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

Engineering and Technology

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

T. Kim, Y. Shin, et al.

Explore a groundbreaking silent speech interface that utilizes advanced crystalline-silicon-based strain sensors, achieving impressive classification accuracy of 87.53%. This innovative research conducted by a team of experts at Yonsei University promises to revolutionize how we interact silently through technology.

00:00
00:00
Playback language: English
Abstract
This paper introduces a novel silent speech interface (SSI) using crystalline-silicon-based strain sensors and a 3D convolutional deep learning algorithm. Minimized strain gauges (<0.1 mm²) effectively capture biaxial strain information. Four sensors near the mouth classified 100 words with 87.53% accuracy, outperforming an sEMG-based SSI (42.60%) with similar sensor dimensions. The system's reliability was verified through various analyses.
Publisher
Nature Communications
Published On
Oct 03, 2022
Authors
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
Tags
silent speech interface
strain sensors
deep learning
classification accuracy
biometrics

Related Publications

Explore these studies to deepen your understanding of the subject.

Ultrasensitive textile strain sensors redefine wearable silent speech interfaces with high machine learning efficiency
Engineering and Technology

Ultrasensitive textile strain sensors redefine wearable silent speech interfaces with high machine learning efficiency

C. Tang, M. Xu, et al.

Deep-learning-based image segmentation integrated with optical microscopy for automatically searching for two-dimensional materials
Engineering and Technology

Deep-learning-based image segmentation integrated with optical microscopy for automatically searching for two-dimensional materials

S. Masubuchi, E. Watanabe, et al.

Development and evaluation of deep learning algorithms for assessment of acute burns and the need for surgery
Medicine and Health

Development and evaluation of deep learning algorithms for assessment of acute burns and the need for surgery

C. Boissin, L. Laflamme, et al.

Biodegradable, flexible silicon nanomembrane-based NOx gas sensor system with record-high performance for transient environmental monitors and medical implants
Engineering and Technology

Biodegradable, flexible silicon nanomembrane-based NOx gas sensor system with record-high performance for transient environmental monitors and medical implants

G. Ko, S. D. Han, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny