Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition
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| Publicado en: | Biosensors vol. 15, no. 6 (2025), p. 339 |
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| Autor principal: | |
| Otros Autores: | , |
| Publicado: |
MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2079-6374 | ||
| 024 | 7 | |a 10.3390/bios15060339 |2 doi | |
| 035 | |a 3223880359 | ||
| 045 | 2 | |b d20250601 |b d20250630 | |
| 084 | |a 231435 |2 nlm | ||
| 100 | 1 | |a Fan Fengya |u School of Computer Science and Technology, University of Science and Technology of China, No. 96, Jinzhai Road Baohe District, Hefei 230026, China; fanfengya@mail.ustc.edu.cn (F.F.); sa20011167@mail.ustc.edu.cn (M.D.) | |
| 245 | 1 | |a Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Soft sensors are designed to be flexible, making them ideal for wearable devices as they can conform to the human body during motion, capturing pertinent information effectively. However, once these wearable sensors are constructed, modifying them is not straightforward without undergoing a re-prototyping process. In this study, we introduced a novel design for a modular soft sensor unit (M2SU) that incorporates a short, wire-shaped sensory structure made of eutectogel, with magnetic blocks at both ends. This design facilitates the easy assembly and reversible integration of the sensor directly onto a wearable device in situ. Leveraging the piezoresistive properties of eutectogel and the dual conductive and magnetic characteristics of neodymium magnets, our sensor unit acts as both a sensing element and a modular component. To explore the practical application of M2SUs in wearable sensing, we equipped a glove with 8 M2SUs. We evaluated its performance across three common gesture recognition tasks: numeric keypad typing (Task 1), symbol drawing (Task 2), and uppercase letter writing (Task 3). Employing a 1D convolutional neural network to analyze the collected data, we achieved task-specific accuracies of 80.43% (Top 3: 97.68%) for Task 1, 88.58% (Top 3: 96.13%) for Task 2, and 79.87% (Top 3: 91.59%) for Task 3. These results confirm that our modular soft sensor design can facilitate high-accuracy gesture recognition on wearable devices through straightforward, in situ assembly. | |
| 653 | |a Neodymium | ||
| 653 | |a Silicones | ||
| 653 | |a Sensors | ||
| 653 | |a Magnetic properties | ||
| 653 | |a Modular equipment | ||
| 653 | |a Artificial neural networks | ||
| 653 | |a Prototyping | ||
| 653 | |a Electrocardiography | ||
| 653 | |a Gesture recognition | ||
| 653 | |a Wearable technology | ||
| 653 | |a Human motion | ||
| 653 | |a Wearable computers | ||
| 653 | |a Design | ||
| 653 | |a Skin | ||
| 653 | |a Modular units | ||
| 653 | |a Modular structures | ||
| 653 | |a Deformation | ||
| 653 | |a Permanent magnets | ||
| 653 | |a Hydrogels | ||
| 653 | |a Neural networks | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Deng Mo |u School of Computer Science and Technology, University of Science and Technology of China, No. 96, Jinzhai Road Baohe District, Hefei 230026, China; fanfengya@mail.ustc.edu.cn (F.F.); sa20011167@mail.ustc.edu.cn (M.D.) | |
| 700 | 1 | |a Wei, Xi |u Department of Biomedical Engineering, School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, No. 193, Tunxi Road, Hefei 230009, China | |
| 773 | 0 | |t Biosensors |g vol. 15, no. 6 (2025), p. 339 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3223880359/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3223880359/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3223880359/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |