Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition
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-proto...
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MDPI AG
2025-05-01
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| Series: | Biosensors |
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| Online Access: | https://www.mdpi.com/2079-6374/15/6/339 |
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| author | Fengya Fan Mo Deng Xi Wei |
| author_facet | Fengya Fan Mo Deng Xi Wei |
| author_sort | Fengya Fan |
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| description | 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. |
| format | Article |
| id | doaj-art-acfac1fbb9954a0e8a651b68cbfb7885 |
| institution | Kabale University |
| issn | 2079-6374 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biosensors |
| spelling | doaj-art-acfac1fbb9954a0e8a651b68cbfb78852025-08-20T03:26:51ZengMDPI AGBiosensors2079-63742025-05-0115633910.3390/bios15060339Modular Soft Sensor Made of Eutectogel and Its Application in Gesture RecognitionFengya Fan0Mo Deng1Xi Wei2School of Computer Science and Technology, University of Science and Technology of China, No. 96, Jinzhai Road Baohe District, Hefei 230026, ChinaSchool of Computer Science and Technology, University of Science and Technology of China, No. 96, Jinzhai Road Baohe District, Hefei 230026, ChinaDepartment of Biomedical Engineering, School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, No. 193, Tunxi Road, Hefei 230009, ChinaSoft 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.https://www.mdpi.com/2079-6374/15/6/339gel sensorstretchable sensorgesture recognitionsoft wearable devicemodular design |
| spellingShingle | Fengya Fan Mo Deng Xi Wei Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition Biosensors gel sensor stretchable sensor gesture recognition soft wearable device modular design |
| title | Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition |
| title_full | Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition |
| title_fullStr | Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition |
| title_full_unstemmed | Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition |
| title_short | Modular Soft Sensor Made of Eutectogel and Its Application in Gesture Recognition |
| title_sort | modular soft sensor made of eutectogel and its application in gesture recognition |
| topic | gel sensor stretchable sensor gesture recognition soft wearable device modular design |
| url | https://www.mdpi.com/2079-6374/15/6/339 |
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