Document Type
Article
Publication Date
10-2019
Publication Title
Information
Volume
10
Issue
10
Pages
325 (14 pg.)
DOI
10.3390/info10100325
Abstract
Flexible paper-based physiological sensor electrodes were developed using chemically-modified graphene (CG) and carboxylic-functionalized multiwalled carbon nanotube composites (f@MWCNTs). A solvothermal process with additional treatment was conducted to synthesize CG and f@MWCNTs to make CG-f@MWCNT composites. The composite was sonicated in an appropriate solvent to make a uniform suspension, and then it was drop cast on a nylon membrane in a vacuum filter. A number of batches (0%~35% f@MWCNTs) were prepared to investigate the performance of the physical characteristics. The 25% f@MWCNT-loaded composite showed the best adhesion on the paper substrate. The surface topography and chemical bonding of the proposed CG-f@MWCNT electrodes were characterized by scanning electron microscopy (SEM) and Raman spectroscopy, respectively. The average sheet resistance of the 25% CG-f@MWCNT electrode was determined to be 75 Ω/⬜ , and it showed a skin contact impedance of 45.12 kΩ at 100 Hz. Electrocardiogram (ECG) signals were recorded from the chest and fingertips of healthy adults using the proposed electrodes. The CG-f@MWCNT electrodes demonstrated comfortability and a high sensitivity for electrocardiogram signal detection.
Original Publication Citation
Hossain, M. F., Heo, J. S., Nelson, J., & Kim, I. (2019). Paper-based flexible electrode using chemically-modified graphene and functionalized multiwalled carbon nanotube composites for electrophysiological signal sensing. Information, 10(10), 325. doi:10.3390/info10100325
Repository Citation
Hossain, Md Faruk; Heo, Jae Sang; Nelson, John; and KIm, Insoo, "Paper-Based Flexible Electrode Using Chemically-Modified Graphene and Functionalized Multiwalled Carbon Nanotube Composites for Electrophysiological Signal Sensing" (2019). Bioelectrics Publications. 276.
https://digitalcommons.odu.edu/bioelectrics_pubs/276
Included in
Biomedical Devices and Instrumentation Commons, Computer Sciences Commons, Signal Processing Commons
Comments
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.