HDE-Array: Development and Validation of a New Dry Electrode Array Design to Acquire HD-sEMG for Hand Position Estimation
Giovanni Rolandino, Chiara Zangrandi, Taian Vieira, Giacinto Luigi Cerone, Brian Andrews, James J. FitzGerald

TL;DR
This study introduces HDE-Array, a new dry electrode array for high-density surface electromyography, demonstrating comparable or better hand position estimation accuracy with RPC-Net compared to traditional gel electrodes, with potential benefits for rehabilitation devices.
Contribution
The paper presents a novel dry electrode array design, HDE-Array, validated for effective hand position estimation using HD-sEMG signals with RPC-Net, offering a cost-effective and user-friendly alternative to gel electrodes.
Findings
HDE-Array achieves comparable or superior accuracy to gel electrodes in hand position estimation.
Dry electrodes show effective performance with simplified setup.
Variance analysis confirms minimal information loss with two-row electrode design.
Abstract
This paper aims to introduce HDE-Array (High-Density Electrode Array), a novel dry electrode array for acquiring High-Density surface electromyography (HD-sEMG) for hand position estimation through RPC-Net (Recursive Prosthetic Control Network), a neural network defined in a previous study. We aim to demonstrate the hypothesis that the position estimates returned by RPC-Net using HD-sEMG signals acquired with HDE-Array are as accurate as those obtained from signals acquired with gel electrodes. We compared the results, in terms of precision of hand position estimation by RPC-Net, using signals acquired by traditional gel electrodes and by HDE-Array. As additional validation, we performed a variance analysis to confirm that the presence of only two rows of electrodes does not result in an excessive loss of information, and we characterized the electrode-skin impedance to assess the…
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