Intelligent Sensing: The Emerging Integration of Machine Learning and Soft Sensors Based on Hydrogels and Ionogels
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| Publicado en: | Advanced Science vol. 12, no. 48 (Dec 1, 2025) |
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| Autor principal: | |
| Otros Autores: | , , , , , , , |
| Publicado: |
John Wiley & Sons, Inc.
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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|---|---|---|---|
| 001 | 3288126191 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2198-3844 | ||
| 024 | 7 | |a 10.1002/advs.202517851 |2 doi | |
| 035 | |a 3288126191 | ||
| 045 | 0 | |b d20251201 | |
| 100 | 1 | |a He, Wenqing |u College of Materials and Energy, Guang'an Institute of Technology, Guang'an, P. R. China | |
| 245 | 1 | |a Intelligent Sensing: The Emerging Integration of Machine Learning and Soft Sensors Based on Hydrogels and Ionogels | |
| 260 | |b John Wiley & Sons, Inc. |c Dec 1, 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Intelligent sensing means the capability of systems to perceive, learn, analyze, and predict based on external stimuli, mimicking the cognitive functions of the human brain. With the assistance of machine learning algorithms for data processing, soft sensors made from hydrogels and ionogels possess intelligent sensing abilities. Here, the recent advances of hydrogel‐ and ionogel‐based soft sensors are comprehensively investigated and summarized, with a specific focus on machine learning‐implemented applications, including handwriting/gesture/object/motion/speech recognition, health monitoring, food detection, and beyond. With current limitations and future perspectives discussed, the fusion of the two is envisioned that can accelerate the development of intelligent sensing in the areas of human‐machine interface (HMI), health care, and soft robotics. | |
| 653 | |a Biocompatibility | ||
| 653 | |a Mechanical properties | ||
| 653 | |a Machine learning | ||
| 653 | |a Text categorization | ||
| 653 | |a Accuracy | ||
| 653 | |a Deep learning | ||
| 653 | |a Datasets | ||
| 653 | |a Regression analysis | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Signal processing | ||
| 653 | |a Sensors | ||
| 653 | |a Neural networks | ||
| 653 | |a Support vector machines | ||
| 653 | |a Data processing | ||
| 653 | |a Feature selection | ||
| 653 | |a Natural language processing | ||
| 653 | |a Algorithms | ||
| 653 | |a Clustering | ||
| 653 | |a Decision trees | ||
| 653 | |a Human-computer interaction | ||
| 653 | |a Hydrogels | ||
| 653 | |a Composite materials | ||
| 700 | 1 | |a Lin, Rumin |u Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, P. R. China | |
| 700 | 1 | |a Kong, Suixiu |u Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen University, Shenzhen, P. R. China | |
| 700 | 1 | |a Qiang, Mengyi |u Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, P. R. China | |
| 700 | 1 | |a Huang, Lingqi |u School of Environmental and Natural Resources, Zhejiang University of Science and Technology, Hangzhou, P. R. China | |
| 700 | 1 | |a Dai, Bing |u College of Intelligent Textile and Fabric Electronics, Zhongyuan University of Technology, Zhengzhou, P. R. China | |
| 700 | 1 | |a Yao, Xi |u Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, P. R. China | |
| 700 | 1 | |a Su, Lei |u School of Biomedical Engineering, Marshall Laboratory of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, P. R. China | |
| 700 | 1 | |a Zhang, Xueji |u School of Biomedical Engineering, Marshall Laboratory of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, P. R. China | |
| 773 | 0 | |t Advanced Science |g vol. 12, no. 48 (Dec 1, 2025) | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3288126191/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3288126191/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3288126191/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |