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Substrate-Free Multilayer Graphene Electronic Skin for Intelligent Diagnosis.
Qiao, Yancong; Li, Xiaoshi; Jian, Jinming; Wu, Qi; Wei, Yuhong; Shuai, Hua; Hirtz, Thomas; Zhi, Yao; Deng, Ge; Wang, Yunfan; Gou, Guangyang; Xu, Jiandong; Cui, Tianrui; Tian, He; Yang, Yi; Ren, Tian-Ling.
Affiliation
  • Qiao Y; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Li X; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Jian J; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Wu Q; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Wei Y; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Shuai H; Department of Physics, Engineering Physics, The Ohio State University, 191 West Woodruff Avenue, Columbus, Ohio 43210, United States.
  • Hirtz T; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Zhi Y; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Deng G; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Wang Y; Institute of Electronics, Tsinghua University, Beijing 100084, China.
  • Gou G; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Xu J; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Cui T; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Tian H; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Yang Y; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
  • Ren TL; Institute of Microelectronics and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.
ACS Appl Mater Interfaces ; 12(44): 49945-49956, 2020 Nov 04.
Article in En | MEDLINE | ID: mdl-33090758
ABSTRACT
Current wearable sensors are fabricated with substrates, which limits the comfort, flexibility, stretchability, and induces interface mismatch. In addition, the substrate prevents the evaporation of sweat and is harmful to skin health. In this work, we have enabled the substrate-free laser scribed graphene (SFG) electronic skin (e-skin) with multifunctions. Compared with the e-skin with the substrate, the SFG has good gas permeability, low impedance, and flexibility. Only assisted using water, the SFG can be transferred to almost any objects including silicon and human skin and it can even be suspended. Many through-holes like stomas in leaf can be formed in the SFG, which make it breathable. After designing the pattern, the gauge factor (GF) of graphene electronic skin (GES) can be designed as the strain sensor. Physiological signals such as respiration, human motion, and electrocardiogram (ECG) can be detected. Moreover, the suspended SFG detect vibrations with high sensitivity. Due to the substrate-free structure, the impedance between SFG e-skin and the human body decreases greatly. Finally, an ECG detecting system has been designed based on the GES, which can monitor the body condition in real time. To analyze the ECG signals automatically, a convolutional neural network (CNN) was built and trained successfully. This work has high potential in the field of health telemonitoring.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Wearable Electronic Devices / Graphite Type of study: Diagnostic_studies Limits: Humans Language: En Journal: ACS Appl Mater Interfaces Journal subject: BIOTECNOLOGIA / ENGENHARIA BIOMEDICA Year: 2020 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Wearable Electronic Devices / Graphite Type of study: Diagnostic_studies Limits: Humans Language: En Journal: ACS Appl Mater Interfaces Journal subject: BIOTECNOLOGIA / ENGENHARIA BIOMEDICA Year: 2020 Document type: Article Affiliation country: