SENSORS
·
2021
·Vol. 21
·期 17
·5964
·
IF 3.576
Wei Liu,Yineng Xiao,Xiaoming Wang,Fangming Deng
This paper presents a hydrogel-based flexible sensor array to detect plantar pressure distribution and recognize the gait patterns to assist those who suffer from gait disorders to rehabilitate better. The traditional pressure detection array is composed of rigid metal sensors, which have poor biocompatibility and expensive manufacturing costs. To solve the above problems, we have designed and fabricated a novel flexible sensor array based on AAM/NaCl (Acrylamide/Sodium chloride) hydrogel and PI (Polyimide) membrane. The proposed array exhibits excellent structural flexibility (209 KPa) and high sensitivity (12.3 mV·N−1), which allows it to be in full contact with the sole of the foot to collect pressure signals accurately. The Wavelet Transform-Random Forest (WT-RF) algorithm is introduced to recognize the gaits based on the plantar pressure signals. Wavelet transform realizes the signal filtering and normalization, and random forest is responsible for the classification of the processed signals. The classification accuracy of the WT-RF algorithm reaches 91.9%, which ensures the precise recognition of gaits.Keywords:plantar pressure detection;gait recognition;flexible hydrogel sensor
研究领域:
生物医学工程
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康复医学
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产品关联
DOI
PubMed
高影响因子
JOURNAL OF COLLOID AND INTERFACE SCIENCE
·
2024
·
IF 9.4
Haifei Wang,Guanhua Lin,Yang Lin,Yang Cui,Gang Chen,Zhengchun Peng
Based on real-time detection of plantar pressure, gait recognition could provide important health information for rehabilitation administration, fatigue prevention, and sports training assessment. So far, such researches are extremely limited due to lacking of reliable, stable and comfortable plantar pressure sensors. Herein, a strategy for preparing high compression strength and resilience conductive iongels has been proposed by implanting physically entangled polymer chains with covalently cross-linked networks. The resulting iongels have excellent mechanical properties including nice compliance (young’s modulus < 300 kPa), high compression strength (>10 MPa at a strain of 90 %), and good resilience (self-recovery within seconds). And capacitive pressure sensor composed by them possesses excellent sensitivity, good linear response even under very small stress (∼kPa), and long-term durability (cycles > 100,000) under high-stress conditions (133 kPa). Then, capacitive pressure sensor arrays have been prepared for high-precision detection of plantar pressure spatial distribution, which also exhibit excellent sensing performances and long-term stability. Further, an extremely sensitive and fast response plantar pressure monitoring system has been designed for monitoring plantar pressure of foot at different postures including upright, forward and backward. The system achieves real-time tracking and monitoring of changes of plantar pressure during different static and dynamic posture processes. And the characteristics of plantar pressure information can be digitally and photography displayed. Finally, we propose an intelligent framework for real-time detection of plantar pressure by combining electronic insoles with data analysis system, which presents excellent applications in sport trainings and safety precautions.
研究领域:
生物医学工程
·
材料科学
✓ 已验证
产品关联
DOI
PubMed
高影响因子
Nano Energy
·
2024
·
IF 16.8
Dedong Guo,Yuanlong Li,Qihui Zhou,Zhongxiang Yu,Xueqian Liu,Shuheng Dong,Shipeng Zhang,Ho-Kun Sung,Zhao Yao,Yang Li,Yuanyue Li
Gait recognition and rehabilitation training based on pressure sensing technology have an important role in the field of rehabilitation medicine. However, existing pressure sensors that are used in this process are often fabricated from non-degradable or non-biocompatible source materials, which limits their application in long-term sustainable use. In this study, we propose a high-performance, degradable, biocompatible and flexible capacitive pressure sensor. Its dielectric layer is prepared using a polyvinyl alcohol/sodium alginate (PVA/SA) electrospun nanofiber membrane (ENM), while its upper and lower electrodes are fabricated from PVA@graphene screen-printed ENMs. Experimental results demonstrate the sensor's exceptional pressure sensing performance, characterized by its high sensitivity (0.54 kPa −1 at 0–10 kPa), low detection limit (∼2.2 Pa), rapid response time (26.6/29.9 ms), and excellent stability (5000 cycles). Furthermore, it exhibits outstanding biocompatibility, achieving a cell viability assay survival rate exceeding 97%, and remarkable degradability, completely degrading within one hour. A gait recognition and rehabilitation training system has been developed by integrating the sensors with a deep learning algorithm and wireless transmission technology. The system can effectively monitor and record dynamic parameters of lower limb swing during walking, exhibiting an impressive gait recognition accuracy of 98% over five normal and abnormal gaits. Moreover, it can guide patients in performing diverse rehabilitation actions as well as monitor their progress through action count recording. This innovative solution offers a sustainable approach to gait recognition and rehabilitation training within the field of rehabilitation medicine, thereby opening up new avenues for patient recovery.
研究领域:
康复医学
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材料科学
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传感器技术
✓ 已验证
产品关联
DOI
高影响因子
CHEMICAL ENGINEERING JOURNAL
·
2025
·
IF 13.2
Xia Yin,Shunhang Zhang,Yanning Qu,Shijin Zhang,Xinyu Zhang,Jisheng Zhao,Xiaohang Li,HanXiao Zeng,Hang Wang,Hong Liu,Mingwei Tian
Real-time and accurate monitoring of abnormal gait is highly desired in preventive healthcare and medical diagnosis of neurodegenerative disorders. However, the development of wearable monitoring devices that are both comfortable to wear and capable of real-time sensing remains a significant challenge. Herein, a high-resolution gait recognition insole (GRI) composed of the sensitivity-tunable sensing fiber is proposed. The GRI is capable of both static and dynamic plantar pressure mapping with a 144-pixel sensor array pixel. We design a sensitivity-tunable sensing fiber with core-sheath structure through conductive particles concentration gradient directed migration. The sheath layer exhibits a hierarchical architecture with micro-scale pores formed by carbon black concentration gradient directed migration. This fabrication technique strategically enhances sensor sensitivity by magnifying the initial resistance values. Furthermore, the GRI system is designed to integrate with machine learning algorithms, thereby enabling the recognition of abnormal gait patterns associated with neurological disorders. The system can accurately recognize abnormal gait with an accuracy of 98.42%, showing great potential for reliable applications in healthcare monitoring, sports training, and rehabilitation engineering.
研究领域:
生物医学工程
·
预防医学
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神经科学
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产品关联
DOI
高影响因子
SENSORS
·
2019
·Vol. 19
·期 23
·5197
·
IF 3.031
Wenzheng Heng,Gaoyang Pang,Feihong Xu,Xiaoyan Huang,Zhibo Pang,Geng Yang
Gait analysis is an important assessment tool for analyzing vital signals collected from individuals and for providing physical information of the human body, and it is emerging in a diverse range of application scenarios, such as disease diagnosis, fall prevention, rehabilitation, and human–robot interaction. Herein, a kind of surface processed conductive rubber was designed and investigated to develop a pressure-sensitive insole to monitor planar pressure in a real-time manner. Due to a novel surface processing method, the pressure sensor was characterized by stable contact resistance, simple manufacturing, and high mechanical durability. In the experiments, it was demonstrated that the developed pressure sensors were easily assembled with the inkjet-printed electrodes and a flexible substrate as a pressure-sensitive insole while maintaining good sensing performance. Moreover, resistive signals were wirelessly transmitted to computers in real time. By analyzing sampled resistive data combined with the gait information monitored by a visual-based reference system based on machine learning method (k-Nearest Neighbor algorithm), the corresponding relationship between plantar pressure distribution and lower limb joint angles was obtained. Finally, the experimental validation of the ability to accurately divide gait into several phases was conducted, illustrating the potential application of the developed device in healthcare and robotics.Keywords:gait phase;insole sensors;surface processing;inkjet printing;visual-based reference;machine learning
研究领域:
生物医学工程
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电子工程
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人工智能
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产品关联
DOI
PubMed
高影响因子
Advanced Science
·
2024
·Vol. 11
·期 28
·2401436
·
IF 14.3
Yihan Wang,Lang Chu,Si Meng,Mingxuan Yang,Yidan Yu,Xiaokang Deng,Cheng Qi,Tiantian Kong,Zhou Liu
Yarn-woven triboelectric nanogenerators (TENGs) have greatly advanced wearable sensor technology, but their limited sensitivity and stability hinder broad adoption. To address these limitations, Poly(VDF-TrFE) and P(olyadiohexylenediamine (PA66)-based nanofibers coaxial yarns (NCYs) combining coaxial conjugated electrospinning and online conductive adhesive coating are developed. The integration of these NCYs led to enhanced TENGs (NCY-TENGs), notable for their flexibility, stretchability, and improved sensitivity, which is ideal for capturing body motion signals. One significant application of this technology is the fabrication of smart insoles from NCY-TENG plain-woven fabrics. These insoles are highly sensitive and possess antibacterial, breathable, and washable properties, making them ideal for real-time gait monitoring in patients with diabetic foot conditions. The NCY-TENGs and their derivatives show immense potential for a variety of wearable electronic devices, representing a considerable advancement in the field of wearable sensors.
