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Article: A fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation

TitleA fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation
Authors
Issue Date27-Nov-2023
PublisherNature Research
Citation
Nature Communications, 2023, v. 14, n. 1 How to Cite?
Abstract

Post-surgical treatments of the human throat often require continuous monitoring of diverse vital and muscle activities. However, wireless, continuous monitoring and analysis of these activities directly from the throat skin have not been developed. Here, we report the design and validation of a fully integrated standalone stretchable device platform that provides wireless measurements and machine learning-based analysis of diverse vibrations and muscle electrical activities from the throat. We demonstrate that the modified composite hydrogel with low contact impedance and reduced adhesion provides high-quality long-term monitoring of local muscle electrical signals. We show that the integrated triaxial broad-band accelerometer also measures large body movements and subtle physiological activities/vibrations. We find that the combined data processed by a 2D-like sequential feature extractor with fully connected neurons facilitates the classification of various motion/speech features at a high accuracy of over 90%, which adapts to the data with noise from motion artifacts or the data from new human subjects. The resulting standalone stretchable device with wireless monitoring and machine learning-based processing capabilities paves the way to design and apply wearable skin-interfaced systems for the remote monitoring and treatment evaluation of various diseases.


Persistent Identifierhttp://hdl.handle.net/10722/339646
ISSN
2023 Impact Factor: 14.7
2023 SCImago Journal Rankings: 4.887

 

DC FieldValueLanguage
dc.contributor.authorXu, Hongcheng-
dc.contributor.authorZheng, Weihao-
dc.contributor.authorZhang, Yang-
dc.contributor.authorZhao, Daqing-
dc.contributor.authorWang, Lu-
dc.contributor.authorZhao, Yunlong-
dc.contributor.authorWang, Weidong-
dc.contributor.authorYuan, Yangbo-
dc.contributor.authorZhang, Ji-
dc.contributor.authorHuo, Zimin-
dc.contributor.authorWang, Yuejiao-
dc.contributor.authorZhao, Ningjuan-
dc.contributor.authorQin, Yuxin-
dc.contributor.authorLiu, Ke-
dc.contributor.authorXi, Ruida-
dc.contributor.authorChen, Gang-
dc.contributor.authorZhang, Haiyan-
dc.contributor.authorTang, Chu-
dc.contributor.authorYan, Junyu-
dc.contributor.authorGe, Qi-
dc.contributor.authorCheng, Huanyu-
dc.contributor.authorLu, Yang-
dc.contributor.authorGao, Libo -
dc.date.accessioned2024-03-11T10:38:14Z-
dc.date.available2024-03-11T10:38:14Z-
dc.date.issued2023-11-27-
dc.identifier.citationNature Communications, 2023, v. 14, n. 1-
dc.identifier.issn2041-1723-
dc.identifier.urihttp://hdl.handle.net/10722/339646-
dc.description.abstract<p>Post-surgical treatments of the human throat often require continuous monitoring of diverse vital and muscle activities. However, wireless, continuous monitoring and analysis of these activities directly from the throat skin have not been developed. Here, we report the design and validation of a fully integrated standalone stretchable device platform that provides wireless measurements and machine learning-based analysis of diverse vibrations and muscle electrical activities from the throat. We demonstrate that the modified composite hydrogel with low contact impedance and reduced adhesion provides high-quality long-term monitoring of local muscle electrical signals. We show that the integrated triaxial broad-band accelerometer also measures large body movements and subtle physiological activities/vibrations. We find that the combined data processed by a 2D-like sequential feature extractor with fully connected neurons facilitates the classification of various motion/speech features at a high accuracy of over 90%, which adapts to the data with noise from motion artifacts or the data from new human subjects. The resulting standalone stretchable device with wireless monitoring and machine learning-based processing capabilities paves the way to design and apply wearable skin-interfaced systems for the remote monitoring and treatment evaluation of various diseases.<br></p>-
dc.languageeng-
dc.publisherNature Research-
dc.relation.ispartofNature Communications-
dc.titleA fully integrated, standalone stretchable device platform with in-sensor adaptive machine learning for rehabilitation-
dc.typeArticle-
dc.identifier.doi10.1038/s41467-023-43664-7-
dc.identifier.scopuseid_2-s2.0-85177879633-
dc.identifier.volume14-
dc.identifier.issue1-
dc.identifier.eissn2041-1723-
dc.identifier.issnl2041-1723-

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