Smart Materials and Structures
·
2017
·Vol. 26
·期 9
·095033
·
IF 2.909
Cuiping Mao,Huihui Zhang,Zhisong Lu
The development of textile-based devices for human physiological monitoring has attracted tremendous interest in recent years. However, flexible physiological sensing elements based on silk fabrics have not been realized. In this paper, ZnO nanorod arrays are grown in situ on reduced graphene oxide-coated silk fabrics via a facile electro-deposition method for the fabrication of silk-fabric-based mechanical sensing devices. The data show that well-aligned ZnO nanorods with hexagonal wurtzite crystalline structures are synthesized on the conductive silk fabric surface. After magnetron sputtering of gold electrodes, silk-fabric-based devices are produced and applied to detect periodic bending and twisting. Based on the electric signals, the deformation and release processes can be easily differentiated. Human arterial pulse and respiration can also be real-time monitored to calculate the pulse rate and respiration frequency, respectively. Throat vibrations during coughing and singing are detected to demonstrate the voice recognition capability. This work may not only help develop silk-fabric-based mechanical sensing elements for potential applications in clinical diagnosis, daily healthcare monitoring and voice recognition, but also provide a versatile method for fabricating textile-based flexible electronic devices.
研究领域:
生物医学工程
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材料科学
·
传感器技术
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产品关联
DOI
高影响因子
ACS Applied Materials & Interfaces
·
2024
·
IF 8.3
Xiaoguang Gao,Lin Yuan,Chengzhen Xue,Xiaoliang Zhang,Xuejuan Meng,Xiaochun Li
Flexible piezoresistive sensors with a porous structure that are used in the field of speech recognition are seldom characterized by both high sensitivity and ease of preparation. In this study, a piezoresistive sensor with a porous structure that is both highly sensitive and can be prepared by using a simple method is proposed for speech recognition. The preparation process utilizes the interaction of bubbles generated by ethanol evaporation and active agents with polydimethylsiloxane to produce a porous flexible substrate. This preparation process requires neither templates nor harsh experimental conditions such as a low temperature and a low pressure. Furthermore, the prepared piezoresistive sensor has excellent properties, such as a high sensitivity (27.6 kPa–1), a satisfactory response time (800 μs), and a good stability (10,000 cycles). When used for speech recognition, more than 1500 vocalizations and silent speech signals obtained from subjects saying numbers from “0” to “9” were collected by the sensor for training a convolutional neural network model. The average accuracy of the recognition reached 94.8%. The simple preparation process and the excellent performance of the prepared flexible piezoresistive sensor endow it with a wide application prospect in the field of speech recognition.
研究领域:
材料科学
·
电子工程
·
人工智能
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产品关联
DOI
PubMed
高影响因子
CHEMICAL ENGINEERING JOURNAL
·
2024
·
IF 13.3
Chunqing Yang,Dongzhi Zhang,Weiwei Wang,Hao Zhang,Lina Zhou
Flexible sensors exhibit exceptional mechanical adaptability, enabling them to accommodate diverse operational settings. They seamlessly conform to the deformation requirements of the human body or irregular object surfaces and have found extensive applications in human motion tracking, tire pressure monitoring, and human–computer interactions. Here, we have prepared a sandwich-structured MXene/helical multi-walled carbon nanotubes (Hs-MWCNTs) flexible strain sensor. The fabricated sensor has a wide detection range (0–77 %), high sensitivity (gauge factor 243.6 at 70–77 % strain), reliable repeatability (over 35000 s), and other excellent sensing performance. MXene/Hs-MWCNTs flexible strain sensor has significant advantages in detecting tiny signals such as human pulse and tire pressure. The constructed 4 × 4 flexible sensing arrays can achieve pressure distribution detection of objects with different shapes. In addition, based on MXene/Hs-MWCNTs flexible strain sensor and continuous wavelet transform convolutional neural network algorithms, speech recognition of some English words is successfully achieved with a recognition accuracy of 94.4 %. The results indicate that MXene/Hs-MWCNTs flexible strain sensor has great potential for application in fields such as human motion detection, health monitoring and speech recognition.
