Wearable surface electromyography (sEMG) technologies with graphene textile electrodes

Official URL: https://risc01.sabanciuniv.edu/record=b2486474_(Table of contents)

Ability to acquire, record, and process muscular biopotentials with wearable health trackers, diagnostic and/or assistive devices through the integration of soft, gel-free surface electrodes will enable seamless monitoring of muscle status in dynamic settings and can facilitate various applications. To this end, one of the fundamental limitations against the development of such systems is due to the drawbacks of clinical Ag/AgCl wet electrodes which have a gel layer that causes discomfort and can lead into skin irritation especially in wearable, portable applications with typically longer monitoring durations. The major objective of this thesis is to develop, explore and evaluate the application of novel and truly wearable graphene textile electrodes specifically in surface electromyography (sEMG) applications. Benchmarking of the textile electrodes with respect to clinical electrodes was performed in terms of their skin electrode impedance (SEI) values and signal-to-noise ratios (SNR) acquired through static experiments. SEI values of textile electrodes were found to be well within the acceptable range and comparison of SNR values showed that graphene textile performance in static settings swings between 65% and 90% level of clinical signal quality. Custom-designed wearable platforms consist of muscle specific elastic bands with integrated graphene electrodes and battery-powered, small footprint hardware that can stream data wirelessly over Bluetooth. Feasibility of the developed wearables were shown with two different applications in dynamic conditions where a calf band was designed and used for activity tracking, and an arm band was developed for localized muscle fatigue assessment. The holistic system design concept presented here that is inclusive of fundamental material aspects up to the implementation of high-level user interface will be valuable for the development of wearable EMG platforms