Microsystems & Nanoengineering (May 2024)

Multichannel microneedle dry electrode patches for minimally invasive transdermal recording of electrophysiological signals

  • Zhengjie Liu,
  • Xingyuan Xu,
  • Shuang Huang,
  • Xinshuo Huang,
  • Zhibo Liu,
  • Chuanjie Yao,
  • Mengyi He,
  • Jiayi Chen,
  • Hui-jiuan Chen,
  • Jing Liu,
  • Xi Xie

DOI
https://doi.org/10.1038/s41378-024-00702-8
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 18

Abstract

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Abstract The collection of multiple-channel electrophysiological signals enables a comprehensive understanding of the spatial distribution and temporal features of electrophysiological activities. This approach can help to distinguish the traits and patterns of different ailments to enhance diagnostic accuracy. Microneedle array electrodes, which can penetrate skin without pain, can lessen the impedance between the electrodes and skin; however, current microneedle methods are limited to single channels and cannot achieve multichannel collection in small areas. Here, a multichannel (32 channels) microneedle dry electrode patch device was developed via a dimensionality reduction fabrication and integration approach and supported by a self-developed circuit system to record weak electrophysiological signals, including electroencephalography (EEG), electrocardiogram (ECG), and electromyography (EMG) signals. The microneedles reduced the electrode–skin contact impedance by penetrating the nonconducting stratum corneum in a painless way. The multichannel microneedle array (MMA) enabled painless transdermal recording of multichannel electrophysiological signals from the subcutaneous space, with high temporal and spatial resolution, reaching the level of a single microneedle in terms of signal precision. The MMA demonstrated the detection of the spatial distribution of ECG, EMG and EEG signals in live rabbit models, and the microneedle electrode (MNE) achieved better signal quality in the transcutaneous detection of EEG signals than did the conventional flat dry electrode array. This work offers a promising opportunity to develop advanced tools for neural interface technology and electrophysiological recording.