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Ecofriendly and high-performance flexible pressure sensor derived from natural plant materials for intelligent audible and silent speech recognition
Nano Energy ( IF 17.6 ) Pub Date : 2024-05-06 , DOI: 10.1016/j.nanoen.2024.109701
Xuqi Zheng , Bingcheng Yi , Qihui Zhou , Ruijie Xu , Xueqian Liu , Ho-Kun Sung , Leonid Chernogor , Minghui Cao , Zhao Yao , Yang Li , Yuanyue Li

Flexible pressure sensors (FPSs) are widely used in human–computer interaction (HCI) and medical diagnoses, but their further development faces several challenges. Integrating artificial intelligence (AI) with FPSs is indispensable for advancing the cognitive capabilities of HCI systems, but the FPS must also be ecofriendly, cost-effective, and high-performance to meet the demands of environmental protection and sustainable development. Here, a biodegradable capacitive FPS is presented that is fabricated from natural plant materials (i.e., cornstarch and lignocellulose) while exhibiting remarkable attributes such as high sensitivity (2.427 kPa at 0–2 kPa), rapid response/recovery time (20/24 ms), extremely low detection limit (∼10 Pa), outstanding stability (> 6000 fatigue tests), excellent biocompatibility (survival rate exceeding 99 % in cell viability assays), and prominent biodegradability (complete degradation within 24 h). Prepared sensors were integrated with optimized AI algorithms, embedded systems, and wireless transmission technologies to develop a dual-functional (i.e., audible and silent) speech recognition system that achieved recognition rates exceeding 95 %. The developed sensor is expected to play a crucial role in future HCI and medical assistance applications.

中文翻译:

源自天然植物材料的环保高性能柔性压力传感器,用于智能有声和无声语音识别

柔性压力传感器(FPS)广泛应用于人机交互(HCI)和医疗诊断中,但其进一步发展面临着一些挑战。人工智能(AI)与FPS的结合对于提升HCI系统的认知能力是不可或缺的,但FPS也必须环保、经济高效且高性能,以满足环境保护和可持续发展的需求。这里提出了一种可生物降解的电容式 FPS,它由天然植物材料(即玉米淀粉和木质纤维素)制成,同时具有高灵敏度(0–2 kPa 时为 2.427 kPa)、快速响应/恢复时间(20/24 ms)等显着属性。 )、极低的检测限(∼10 Pa)、出色的稳定性(> 6000 次疲劳测试)、优异的生物相容性(细胞活力测定中存活率超过 99%)以及突出的生物降解性(24 小时内完全降解)。将准备好的传感器与优化的AI算法、嵌入式系统和无线传输技术集成,开发出双功能(即有声和无声)语音识别系统,识别率超过95%。所开发的传感器预计将在未来的人机交互和医疗援助应用中发挥至关重要的作用。
更新日期:2024-05-06
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