Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces

A wearable silent speech interface (SSI) is a promising platform that enables verbal communication without vocalization. The most widely studied methodology for SSI focuses on surface electromyography (sEMG). However, sEMG suffers from low scalability because of signal quality-related issues, includ...

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Vydané v:	Nature communications Ročník 13; číslo 1; s. 5815 - 12
Hlavní autori:	Kim, Taemin, Shin, Yejee, Kang, Kyowon, Kim, Kiho, Kim, Gwanho, Byeon, Yunsu, Kim, Hwayeon, Gao, Yuyan, Lee, Jeong Ryong, Son, Geonhui, Kim, Taeseong, Jun, Yohan, Kim, Jihyun, Lee, Jinyoung, Um, Seyun, Kwon, Yoohwan, Son, Byung Gwan, Cho, Myeongki, Sang, Mingyu, Shin, Jongwoon, Kim, Kyubeen, Suh, Jungmin, Choi, Heekyeong, Hong, Seokjun, Cheng, Huanyu, Kang, Hong-Goo, Hwang, Dosik, Yu, Ki Jun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 03.10.2022 Nature Publishing Group Nature Portfolio
Predmet:	142/126 639/166/985 639/166/987 639/925/350/59 639/925/927/59 Accuracy Algorithms Classification Crystal structure Crystallinity Deep learning Electromyography Gauges Humanities and Social Sciences Interfaces Machine learning multidisciplinary Reliability analysis Science Science (multidisciplinary) Sensors Signal quality Signal to noise ratio Silicon Speech Strain gauges Verbal communication Vocalization behavior Words (language)
ISSN:	2041-1723, 2041-1723
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