研究领域:
材料科学
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传感器技术
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机器学习
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产品关联
DOI
高影响因子
Advanced Science
·
2025
·
IF 14.1
Mengyao Gao,Weijie Liu,Kun Chen,Huili Sun,Xiaoqing Liu,Haonan Xing,Huatang Wang,Benpeng Zhu,Haizhong Guo
Hearing loss is among the most prevalent sensory impairments globally. Hearing aids assist individuals with hearing impairments in perceiving sound more effectively, serving as essential tools for reconnecting them with the world. Herein, an MXene/Polyvinyl Alcohol sound sensor (MPSS) capable of recognizing weak sound signals is developed. It can not only recognize different speech signals and sound properties but also show good stability in the process of long-term sound recording. In addition, by combining the sensor with machine learning, the accuracy rate of voiceprint recognition of wildlife conservation is up to 99%, underscoring its practical significance for wildlife protection. Utilizing piezoresistive effects, a hearing aid with a detection sound threshold of 60 dB and a frequency range of 20–4000 Hz is achieved, which provides a feasible scheme in hearing aids.
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
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产品关联
DOI
PubMed
高影响因子
Materials
·
2025
·Vol. 18
·期 9
·2014
·
IF 3.2
Tao Chen,Andeng Liu,Wentao Lei,Guoxu Wu,Jiajun Xiang,Yixin Dong,Yangyang Chen,Bingqi Chen,Meidan Ye,Jizhong Zhao,Wenxi Guo
Flexible wearable electronics face critical challenges in achieving reliable physiological monitoring, particularly due to the trade-off between sensitivity and durability in flexible electrodes, compounded by mechanical modulus mismatch with biological tissues. To address these limitations, we develop an anti-freezing ionic hydrogel through a chitosan/acrylamide/LiCl system engineered via the solution post-treatment strategy. The optimized hydrogel exhibits exceptional ionic conductivity (24.1 mS/cm at 25 °C) and excellent cryogenic tolerance. Leveraging these attributes, we construct a gel-based triboelectric nanogenerator (G-TENG) that demonstrates ultrahigh sensitivity (1.56 V/kPa) under low pressure. The device enables the precise capture of subtle vibrations at a frequency of 1088 Hz with a signal-to-noise ratio of 16.27 dB and demonstrates operational stability (>16,000 cycles), successfully differentiating complex physiological activities including swallowing, coughing, and phonation. Through machine learning-assisted analysis, the system achieves 96.56% recognition accuracy for five words and demonstrates good signal recognition ability in different ambient sound scenarios. This work provides a paradigm for designing environmentally adaptive wearable sensors through interfacial modulus engineering and ion transport optimization.
研究领域:
材料科学
·
生物医学工程
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传感器技术
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产品关联
DOI
PubMed
高影响因子
Nano-Micro Letters
·
2024
·Vol. 17
·期 1
·1-15
·
IF 31.6
Xiao Yanan,Li He,Gu Tianyi,Jia Xiaoteng,Sun Shixiang,Liu Yong,Wang Bin,Tian He,Sun Peng,Liu Fangmeng,Lu Geyu
Emphasized the innovation in both the material design and methodology between the sensing performance and mechanical properties.
The composite aerogel pressure sensors exhibited low hysteresis (13.69%), wide detection range (6.25 Pa-1200 kPa), and cyclic stability to acquire stable and accurate pronunciation signals.
Over 6888 and 4158 pronunciation signals were collected by the pressure sensor and utilized for training the convolutional neural network model, allowing for accurate recognition of six dialects (96.2% accuracy) and seven words (96.6% accuracy).
研究领域:
生物医学工程
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传感器技术
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人机交互
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语音信号处理
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功能材料
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可穿戴设备
✓ 已验证
DOI
高影响因子
JOURNAL OF COLLOID AND INTERFACE SCIENCE
·
2025
·
IF 9.7
Weiwei He,Puye Zhang,Zhonglue Hu,Shuai Yang,Wei Chen,Tianlong He,Lei Tang,Jiajia Zheng,Runsheng Li,Boce Xue,Guoqing Hu,Yanzhen Zhang
Amid the global wave of intelligentization, flexible pressure sensors have emerged as core sensing components owing to their excellent flexibility, portability, and highly sensitive response to pressure signals in fields such as human-computer interaction, health monitoring, smart wearable devices, and artificial-intelligence terminals. Herein, we developed a flexible pressure sensor with a hierarchically porous structure via a hybrid manufacturing strategy integrating three-dimensional (3D) printing and electrospinning. A MXene/silver nanowires/polydimethylsiloxane (MAP) conductive ink modified with nano silicon dioxide (SiO 2 ) was formulated to optimize printability, and the multi-scale porous sensing unit was constructed by direct ink writing (DIW) combined with a sacrificial template method, followed by encapsulation with a fibrous film electrode. Benefiting from the synergistic effect of macro-micro porous structure and the structural-mechanical matching design, the sensor exhibits high sensitivity (0.813 kPa −1 ), fast response (37 ms/30 ms), and an extremely low detection limit (1.47 Pa), thus enabling the effective monitoring of various human physiological motion signals and demonstrating significant potential in health monitoring applications. Furthermore, by integrating deep learning algorithms, high-accuracy recognition (94.9 %) of several spoken phrases is achieved, extending the sensor's applicability to human-computer interaction and intelligent speech perception. In summary, this study proposes a strategy based on a hybrid manufacturing technology for fabricating hierarchically porous flexible pressure sensors, demonstrating broad application prospects in health monitoring and smart human-computer interaction, thus providing new pathways for the innovative design and functional expansion of wearable electronic devices.
