Printed, Wireless, Soft Bioelectronics and Deep Learning Algorithm for Smart Human-Machine Interfaces

Recent advances in flexible materials and wearable electronics offer a noninvasive, high-fidelity recording of biopotentials for portable healthcare, disease diagnosis, and machine interfaces. Current device-manufacturing methods, however, still heavily rely on the conventional cleanroom microfabric...

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Veröffentlicht in:	ACS applied materials & interfaces Jg. 12; H. 44; S. 49398
Hauptverfasser:	Kwon, Young-Tae, Kim, Hojoong, Mahmood, Musa, Kim, Yun-Soung, Demolder, Carl, Yeo, Woon-Hong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 04.11.2020
Schlagworte:	Algorithms Deep Learning Electronics Humans Nanotechnology Particle Size Surface Properties Wearable Electronic Devices deep learning algorithm additive nanomanufacturing printed bioelectronics electromyograms (EMGs) human−machine interface
ISSN:	1944-8252, 1944-8252
Online-Zugang:	Weitere Angaben
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