{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T14:38:43Z","timestamp":1777905523693,"version":"3.51.4"},"reference-count":72,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,12]],"date-time":"2021-09-12T00:00:00Z","timestamp":1631404800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/N025946\/1"],"award-info":[{"award-number":["EP\/N025946\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>There has been considerable interest in applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of brain function. EEG\u2013fNIRS can provide a comprehensive picture of brain electrical and hemodynamic function and has been applied across various fields of brain science. The development of wearable, mechanically and electrically integrated EEG\u2013fNIRS technology is a critical next step in the evolution of this field. A suitable system design could significantly increase the data\/image quality, the wearability, patient\/subject comfort, and capability for long-term monitoring. Here, we present a concise, yet comprehensive, review of the progress that has been made toward achieving a wearable, integrated EEG\u2013fNIRS system. Significant marks of progress include the development of both discrete component-based and microchip-based EEG\u2013fNIRS technologies; modular systems; miniaturized, lightweight form factors; wireless capabilities; and shared analogue-to-digital converter (ADC) architecture between fNIRS and EEG data acquisitions. In describing the attributes, advantages, and disadvantages of current technologies, this review aims to provide a roadmap toward the next generation of wearable, integrated EEG\u2013fNIRS systems.<\/jats:p>","DOI":"10.3390\/s21186106","type":"journal-article","created":{"date-parts":[[2021,9,12]],"date-time":"2021-09-12T21:48:01Z","timestamp":1631483281000},"page":"6106","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":98,"title":["Wearable, Integrated EEG\u2013fNIRS Technologies: A Review"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4568-5421","authenticated-orcid":false,"given":"Julie","family":"Uchitel","sequence":"first","affiliation":[{"name":"DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK"},{"name":"Department of Paediatrics, University of Cambridge, Cambridge CB2 0QQ, UK"}]},{"given":"Ernesto E.","family":"Vidal-Rosas","sequence":"additional","affiliation":[{"name":"DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK"}]},{"given":"Robert J.","family":"Cooper","sequence":"additional","affiliation":[{"name":"DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9408-4724","authenticated-orcid":false,"given":"Hubin","family":"Zhao","sequence":"additional","affiliation":[{"name":"DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK"},{"name":"James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/hbm.10057","article-title":"How can EEG\/MEG and fMRI\/PET data be combined?","volume":"17","author":"Horwitz","year":"2002","journal-title":"Hum. 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