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产品关联
DOI
PubMed
高影响因子
Advanced Electronic Materials
·
2025
·
IF 5.3
Anqi Zhou,Wenchang Yi,Yingjun Wu,Ziyi Wu,Yawei Fu,Tang Liu,Huimin Li,Naizheng Bian,Song Liu
MXene aerogels, known for their exceptional conductivity, hold significant potential in the development of pressure sensors. However, the van der Waals forces that solely exist between pure MXene nanosheets are inadequate for forming aerogels with high elasticity and mechanical properties, thus restricting the broad application of MXene aerogels in sensor technology. In this research, reduced graphene oxide (RGO) is utilized as the primary framework and incorporate polyaniline (PANI) to enhance intermolecular interaction forces, employing freeze-drying techniques to fabricate 3D porous-structured MXene aerogels. This approach significantly enhances the elasticity and electrical responsiveness of the aerogel. The resulting aerogel-based pressure sensor exhibits high sensitivity (4 kPa −1 ), a wide linear response range (1–20 kPa), rapid response/recovery time (300/100 ms), and excellent stability. The sensor is capable of detecting a variety of pressure signals, from gentle breezes to human motion, and is applied in voice recognition. Using a machine learning framework based on feature engineering, it is possible to accurately identify and classify distinctly pronounced letters from sensor outputs with an accuracy rate as high as 98%. In summary, the high-performance flexible pressure sensor based on MXene aerogel shows great potential for applications in health monitoring, smart wearable devices, and artificial intelligence.
研究领域:
材料科学
·
传感器技术
·
纳米技术
·
柔性电子学
·
人工智能
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产品关联
DOI
高影响因子
ACS Applied Materials & Interfaces
·
2018
·
IF 8.097
Xiangsheng Han,Lili Lv,Daoyong Yu,Xiaochen Wu,Chaoxu Li
One-dimensional organic nanomaterials with a combination of electric conductivity, flexibility, and mechanical robustness are highly in demand in a variety of flexible electronic devices. Herein, conducting polymers were combined with robust Kevlar nanofibrils (aramid nanofibrils, abbreviated as ANFs) via in situ polymerization. Owing to the strong interactions between ANFs and conjugated polymers, the resultant core–shell ANFs showed high electric conductivity in combination with flexibility, robustness, physical stability, and endurance to bending and solvents, in sharp contrast to many inorganic conductive nanomaterials. Due to their responsivity of conductivity to different stimuli (e.g., humidity and strain), their membranes were capable not only of sensing human motions and speech words, but also of showing high sensitivity to variation of environmental humidity. In such a way, these core–shell ANFs may pave the way for combining both conductivity and mechanical properties applicable for diverse wearable devices.
研究领域:
材料科学
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纳米技术
·
柔性电子
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可穿戴设备
·
传感器
✓ 已验证
产品关联
DOI
PubMed
高影响因子
ADVANCED FUNCTIONAL MATERIALS
·
2025
·
IF 19
Kewei Zhao,Xianglei Zhao,Xin Guo,Yanyan Zhao,Mingqiong Tong,Lin Chen,Shujuan Zhuang,Xiangling Gu
Multifunctional hydrogels applied in flexible electronics and smart sensing face prominent challenges including functionality integration, environmental adaptability, and sustainability. This paper presents an anti-ion-regulated differential metal-ion coordination strategy to fabricate a multifunctional hydrogel (SP-M n+ X y− ) with switchable modules, recyclability, and time-dependent encryption. The SA-PAM double-network hydrogel, modulated by Fe 3+ and Ca 2+ (with Cl − or Ac − as counterions), exhibits distinct coordination behaviors: Fe 3+ demonstrates strong coordination due to high charge density, while Ca 2+ ’s binding is counterion-dependent–rapid network densification with CaCl 2 (fully dissociated Cl − ) versus controlled release with CaAc 2 (weakly dissociated Ac − ). The hydrogel achieves outstanding mechanical strength (0.52 MPa), wide sensing range (300%), fast response (114 ms), and freeze resistance (−20 °C). Reversible chelation of ethylene diamine tetraacetic acid enables efficient switching among conductive, adhesive, and sensing modules (performance decay < 17.95% after cycles). Leveraging Fe 3+ /Ca 2+ coordination kinetics, time-dependent color changes enable dynamic encryption. With high conductivity (15.1 S·m −1 ) and self-adhesion (9.5 kPa), the hydrogel serves as a wearable sensor for motion tracking, speech recognition, and electrocardiograph monitoring. Key innovations are achieved in this work, including: anti-ion-mediated precise property control, green fabrication of recyclable, multi-modal hydrogels, and kinetic-driven encryption, which advances hydrogel design for flexible electronics, sensing, and information security. Graphical Counterion-Mediated Differential Metal Coordination enables recyclable, multifunctional hydrogels (SP-M n+ X y− ) with switchable conductive/adhesive/sensing modules and time-dependent encryption, which yields advancing wearable electronics with the capability of motion/speech/ECG monitoring, self-power supply, and secure time-dependent information coding.
