4.6 Article

A Mass-Producible Washable Smart Garment with Embedded Textile EMG Electrodes for Control of Myoelectric Prostheses: A Pilot Study

Journal

SENSORS
Volume 22, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/s22020666

Keywords

electromyography; smart textiles; dry-contact electrodes; e-textile; conductive elastomeric yarn; knitted sensor; fabric sensor; ANN; prosthetic control

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This study developed textile electrodes as an alternative to traditional gel electrodes for recording electromyography (EMG) signals, and compared their performance and washability. The results showed that the textile electrodes performed comparably to gel electrodes in signal recording, and were able to successfully control a myoelectric prosthetic hand.
Electromyography (EMG) is the resulting electrical signal from muscle activity, commonly used as a proxy for users' intent in voluntary control of prosthetic devices. EMG signals are recorded with gold standard Ag/AgCl gel electrodes, though there are limitations in continuous use applications, with potential skin irritations and discomfort. Alternative dry solid metallic electrodes also face long-term usability and comfort challenges due to their inflexible and non-breathable structures. This is critical when the anatomy of the targeted body region is variable (e.g., residual limbs of individuals with amputation), and conformal contact is essential. In this study, textile electrodes were developed, and their performance in recording EMG signals was compared to gel electrodes. Additionally, to assess the reusability and robustness of the textile electrodes, the effect of 30 consumer washes was investigated. Comparisons were made between the signal-to-noise ratio (SNR), with no statistically significant difference, and with the power spectral density (PSD), showing a high correlation. Subsequently, a fully textile sleeve was fabricated covering the forearm, with 14 textile electrodes. For three individuals, an artificial neural network model was trained, capturing the EMG of 7 distinct finger movements. The personalized models were then used to successfully control a myoelectric prosthetic hand.

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