Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces
Designing an efficient platform that enables verbal communication without vocalization remains a challenge. Here, the authors propose a silent speech interface by utilizing a deep learning algorithm combined with strain sensors attached near the subject’s mouth, able to collect 100 words and classif...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-10-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-33457-9 |
| _version_ | 1811194908346679296 |
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| author | Taemin Kim Yejee Shin Kyowon Kang Kiho Kim Gwanho Kim Yunsu Byeon Hwayeon Kim Yuyan Gao Jeong Ryong Lee Geonhui Son Taeseong Kim Yohan Jun Jihyun Kim Jinyoung Lee Seyun Um Yoohwan Kwon Byung Gwan Son Myeongki Cho Mingyu Sang Jongwoon Shin Kyubeen Kim Jungmin Suh Heekyeong Choi Seokjun Hong Huanyu Cheng Hong-Goo Kang Dosik Hwang Ki Jun Yu |
| author_facet | Taemin Kim Yejee Shin Kyowon Kang Kiho Kim Gwanho Kim Yunsu Byeon Hwayeon Kim Yuyan Gao Jeong Ryong Lee Geonhui Son Taeseong Kim Yohan Jun Jihyun Kim Jinyoung Lee Seyun Um Yoohwan Kwon Byung Gwan Son Myeongki Cho Mingyu Sang Jongwoon Shin Kyubeen Kim Jungmin Suh Heekyeong Choi Seokjun Hong Huanyu Cheng Hong-Goo Kang Dosik Hwang Ki Jun Yu |
| author_sort | Taemin Kim |
| collection | DOAJ |
| description | Designing an efficient platform that enables verbal communication without vocalization remains a challenge. Here, the authors propose a silent speech interface by utilizing a deep learning algorithm combined with strain sensors attached near the subject’s mouth, able to collect 100 words and classify at a high accuracy rate. |
| first_indexed | 2024-04-12T00:34:00Z |
| format | Article |
| id | doaj.art-5d52d8b8075546b3bd48ee76f1eb8f92 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-12T00:34:00Z |
| publishDate | 2022-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-5d52d8b8075546b3bd48ee76f1eb8f922022-12-22T03:55:12ZengNature PortfolioNature Communications2041-17232022-10-0113111210.1038/s41467-022-33457-9Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfacesTaemin Kim0Yejee Shin1Kyowon Kang2Kiho Kim3Gwanho Kim4Yunsu Byeon5Hwayeon Kim6Yuyan Gao7Jeong Ryong Lee8Geonhui Son9Taeseong Kim10Yohan Jun11Jihyun Kim12Jinyoung Lee13Seyun Um14Yoohwan Kwon15Byung Gwan Son16Myeongki Cho17Mingyu Sang18Jongwoon Shin19Kyubeen Kim20Jungmin Suh21Heekyeong Choi22Seokjun Hong23Huanyu Cheng24Hong-Goo Kang25Dosik Hwang26Ki Jun Yu27Functional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityMedical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityMedical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDigital Signal Processing & Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDepartment of Engineering Science and Mechanics, The Pennsylvania State UniversityMedical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityMedical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityMedical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityMedical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDigital Signal Processing & Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDigital Signal Processing & Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDigital Signal Processing & Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDigital Signal Processing & Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDigital Signal Processing & Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDepartment of Engineering Science and Mechanics, The Pennsylvania State UniversityDigital Signal Processing & Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityMedical Artificial Intelligence Lab, School of Electrical and Electronic Engineering, Yonsei UniversityFunctional Bio-integrated Electronics and Energy Management Lab, School of Electrical and Electronic Engineering, Yonsei UniversityDesigning an efficient platform that enables verbal communication without vocalization remains a challenge. Here, the authors propose a silent speech interface by utilizing a deep learning algorithm combined with strain sensors attached near the subject’s mouth, able to collect 100 words and classify at a high accuracy rate.https://doi.org/10.1038/s41467-022-33457-9 |
| spellingShingle | Taemin Kim Yejee Shin Kyowon Kang Kiho Kim Gwanho Kim Yunsu Byeon Hwayeon Kim Yuyan Gao Jeong Ryong Lee Geonhui Son Taeseong Kim Yohan Jun Jihyun Kim Jinyoung Lee Seyun Um Yoohwan Kwon Byung Gwan Son Myeongki Cho Mingyu Sang Jongwoon Shin Kyubeen Kim Jungmin Suh Heekyeong Choi Seokjun Hong Huanyu Cheng Hong-Goo Kang Dosik Hwang Ki Jun Yu Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces Nature Communications |
| title | Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces |
| title_full | Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces |
| title_fullStr | Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces |
| title_full_unstemmed | Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces |
| title_short | Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces |
| title_sort | ultrathin crystalline silicon based strain gauges with deep learning algorithms for silent speech interfaces |
| url | https://doi.org/10.1038/s41467-022-33457-9 |
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