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<p>Bionic limbs require reliable, low-noise and high-comfort interfaces between electrodes and the prosthetic system. This work presents the first fully flexible, wearable myoelectric control system compatible with both dry and wet electrodes. It features a low-noise front-end circuit on foil using amorphous Indium-Gallium-Zinc-Oxide (a-IGZO) Thin-Film Transistors, optimized for multi-electrode sensing. The design includes an autozeroed pre-charging buffer to minimize offset and 1/f noise while maintaining high input impedance (841 MΩ at 50 Hz). The front-end achieves 22 µVrms input noise, &lt; −90 dBc crosstalk, and a 4.6 mV input offset consuming 55.3 µW per channel. EMG signals measured by this AFE were used to drive an elbow musculoskeletal model and predict the resulting human elbow flexion-extension moments, which in turn were used to realize a closed-loop real-time control in a simulated bionic elbow joint, using both dry and wet electrodes. Experiments done with a series of movements show a 20°rms error in angular control.</p>

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Flexible circuits for bionic limbs: a high impedance multiplexing front-end for myoelectric control

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月19日

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  • Kyle van Oosterhout,
  • Simon van Diemen,
  • Martijn Timmermans,
  • Marco Fattori,
  • Massimo Sartori,
  • Eugenio Cantatore

摘要

Bionic limbs require reliable, low-noise and high-comfort interfaces between electrodes and the prosthetic system. This work presents the first fully flexible, wearable myoelectric control system compatible with both dry and wet electrodes. It features a low-noise front-end circuit on foil using amorphous Indium-Gallium-Zinc-Oxide (a-IGZO) Thin-Film Transistors, optimized for multi-electrode sensing. The design includes an autozeroed pre-charging buffer to minimize offset and 1/f noise while maintaining high input impedance (841 MΩ at 50 Hz). The front-end achieves 22 µVrms input noise, < −90 dBc crosstalk, and a 4.6 mV input offset consuming 55.3 µW per channel. EMG signals measured by this AFE were used to drive an elbow musculoskeletal model and predict the resulting human elbow flexion-extension moments, which in turn were used to realize a closed-loop real-time control in a simulated bionic elbow joint, using both dry and wet electrodes. Experiments done with a series of movements show a 20°rms error in angular control.