Abstract
Studies show that biofeedback increases patient proprioception in physical rehabilitation training, improving outcomes; surface Electromyography (sEMG) is particularly appealing as it enables accurate progress evaluation and instant feedback. Furthermore, extending the rehabilitation processes to patients’ homes has been shown to increase the quality of the recovery process. This led research to move towards telerehabilitation, however, usability remains an issue in sEMG biofeedback, mainly because of the electrode materials. This work proposes a novel electrode, designed using a Shieldex Technik-Tex P130+B conductive fabric substrate, spray-coated with graphene to reduce the contact impedance with the skin. Experimental evaluation was performed in a population of 16 subjects with ages ranging from 20 to 50 years; results show up to 97% correlation and less than 3 dB (in average) degradation of the signal quality comparatively to standard pre-gelled Ag/AgCl electrodes.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
- 2.
- 3.
- 4.
References
Cieza, A., Causey, K., Kamenov, K., Hanson, S., Chatterji, S., Vos, T.: Global estimates of the need for rehabilitation based on the Global Burden of Disease study 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 2006–2017 (2020)
Basmajian, J.: Research foundations of EMG biofeedback in rehabilitation. Biofeedback Self Regul. 13, 275–298 (1988)
Cottrell, M., Galea, O., O’Leary, S., Hill, A., Russell, T.: Real-time telerehabilitation for the treatment of musculoskeletal conditions is effective and comparable to standard practice: a systematic review and meta-analysis. Clin. Rehabil. 31, 625–638 (2017)
Lemos, A., Oliveira, C., Telo, G., da Silva, H.P.: Bridging the clinic-home divide in muscular rehabilitation. In: Biofeedback, pp. 137–144. InTech (2018)
Silva, H., Scherer, R., Sousa, J., Londral, A.: Towards improving the usability of electromyographic interfaces. In: Pons, J.L., Torricelli, D., Pajaro, M. (eds.) Converging Clinical and Engineering Research on Neurorehabilitation. BB, vol. 1, pp. 437–441. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-34546-3_71
Samuel, O.W., et al.: A novel time-domain descriptor for improved prediction of upper limb movement intent in EMG-PR system. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3513–3516 (2018)
Silva, H.P.: The Biosignal C.A.O.S.: reflections on the usability of physiological sensing for human-computer interaction practitioners and researchers. In: Ibáñez, J., González-Vargas, J., Azorín, J.M., Akay, M., Pons, J.L. (eds.) Converging Clinical and Engineering Research on Neurorehabilitation II. BB, vol. 15, pp. 807–811. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-46669-9_132
Alizadeh-Meghrazi, M., et al.: A mass-producible washable smart garment with embedded textile EMG electrodes for control of myoelectric prostheses: a pilot study. Sensors 22, 666 (2022)
Kowalczyk, D., et al.: Electrically conductive composite textiles modified with graphene using sol-gel method. J. Alloys Compd. 784, 22–28 (2019)
Liu, J., Liu, M., Bai, Y., Zhang, J., Liu, H., Zhu, W.: Recent progress in flexible wearable sensors for vital sign monitoring. Sensors 20, 4009 (2020)
Zheng, Y., et al.: High-performance wearable strain sensor based on graphene/cotton fabric with high durability and low detection limit. ACS Appl. Mater. Interfaces. 12, 1474–1485 (2020)
Samanta, A., Bordes, R.: Conductive textiles prepared by spray coating of water-based graphene dispersions. RSC Adv. 10, 2396–2403 (2020)
Song, M.-S., Kang, S.-G., Lee, K.-T., Kim, J.: Wireless, Skin-mountable EMG sensor for human–machine interface application. Micromachines 10, 879 (2019)
Pylatiuk, C., et al.: Comparison of surface EMG monitoring electrodes for long-term use in rehabilitation device control. In: Proceedings of IEEE ICORR, pp. 300–304 (2009)
Luca, C: Surface electromyography: detection and recording. DelSys (2002)
Bonato, P., D’Alessio, T., Knaflitz, M.: A statistical method for the measurement of muscle activation intervals from surface myoelectric signal during gait. IEEE Trans. Biomed. Eng. 45, 287–299 (1998)
Acknowledgments
This work was partially funded by PLUX, S.A., by Fundação para a Ciência e Tecnologia (FCT) grants “NOVA I4H” (PD/BDE/150858/2021) and UIDB/50008/2020, and by Portugal 2020 grant “SMART-HEALTH-4-ALL” (POCI-01-0247-FEDER-046115 & LISBOA-01-0247-FEDER-046115).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 IFIP International Federation for Information Processing
About this paper
Cite this paper
Argiró, M.H.H., Quaresma, C., Silva, H.P. (2022). Novel Graphene Electrode for Electromyography Using Wearables Based on Smart Textiles. In: Camarinha-Matos, L.M. (eds) Technological Innovation for Digitalization and Virtualization. DoCEIS 2022. IFIP Advances in Information and Communication Technology, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-031-07520-9_19
Download citation
DOI: https://doi.org/10.1007/978-3-031-07520-9_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-07519-3
Online ISBN: 978-3-031-07520-9
eBook Packages: Computer ScienceComputer Science (R0)
