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Myolink: A 128-Channel, [Formula: see text], Embedded Recording System, Optimized for High-Density Surface

Simos Koutsoftidis, Deren Y Barsakcioglu, Konstantinos Petkos

    IEEE Transactions on Bio-Medical Engineering
    |April 25, 2022
    PubMed
    Summary
    This summary is machine-generated.

    Myolink, a novel portable amplifier, enhances high-density surface electromyogram (HD sEMG) acquisition. This system achieves superior signal quality and motor unit decomposition accuracy, particularly at low force levels.

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Signal Processing

    Background:

    • Electrophysiology amplifiers are crucial for acquiring biological signals.
    • High-density surface electromyogram (HD sEMG) requires high-fidelity signal acquisition.
    • Existing systems may have limitations in noise performance and channel density.

    Purpose of the Study:

    • To develop and characterize Myolink, a portable, modular, low-noise amplifier for HD sEMG.
    • To evaluate the performance of Myolink compared to commercial systems.
    • To assess the impact of improved signal quality on motor unit decomposition.

    Main Methods:

    • Designed a modular amplifier system with custom analog front-end and FPGA controller.
    • Achieved low input-referred noise (IRN) within a specific bandwidth.
    • Tested the system with experimental HD sEMG recordings and motor unit decomposition.

    Main Results:

    • Myolink modules acquire 32 channels each, expandable up to 128 channels.
    • Achieved ultra-low input-referred noise (IRN) below current commercial systems.
    • Demonstrated higher-quality HD sEMG acquisition and improved motor unit decomposition accuracy, especially at low forces.

    Conclusions:

    • Myolink offers a portable, ultra-low-noise solution for HD sEMG.
    • The system's superior IRN performance significantly enhances HD sEMG decomposition.
    • This advancement has implications for various applications requiring precise muscle activity analysis.