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However, past developments were primarily driven by brain\u2013computer interfaces (BCI), leaving their comparability to wet electrodes in clinical and daily life applications an open question. Here, we developed a new dry EEG system and systematically benchmarked its performance against a commercial wet EEG system across various tasks. Methods: Participants (n = 19) underwent simultaneous recording using both devices. We first collected resting-state EEG under both eyes-closed and eyes-open conditions, followed by a steady-state visual evoked potential (SSVEP) task at different flicker frequencies and a motor imagery (MI) task. System performance was evaluated using power spectral density (PSD), signal to noise ratio (SNR), event-related spectral perturbation (ERSP), and single-trial classification accuracy. Results: The two systems performed similarly across different tasks. During the resting state, no statistically significant differences were observed between the two systems in the PSD of the five frequency bands (p &gt; 0.05 in all cases). Similarly, SNR in the SSVEP task showed no significant differences at 8 Hz, 10 Hz, and 12 Hz after correction. For cognitive tasks, classification accuracies were comparable (SSVEP: dry 80.08% \u00b1 7.1% vs. wet 81.10% \u00b1 6.5%; MI: dry 72.46% \u00b1 3.89% vs. wet 70.7% \u00b1 2.37%). Conclusions: The developed dry EEG system can effectively record electrophysiological measurements commonly employed in research and clinical settings, with quality comparable to that of traditional wet EEG systems.<\/jats:p>","DOI":"10.3390\/bios16090467","type":"journal-article","created":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T08:02:27Z","timestamp":1787817747000},"page":"467","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Systematic Benchmarking of a Dry Electrode EEG Prototype Against Wet Electrode EEG Systems in Electrophysiological\/Cognitive Scenarios"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8182-1909","authenticated-orcid":false,"given":"Boli","family":"Pan","sequence":"first","affiliation":[{"name":"Institute of Artificial Intelligence and Brain Sciences, University of Macau, Taipa, Macau SAR 999078, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Ding","sequence":"additional","affiliation":[{"name":"Beijing Metaneuron Technology Co., Ltd., Beijing 100027, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingbo","family":"Geng","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Brain Sciences, University of Macau, Taipa, Macau SAR 999078, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiacheng","family":"Liang","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Brain Sciences, University of Macau, Taipa, Macau SAR 999078, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fali","family":"Li","sequence":"additional","affiliation":[{"name":"Center for Information in BioMedicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"},{"name":"Key Laboratory of Neuro-Informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0787-8230","authenticated-orcid":false,"given":"Xirong","family":"Li","sequence":"additional","affiliation":[{"name":"Shandong Mental Health Center, Shandong University, Jinan 250014, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0309-9606","authenticated-orcid":false,"given":"Yanbin","family":"Dong","sequence":"additional","affiliation":[{"name":"Beijing Metaneuron Technology Co., Ltd., Beijing 100027, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8006-7333","authenticated-orcid":false,"given":"Rihui","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Brain Sciences, University of Macau, Taipa, Macau SAR 999078, China"},{"name":"Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR 999078, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1007\/s10548-015-0435-5","article-title":"Multipin Electrode Cap System for Dry Electroencephalography","volume":"28","author":"Fiedler","year":"2015","journal-title":"Brain Topogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"12847","DOI":"10.3390\/s140712847","article-title":"Dry EEG electrodes","volume":"14","year":"2014","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.neuroimage.2018.09.012","article-title":"Systematic comparison between a wireless EEG system with dry electrodes and a wired EEG system with wet electrodes","volume":"184","author":"Kam","year":"2019","journal-title":"NeuroImage"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1109\/TBME.2010.2102353","article-title":"Novel dry ploymer foam electrodes for long-term EEG measurement","volume":"58","author":"Lin","year":"2011","journal-title":"IEEE Trans. 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