Hoarseness and dysphonia caused by vocal cord conditions or laryngeal surgeries significantly hinder communication and quality of life. This study presents a plug-and-play humidity-sensing respiratory microphone (HSRM) with generalized features for individual users. Leveraging gold nanoparticle-based humidity sensors integrated into commercially available wearable face masks, the system enables patients to produce verbal communication without relying on vocal cord activity. By integrating nanoparticle-enhanced humidity sensors with advanced convolutional neural networks, the HSRM system accurately decodes respiratory patterns into intelligible speech, achieving a recognition accuracy of 85.61%. Leveraging nanoparticle-polymer interfaces that effectively convert atmospheric humidity fluctuations into precise electrical signals, the system pioneers a contactless and non-invasive paradigm in assistive speech technology. This innovation addresses limitations of existing devices, such as reliance on residual vocal fold vibrations or skin-contact sensors, offering a practical generalized solution for individuals with aphonia. With its potential to facilitate naturalistic communication and transform healthcare applications, the HSRM system sets a new benchmark in wearable assistive technologies for voice rehabilitation and human-machine interaction.
A Wearable AI-Driven Mask with Humidity-Sensing Respiratory Microphone for Non-Vocal Communication.
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作者:Wang Jianfei, Zhang Hongyu, Wu Xiaomin, Gao Mingyan, Wen He, Zhang Zhibo, Makasheva Kremena, Li Wen Jung, Wang Zuobin
| 期刊: | Advanced Science | 影响因子: | 14.100 |
| 时间: | 2025 | 起止号: | 2025 Sep;12(33):e04343 |
| doi: | 10.1002/advs.202504343 | ||
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