Characterization of textile-insulated capacitive biosensors

Charn Loong Ng, Md. Mamun Ibne Reaz

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Capacitive biosensors are an emerging technology revolutionizing wearable sensing systems and personal healthcare devices. They are capable of continuously measuring bioelectrical signals from the human body while utilizing textiles as an insulator. Different textile types have their own unique properties that alter skin-electrode capacitance and the performance of capacitive biosensors. This paper aims to identify the best textile insulator to be used with capacitive biosensors by analysing the characteristics of 6 types of common textile materials (cotton, linen, rayon, nylon, polyester, and PVC-textile) while evaluating their impact on the performance of a capacitive biosensor. A textile-insulated capacitive (TEX-C) biosensor was developed and validated on 3 subjects. Experimental results revealed that higher skin-electrode capacitance of a TEX-C biosensor yields a lower noise floor and better signal quality. Natural fabric such as cotton and linen were the two best insulating materials to integrate with a capacitive biosensor. They yielded the lowest noise floor of 2 mV and achieved consistent electromyography (EMG) signals measurements throughout the performance test.

Original languageEnglish
Article number574
JournalSensors (Switzerland)
Volume17
Issue number3
DOIs
Publication statusPublished - 12 Mar 2017

Fingerprint

Textiles
textiles
Biosensing Techniques
bioinstrumentation
Biosensors
linen
Bedding and Linens
Linen
cotton
low noise
Cotton
Skin
Electrodes
Capacitance
rayon
capacitance
electromyography
insulators
signal measurement
Electromyography

Keywords

  • Biosensor
  • Capacitive
  • Electromyography
  • Textile

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Electrical and Electronic Engineering

Cite this

Characterization of textile-insulated capacitive biosensors. / Ng, Charn Loong; Ibne Reaz, Md. Mamun.

In: Sensors (Switzerland), Vol. 17, No. 3, 574, 12.03.2017.

Research output: Contribution to journalArticle

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