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Deep Learning Assisted Body Area Triboelectric Hydrogel Sensor Network for Infant Care (Adv. Funct. Mater. 35/2022)
Author(s) -
Guo Rui,
Fang Yunsheng,
Wang Zhaosu,
Libanori Alberto,
Xiao Xiao,
Wan Dong,
Cui Xiaojing,
Sang Shengbo,
Zhang Wendong,
Zhang Hulin,
Chen Jun
Publication year - 2022
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.202270199
Subject(s) - triboelectric effect , materials science , mobile phone , smart phone , wireless sensor network , construct (python library) , motion sensors , internet of things , nanotechnology , artificial intelligence , computer science , biomedical engineering , embedded system , telecommunications , medicine , computer network , composite material
Triboelectric Hydrogel Sensor Networks In article number 2204803, Hulin Zhang, Jun Chen, and co‐workers construct a body area sensor network based on edible triboelectric hydrogel sensors, which can realize the recognition of multiple motion patterns of infants with the assistance of deep learning algorithms. Moreover, an application is also developed to wirelessly transmit the motion signals to a mobile phone, providing a promising paradigm for infant care.