Graphene-Clad nanotextile sensors for biosignal acquisition

  • Tamador Mohmed Elnour Elboshra Elkhidir

Student thesis: Master's Thesis


Electrocardiography is a well-established medical test to monitor the electrical activity of the heart and gain useful information on the heart condition. Conventionally, the electrocardiogram (ECG) is acquired using electrodes placed on the skin, usually around the chest and limbs. Conventional ECG electrodes (Ag/AgCl) are supported by adhesive backing and gel to improve contact with the skin. During measurements with Ag/AgCl electrodes, the gel dries with time causing decline of conductivity and performance. Therefore, textile-based dry electrodes are emerging as alternative candidates as their electrical properties remain fairly stable over time. Textile electrodes are dry, free from gel, and can be readily converted into wearable medical garments, which makes them preferable for long term implementations. Graphene has excellent electrical and thermal conductivity, displays high stiffness while being elastic which make it a favorable material for exible electronics and wearable sensors. To harness the unique properties of graphene and the advantages of textile-based materials in biosensing, we show the merger of the two through a simple and scalable fabrication process whereby conductive textiles are formed using graphene as a cladding layer. Based on this technique, we report for the first time the development of graphene-clad textile electrodes for use in electrocardiography. We compare the performance of the new textile electrodes against conventional Ag/AgCl pre-gelled electrodes and demonstrate their robustness in ECG measurements. Excellent conformity was achieved between the signals measured with the new graphene-clad textile electrodes and conventional electrodes. In addition, graphene-textile electrode was integrated with wrist supports to create a wearable prototype that continuously monitors and transmits ECG signals through customized circuit along with Blutooth module. However, the ECG signal extracted from textile electrode is more susceptible to motion artifacts in comparison to conventional electrodes. We have developed a simple method for adaptive out-filtering the motion artifact from electrocardiogram (ECG) obtained by using conductive textile electrodes. The reference signal for adaptive filtering was obtained by placing additional electrodes at one hand to capture the motion of the hand. The adaptive filtering was compared to independent component analysis (ICA) algorithm. The signal to noise ratio (SNR) for the adaptive filtering was higher than independent component analysis in most cases.
Date of Award2015
Original languageAmerican English
SupervisorMurat Yapici (Supervisor)


  • ECG
  • Graphene-clad
  • textile
  • Adaptive filtering
  • Wristbands.

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