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Surface Electromyography With Wearable Graphene Textiles

Özberk Öztürk, Murat Kaya Yapici

2021IEEE Sensors Journal22 citationsDOI

Abstract

In this study, we report the use of graphene-coated fabrics as textile electrodes in surface electromyography (sEMG) acquisition. Their performance was compared with that of wet silver/silver chloride (Ag/AgCl) electrodes for the signals that were taken from three different muscle groups. Comparisons were performed in terms of the skin-electrode impedance (SEI), signal-to-noise ratio (SNR) and cross correlation. SEI values of graphene textile electrodes ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 90\text{k}\Omega $ </tex-math></inline-formula> ) were found to be well within the range of commercial Ag/AgCl electrodes ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 50\text{k}\Omega $ </tex-math></inline-formula> ). At 2 kg load, SNR values of 19.23 dB from triceps brachii, 27.18 dB from biceps brachii, and 28.13 dB from quadriceps femoris muscles were obtained, respectively; which showed that performance of graphene textile electrodes in static settings is at minimum 94% of clinical signal quality both in terms of SNR and similarity of signal morphologies in terms of cross correlation. After benchmarking the electrode performance, a proof of concept fully textile elastic band and a mobile acquisition circuit were combined to further validate the feasibility of surface electromyography with wearable graphene textiles through a step counter application, where the implemented wearable graphene textile-based step counter achieved on average a success rate above 90% for varying speed levels and up to a maximum of ~98%. Results suggests that graphene textiles could be a viable alternative to gelled Ag/AgCl electrodes and can be used to develop wearable, smart garment applications.

Topics & Concepts

GrapheneWearable computerElectrodeElectromyographySIGNAL (programming language)TextileBicepsNoise (video)Materials scienceComputer scienceComposite materialArtificial intelligenceNanotechnologyPhysicsSurgeryEmbedded systemQuantum mechanicsPsychologyMedicinePsychiatryProgramming languageImage (mathematics)Advanced Sensor and Energy Harvesting MaterialsMuscle activation and electromyography studiesConducting polymers and applications
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