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<p>This study investigated if new dry-electrode technologies for electroencephalography (EEG) can substantially lower patient and site burden in clinical trials while maintaining adequate data quality. We benchmarked three dry-electrode EEG devices against a standard EEG using typical clinical trial procedures and EEG tasks that are often used for biomarker purposes. We found that dry-electrode EEG can perform on par with standard EEG for a range of different applications. However, both the participant and technician acceptance varied strongly across devices. Dry-electrode EEG was able to only match the comfort of standard EEG at best but was faster and easier to work with. Consequently, dry-electrode EEG was ranked among the most and least preferred options. The quantitative performance of dry-electrode EEG varied strongly across different applications. For example, quantitative resting state EEG and P300 evoked activity were adequately captured by dry-electrode EEG. However, certain signal aspects, such as low frequency activity (&lt; 6&#xa0;Hz) and induced gamma activity (40–80&#xa0;Hz) presented notable challenges for dry-electrode EEG. Our findings suggest that dry-electrode EEG can substantially improve clinical trial applications of EEG, if the device and its context of use are carefully matched.</p>

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Benchmarking the utility of dry-electrode electroencephalography for clinical trials

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月29日

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  • Joseph Paillard,
  • Philipp Bomatter,
  • Laura Dubreuil-Vall,
  • Jörg Felix Hipp,
  • David Johannes Hawellek

摘要

This study investigated if new dry-electrode technologies for electroencephalography (EEG) can substantially lower patient and site burden in clinical trials while maintaining adequate data quality. We benchmarked three dry-electrode EEG devices against a standard EEG using typical clinical trial procedures and EEG tasks that are often used for biomarker purposes. We found that dry-electrode EEG can perform on par with standard EEG for a range of different applications. However, both the participant and technician acceptance varied strongly across devices. Dry-electrode EEG was able to only match the comfort of standard EEG at best but was faster and easier to work with. Consequently, dry-electrode EEG was ranked among the most and least preferred options. The quantitative performance of dry-electrode EEG varied strongly across different applications. For example, quantitative resting state EEG and P300 evoked activity were adequately captured by dry-electrode EEG. However, certain signal aspects, such as low frequency activity (< 6 Hz) and induced gamma activity (40–80 Hz) presented notable challenges for dry-electrode EEG. Our findings suggest that dry-electrode EEG can substantially improve clinical trial applications of EEG, if the device and its context of use are carefully matched.