, a heterogeneous parallel channel fusion (HPCF) model is proposed for advanced signal processing and recognition of sensor data, where varying signal features are extracted by different-sized convolutional kernels. The human-machine interaction system by combining the on-skin triboelectric sensors and algorithm achieves up to 99.12% accuracy when identifying 26 distinct gestures, which holds vast potential in several areas, such as gesture recognition, virtual reality, and teleoperation .
研究领域:
生物医学工程
·
材料科学
·
人工智能
✓ 已验证
产品关联
DOI
高影响因子
ACS Applied Electronic Materials
·
2021
·
IF 3.314
Min Li,Jian Qiao,Chengfeng Zhu,Yimin Hu,Kunjie Wu,Sha Zeng,Wei Yang,Huichao Zhang,Yulian Wang,Yulong Wu,Runbin Zang,Xiaona Wang,Jiangtao Di,Qingwen Li
Piezoionic materials are potential smart soft materials because of their similarity to biological systems in signal generation and transmission but still have limited use due to their intrinsic low response strain, noisy signal output, and complex structure. We report herein that the piezoelectric effect can be observed on an electrolyte-coated high-surface-area carbon nanotube yarn, generating large lengthwise voltage gradients without the assistance of an external electrical bias when the yarn was stretched. A mechanism of dynamic structure-nonuniform-induced ion squeezing is proposed to explain the electricity generation along the conductive piezoionic yarn. Between the two ends of the yarn, sensitive and high-recognition voltage signals with ultralow noise are generated, when the yarn is subjected to mechanical stretching at a wide range of strains and frequencies. The voltage polarity is tuned by selecting a proper type of absorbed ions. Knitting of the piezoionic yarns as a self-powered sensor into a glove is demonstrated for precisely recognizing hand gestures and human–machine interactions. Because of features such as a simple structure, easy fabrication, high flexibility and stretchability, and a wide range of response, this piezoionic yarn is promising for smart textiles, wearable sensing devices, and implantable artificial muscle feedbacks.
研究领域:
材料科学
·
智能纺织品
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生物医学工程
✓ 已验证
DOI
高影响因子
IEEE SENSORS JOURNAL
·
2024
·
IF 4.3
He Yu,Guan-Ya Zhou,Yu-Bing Liu,Hao-Bin Li,Lin Song,Chang-Yun Kun Xiao,Mu-Gen Peng
Carbon-based nanomaterials, particularly graphene, have garnered significant attention across diverse fields owing to their remarkable properties and versatile applications. Among these, laser-induced graphene (LIG) exhibits high porosity, excellent conductivity, and mechanical flexibility, which can be obtained through laser irradiation of carbon-rich precursors. This article introduces a novel flexible tactile sensor based on LIG/multiwalled carbon nanotube (MWCNT) composites. The surface is treated with spraying SiO2 and precured Ecoflex to form superhydrophobic property with water contact angle (WCA) of 153.4°, which is suitable for underwater condition. Enhanced with deep learning algorithms, the LIG/MWCNT sensors are integrated into a data glove, enabling precise recognition of Arabic sign language gestures with accuracy of 99.34%. The data glove equipped with the sensor can communicate wirelessly with a smartphone App via Bluetooth low energy (BLE) by a low-power and secure wireless protocol. The App displays the finger bending status and the recognized gestures in real time, and also provides feedback to the user. This work showcases the feasibility of the proposed sensing system for gesture recognition and the potential applications in underwater wearable electronics. Based on the excellent performance of the proposed sensing system, this article contributes to advancing the interdisciplinary research field of carbon-based flexible electronics and deep learning-based sensing applications.
研究领域:
材料科学
·
电子工程
·
人工智能
✓ 已验证
产品关联
DOI
高影响因子
危险品化学品经营许可证（带存储）