Journal of Materials Chemistry A
·
2024
·Vol. 12
·期 27
·16839-16853
·
IF 10.7
Mingyu Qi,Dongzhi Zhang,Yihong Guo,Hao Zhang,Jiahui Shao,Yanhua Ma,Chunqing Yang,Ruiyuan Mao
The use of conventional wearable sensors in underwater settings is often impeded by issues such as water swelling, reduced conductivity, and poor adhesion, hindering the progress of underwater sensing technologies. In this study, a double network hydrogel was developed by combining bacterial cellulose (BC) with a copolymer of acrylic acid (AA) and sulfobetaine methacrylate (SBMA). This hydrogel, leveraging the combined effects of hydrophobic association and electrostatic interactions, demonstrated exceptional anti-swelling properties. The presence of numerous hydrogen bonds and dynamic coordination bonds within the hydrogel network conferred remarkable stretchability (>1304%), high toughness (1.3 MJ m−3), and high sensitivity (GF = 2.14). Wearable sensors utilizing this hydrogel were able to precisely and consistently capture real-time motion signals from various environments, including air, underwater, and seawater. Employing a two-dimensional convolutional neural network (2D-CNN) deep learning algorithm to integrate and analyze underwater swimming data, the sensors accurately identified and classified 16 swimming postures with a recognition accuracy of 99.37%, offering a novel solution for safety alerts and postural adjustments during underwater activities. This research introduces innovative approaches for developing high-performance wearable sensors for underwater applications, with promising applications in intelligent sensing and human–computer interaction fields.
研究领域:
材料科学
·
生物医学工程
·
人工智能
✓ 已验证
产品关联
DOI
高影响因子
Journal of Materials Chemistry C
·
2025
·
IF 5.1
Daihui Zhang,Chunqing Yang,Jun Wang,Yukun Liu,Jiahui Shao,Dongzhi Zhang
In recent years, flexible wearable pressure sensors have emerged as a pivotal technology in the realms of intelligent health monitoring and artificial intelligence, steadily gaining traction as a prominent research focus. However, the conventional production process for conductive fillers is often cumbersome and costly, which limits their widespread application and large-scale manufacturing. In this study, a flexible pressure sensor based on polypropylene fluted woven fabric MXene/PS was proposed. The flexible pressure sensor uses spin-coated PS surface encapsulation technology to make the fabric surface hydrophobic, in order to improve the stability of the sensor. The sensor exhibits a wide strain range (0–565 kPa), excellent repeatability and stability (over 15 000 s), and a fast response–recovery time (75/159 ms), which can be attributed to the superior mechanical properties of the polypropylene-potted woven fabric. The MXene/PS pressure sensor can detect subtle deformations of small and medium-sized joints, making it suitable for detecting human motion signals. Additionally, combined with the deep belief network (DBN) algorithm, it can efficiently and accurately recognize human yoga postures, which shows its great application potential in human motion posture monitoring and low-cost flexible electronic products.
研究领域:
材料科学
·
人工智能
·
健康监测
✓ 已验证
产品关联
DOI
高影响因子
BIOSENSORS & BIOELECTRONICS
·
2023
·
IF 12.6
Jize Liu,Wei Zhao,Jiakai Li,Chaofan Li,Shuting Xu,Yang Sun,Zhichao Ma,Hongwei Zhao,Luquan Ren
The accurate monitoring of respiratory events and human motion states holds paramount importance in the realm of health surveillance and disease prognostication. An exquisitely precise, multifaceted, portable, and environmentally resilient sensor designed for health monitoring would undeniably be of utmost desirability , despite its persisting as a formidable challenge. Here, we propose a breath monitoring and posture recognition system that utilizes hydrogel electrolytes based on polyvinyl alcohol, sodium alginate , and starch , suitable for supercapacitors and multimodal wearable sensors . The multimodal smart sensors can independently detect mechanical and thermal changes through the output signals of capacitance and resistance, respectively. Moreover, we have cultivated an artificial neural network to achieve a finger-pressing posture recognition accuracy of up to 99.259%. Our hydrogel sensors have also been successfully employed in the diagnosis of obstructive sleep apnea syndrome. The flexible electronic device derived from this study exhibit a plethora of functionalities, thereby affording a novel perspective for the design and fabrication of advanced flexible electronic contrivances that find applications across diverse domains such as medicine and virtual reality.
研究领域:
生物医学工程
·
材料科学
·
健康监测技术
✓ 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）