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学者姓名：夏圣垣
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Abstract ：
Prolonged exposure to damaging auditory conditions can lead to significant health issues, including hearing impairment and inflammation of the ear canal. We present an intelligent multifunction graphene skin patch (GSP) that integrates health monitoring and high-quality acoustic interaction to address these challenges. Comprising laser-induced graphene (LIG), PI fabric, and Nomex fabric, GSP utilizes triboelectric nanogenerator (TENG), thermosensitive (TS), and thermoacoustic (TA) effects to provide multimodal sensing of external auditory canal health while delivering superior audio quality. GSP demonstrates rapid response and high sensitivity (1.286 kPa-1), along with remarkable durability (12,000 cycles) for precise monitoring of pulse and temperature variations (4/ degrees C). By employing pulse density modulation, we significantly reduce total harmonic distortion from 97.6 % to 2.98 %, ensuring exceptional sound fidelity at low frequencies. Moreover, through deep learning analysis, the accuracy of acoustic data processing improved from 47.1 % to 98.2 %. GSP's multifunctionality enables an integrated health monitoring and warning system, enhancing human-machine interaction. This innovative approach not only bridges the gap between monitoring and rehabilitation but also sets a novel standard for wearable health solutions.
Keyword ：
Deep learning Deep learning Health monitoring Health monitoring Human-machine interaction Human-machine interaction Laser-induced graphene Laser-induced graphene Skin patch Skin patch
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| GB/T 7714 | Sun, Hao , Li, Longwei , Tao, Lu-Qi et al. An intelligent multifunction graphene skin patch for ear health monitoring and acoustic interaction [J]. | NANO ENERGY , 2025 , 137 . |
| MLA | Sun, Hao et al. "An intelligent multifunction graphene skin patch for ear health monitoring and acoustic interaction" . | NANO ENERGY 137 (2025) . |
| APA | Sun, Hao , Li, Longwei , Tao, Lu-Qi , Xue, Hongxiang , Pu, Xiong , Xia, Sheng-Yuan et al. An intelligent multifunction graphene skin patch for ear health monitoring and acoustic interaction . | NANO ENERGY , 2025 , 137 . |
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Abstract ：
In the era of information and data, the collaboration between humans and robots is becoming a trend, making the security of human-robot communication particularly critical. Compared with optical and electromagnetic wave encryption, ultrasound can be used as an information encryption medium, which cannot be directly captured by enemy and cannot be shielded by electromagnetic interference. Here, we creatively present machine learningenhanced multifunctional graphene electronic patches (GEPs) for gesture recognition and ultrasound encryption communication. Thanks to the multifunctionality of the graphene, GEPs can serve both as strain sensors and ultrasonic thermoacoustic (TA) sources. With the help of machine learning, encryption gestures are analyzed by convolutional neural network (CNN), and accuracy is as high as 99.3 % and 92.37 % at training set and test set. Ultrasound robots (URs) controlled by GEPs in wireless encryption still maintains stable operation under strong electromagnetic shielding. This work holds significant application potential in the fields of flexible electronics, multifunctional materials, multi-robot collaborative operations, and encrypted communication.
Keyword ：
Gesture recognition Gesture recognition Human-robot interaction Human-robot interaction Information encryption Information encryption Laser-induced graphene Laser-induced graphene Machine learning Machine learning Ultrasound Ultrasound
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| GB/T 7714 | Sun, Hao , Xia, Sheng-Yuan , He, Renzhi et al. Machine learning-enhanced multifunctional graphene electronic patches for gesture recognition and human-robots ultrasound encryption communication [J]. | CHEMICAL ENGINEERING JOURNAL , 2025 , 508 . |
| MLA | Sun, Hao et al. "Machine learning-enhanced multifunctional graphene electronic patches for gesture recognition and human-robots ultrasound encryption communication" . | CHEMICAL ENGINEERING JOURNAL 508 (2025) . |
| APA | Sun, Hao , Xia, Sheng-Yuan , He, Renzhi , Li, Longwei , Xue, Hongxiang , Tao, Lu-Qi et al. Machine learning-enhanced multifunctional graphene electronic patches for gesture recognition and human-robots ultrasound encryption communication . | CHEMICAL ENGINEERING JOURNAL , 2025 , 508 . |
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