研究领域:
材料科学
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生物医学工程
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电子工程
✓ 已验证
产品关联
DOI
PubMed
高影响因子
Biosensors-Basel
·
2024
·Vol. 14
·期 12
·622
·
IF 4.9
Zhenhe Huang,Qiuqian Ou,Dan Li,Yuanyi Feng,Liangling Cai,Yue Hu,Hongwei Chu
Sarcopenia has been a serious concern in the context of an increasingly aging global population. Existing detection methods for sarcopenia are severely constrained by cumbersome devices, the necessity for specialized personnel, and controlled experimental environments. In this study, we developed an innovative wearable fabric system based on conductive fabric and flexible sensor array. This fabric system demonstrates remarkable pressure-sensing capabilities, with a high sensitivity of 18.8 kPa−1and extraordinary stability. It also exhibits excellent flexibility for wearable applications. By interacting with different parts of the human body, it facilitates the monitoring of various physiological activities, such as pulse dynamics, finger movements, speaking, and ambulation. Moreover, this fabric system can be seamlessly integrated into sole to track critical indicators of sarcopenia patients, such as walking speed and gait. Clinical evaluations have shown that this fabric system can effectively detect variations in indicators relevant to sarcopenia patients, proving that it offers a straightforward and promising approach for the diagnosis and assessment of sarcopenia.
研究领域:
生物医学工程
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老年医学
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传感器技术
✓ 已验证
产品关联
DOI
PubMed
高影响因子
Nano Energy
·
2020
·
IF 16.602
Tao Yang,Hong Pan,Guo Tian,Binbin Zhang,Da Xiong,Yuyu Gao,Cheng Yan,Xiang Chu,Ningjun Chen,Shen Zhong,Lei Zhang,Weili Deng,Weiqing Yang
Piezoelectric-based wearable electronics promise potential applications in human physiological monitoring for disease prediction, diagnose and rehabilitation. Still, it is a big challenge to fulfill excellent compatibility and precisely monitoring of the complexly subtle physiological signals simultaneously. Here, we prepared a three-dimensional hierarchically interlocked PVDF/ZnO nanofiber-based piezoelectric sensor through epitaxial growing ZnO nano rods (NRs) on the surface of electrospun PVDF nanofibers, which enables the fiber-based physiological monitoring electronics (PME) of well flexibility and high gas permeability . Due to synergistic piezoelectric effect of the effectively deformed interlocked ZnO NRs and the uniformly orientated PVDF nanofibers with high electroactive phase, the sensitivities of PME in both pressing and bending modes have been greatly improved 6 times and 41 times than that of pure PVDF nanofibers respectively. On this basis, the designed PME can precisely detect the complexly subtle physiological signals of respiration, wrist pulse and muscle behavior. Moreover, a sensitive gait recognition system was successfully developed based on PME arrays. Therefore, this proposed fiber-based device provides an alternative strategy to monitor the human subtle physiological signals and demonstrates promising potential in the expanded application of healthcare and clinical diagnosis.
研究领域:
材料科学
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生物医学工程
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可穿戴设备
✓ 已验证
产品关联
DOI
高影响因子
CHEMICAL ENGINEERING JOURNAL
·
2024
·
IF 13.3
Zihang Cheng,Yuzhang Wen,Zhenning Xie,Mengqi Zhang,Qingyang Feng,Yunlu Wang,Dongsheng Liu,Yecheng Cao,Yupeng Mao
Supramolecular materials have been considered an innovative material system which provides new perspectives for material innovation in the field of TENG. Here, a supramolecular elastomer (PGE) prepared from polyvinyl alcohol (PVA), glycerin, gelatin and ferric chloride hexahydrate (FeCl 3 ∙6H 2 O) with excellent stretchability and degradability has been reported for human gait and arch health monitoring. The PGE can be used as a strain sensor to monitor the changing angles of multiple joints of the human body (fingers, elbows, knees, ankles) with a response time of 75 ms. Meanwhile, the PGE served as a friction layer can construct a Triboelectric Nanogenerator (PGE-TENG), which is capable of real-time monitoring of different locomotor behaviors and six basic gaits. Combined with machine learning algorithms to develop an intelligent motion monitoring system, it achieves accurate recognition of the health status of human foot arches and walking status of visually impaired people, with recognition accuracies of 97.5 % and 99.6 %. In addition, an intelligent interaction system based on PGE-TENG was developed to provide a new platform for sports enthusiasts working out at home. The multi-sensor coupling technology based on PGE not only realizes high-precision real-time monitoring of human movement, but also opens up new ways in the field of medical and health monitoring, strongly promoting the integration of wearable devices and Internet of Things (IoT) technology.
研究领域:
材料科学
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生物医学工程
·
智能可穿戴设备
✓ 已验证
产品关联
DOI
高影响因子
ADVANCED MATERIALS
·
2022
·Vol. 34
·期 17
·2109126
·
IF 32.086
Neng Xia,Bowen Jin,Dongdong Jin,Zhengxin Yang,Chengfeng Pan,Qianqian Wang,Fengtong Ji,Veronica Iacovacci,Carmel Majidi,Yang Ding,Li Zhang
The efficient motility of invertebrates helps them survive under evolutionary pressures. Reconstructing the locomotion of invertebrates and decoupling the influence of individual basic motion are crucial for understanding their underlying mechanisms, which, however, generally remain a challenge due to the complexity of locomotion gaits. Herein, a magnetic soft robot to reproduce midge larva's key natural swimming gaits is developed, and the coupling effect between body curling and rotation on motility is investigated. Through the authors’ systematically decoupling studies using programmed magnetic field inputs, the soft robot (named LarvaBot) experiences various coupled gaits, including biomimetic side-to-side flexures, and unveils that the optimal rotation amplitude and the synchronization of curling and rotation greatly enhance its motility. The LarvaBot achieves fast locomotion and upstream capability at the moderate Reynolds number regime. The soft robotics-based platform provides new insight to decouple complex biological locomotion, and design programmed swimming gaits for the fast locomotion of soft-bodied swimmers.
研究领域:
生物力学
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机器人学
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生物物理学
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软物质物理
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微流控
✓ 已验证
产品关联
DOI
PubMed
高影响因子
Nanoscale
·
2025
·
IF 5.1
Weili Deng,Tingting Zhou,Wanghong Zeng,Zihan Wang,Yiheng Liu,Boling Lan,Shenglong Wang,Yong Ao,Yue Sun,Shuai Wang,Zhaoyu Li,Long Jin,Weiqing Yang
Wearable piezoelectric sensors have gained significant attention for real-time biomechanical monitoring, yet existing designs often face limitations in sensitivity, durability, and dynamic response. To address these challenges, we develop a wearable sensor utilizing gradient-architected CNT/PMN-PT/PVDF piezoelectric composites for continuous gait monitoring during weight-bearing walking. The sensor features a dual-filler gradient configuration within the poly(vinylidene fluoride) (PVDF) matrix, where strategically distributed carbon nanotubes (CNTs) and lead magnesium niobate-lead titanate (PMN-PT) ceramic particles synergistically enhance electromechanical coupling efficiency. The CNTs-enriched surface layer boosts polarization by facilitating charge injection efficiency, while the gradient-arranged PMN-PT fillers induce stress concentration, further amplifying the piezoelectric output. As a result, the sensor exhibits exceptional performance, with a decent piezoelectric coefficient (d33* = 40 pm/V) and high sensitivity (172 mV/N). Both experimental tests and finite element simulations validate the superior performance of this gradient structure, making it highly effective for real-time kinematic monitoring during weight-bearing walking. This composite-based sensor represents a promising advancement in wearable health technology, with immediate applications in clinical gait analysis, rehabilitation monitoring and sports injury prevention.
研究领域:
材料科学
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生物医学工程
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传感技术
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柔性电子学
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人体运动分析
✓ 已验证
产品关联
DOI
PubMed
高影响因子
ACS Sensors
·
2025
·
IF 9.1
Zongxue Gu,Yingcun Liu,Keshuai Liu,Shichang Yang,Senyuan Ye,Ping Sun,Can Ge,Bin Yu,Hui Sun,Chong Gao,Duo Xu
Incorporating biomass (e.g., bacterial cellulose, BC) pressure-sensing structures into plantar monitoring technologies could effectively defend users against insecure wear and inaccurate detection, while their capability in sensing pressure continuously when subjected to large pressure is hindered by their natural two-dimensional structure. Here, we present a microbial engineering strategy for fabricating hierarchical fully biomass pressure sensors (HFBPSs) with sufficient sensing capabilities and good structural stability for plantar pressure detection. Particularly, the incorporation of the biobased material loofah enables HFBPS to adopt a hierarchical structure from micro- and nanostructured sensing networks, allowing for dynamic changes in the series-parallel configuration of the circuit under large pressure. This innovative structure design breaks the bottleneck of low operating range encountered by traditional rigid two-dimensional BC pressure sensors, ensuring the HFBPS with ultrahigh sensitivity (2.82 kPa–1) and wide detection range (0–600 kPa). In addition to stably monitoring gait motions, the HFBPS integrated into smart insoles can recognize nonstandard Tai Chi movements. Our HFBPS with exceptional pressure-sensing performance provides significant impact on the future development of smart insoles for plantar monitoring.
研究领域:
材料科学
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生物医学工程
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传感器技术
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可穿戴设备
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微生物学
✓ 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）