研究领域:
材料科学
·
高分子化学
·
柔性电子器件
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传感器技术
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生物医学工程
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信息安全
✓ 已验证
产品关联
DOI
高影响因子
ACS Applied Polymer Materials
·
2024
·
IF 4.4
Chenkai Zhu,Zhenzong Shao,Baoning Chang,Yong Wang,Ting Yu,Changyong Huang,Yang Yang,Xilun Ding,Fei Liu,Wuxiang Zhang
Flexible strain sensors based on hydrogels have shown promising application prospects in artificial tissue and body deformation monitoring. However, hydrogel-based sensors with ideal structural performance, self-healing ability, strain detection, and tissue adhesion remain challenging. Herein, a dual-network hydrogel (PG-B-T) flexible sensor based on poly(vinyl alcohol) (PVA) and gelatin was developed, which were multidynamically cross-linked via the one-pot approach. The noncovalent bonds of gelatin cross-linked by tannic acid (TA) could form the first network and impart structural stability with antibacterial performance, while the second network constructed with reversible borate ester bonds by PVA and borax showed the capability of self-healing and electric conductivity. As such, the prepared PG-B-T hydrogel demonstrated exceptional ductility (strain >1000%) and high sensitivity (GF = 2.51). In air or an underwater environment, the PG-B-T hydrogel can perform a wide working range, such as self-healing capability, electrical properties, and sensing properties. Meanwhile, the hydrogen bonds of gelatin enabled strong adhesion to some classic substrates, not only allowing the hydrogel to monitor body movements and detect vocal vibration signals but also achieving underwater information transmission of Morse code via finger movement. Consequently, this work provided a significant strategy for developing multifunctional hydrogels as strain-sensitive sensors that could conveniently and effectively detect motion variation.
研究领域:
材料科学
·
生物医学工程
·
传感器与执行器
·
纳米技术
·
软体机器人
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产品关联
DOI
高影响因子
ADVANCED MATERIALS
·
2025
·Vol. 37
·期 40
·e03926
·
IF 26.8
Jianyu Pu,Yuantao Zhang,Huiming Ning,Yuanhao Tian,Chenxing Xiang,Hui Zhao,Yafeng Liu,Alamusi Lee,Xinglong Gong,Ning Hu,Tonghua Zhang,Shu Wang
Iontronic pressure sensors are widely used in human motion monitoring and human–machine interactions owing to their high sensitivity, wide measurement range, and excellent resolution. However, conventional dielectric layer designs often involve complex fabrication processes, high costs, and limited performances. This paper proposes a novel sensor structure, the dual-dielectric-layer iontronic pressure sensor (DLIPS), which integrates high- and low-permittivity layers. Validated using silkworm cocoon ion gel and open-cell polyurethane foam as dielectrics, the DLIPS exhibited ultrahigh sensitivity (72548.7 kPa −1 ), a wide working pressure range (0.001–420 kPa), an exceptionally low detection limit (0.832 Pa), and remarkable durability exceeding 5000 cycles. By leveraging the distinct responses of the capacitance and resistance to pressure and temperature, the sensor can simultaneously measure both parameters. A deep learning regression model is integrated to decouple the mixed temperature and pressure signals, enabling accurate identification. Owing to its ultrahigh sensitivity and capability to detect minute pressure fluctuations, the DLIPS exhibited strong potential for skin-mounted silent speech recognition systems, achieving a recognition accuracy of up to 98.5%. Furthermore, the DLIPS provides a cost-effective and scalable approach for fabricating ultrahigh-sensitivity pressure sensors, underscoring its versatility in wearable technology applications.
研究领域:
可穿戴电子学
·
传感器与传感技术
·
人机交互
·
柔性电子学
·
信号处理中的人工智能
✓ 已验证
产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）