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Embroidered Electromyography: A Systematic Design Guide

Research output: Contribution to journalArticle

Ali Shafti, Roger B. Ribas Manero, Amanda M. Borg, Kaspar Althoefer, Matthew J. Howard

Original languageEnglish
Pages (from-to)1472-1480
Number of pages9
JournalIEEE transactions on neural systems and rehabilitation engineering
Issue number9
Early online date1 Dec 2016
Publication statusPublished - 2 Sep 2017


  • Embroidered Electromyography_SHAFTI_Accepted27Oct2016_GREEN AAM

    Shafti_TNSRE2016.pdf, 12.7 MB, application/pdf


    Accepted author manuscript

    (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

King's Authors


Muscle activity monitoring or Electromyography (EMG) is a useful tool. However, EMG is typically invasive, expensive and difficult to use for untrained users. A possible solution is textile-based surface EMG (sEMG) integrated into clothing as a wearable device. This is, however, challenging due to (i) uncertainties in the electrical properties of conductive threads used for electrodes, (ii) imprecise fabrication technologies (e.g., embroidery, sewing), and (iii) lack of standardization in design variable selection. This paper, for the first time, provides a design guide for such sensors by performing a thorough examination of the effect of design variables on sEMG signal quality. Results show that imprecisions in digital embroidery lead to a trade-off between low electrode impedance and high manufacturing consistency. An optimum set of variables for this trade-off is identified and tested with sEMG during a variable force isometric grip exercise with n=12 participants, compared with conventional gel-based electrodes. Results show that thread-based electrodes provide a similar level of sensitivity to force variation as gel-based electrodes with about 90% correlation to expected linear behavior. As proof of concept, jogging leggings with integrated embroidered sEMG are made and successfully tested for detection of muscle fatigue while running on different surfaces.

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