Cargando…

Wearable, Integrated EEG–fNIRS Technologies: A Review

There has been considerable interest in applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of brain function. EEG–fNIRS can provide a comprehensive picture of brain electrical and hemodynamic function and has been applied...

Descripción completa

Detalles Bibliográficos
Autores principales: Uchitel, Julie, Vidal-Rosas, Ernesto E., Cooper, Robert J., Zhao, Hubin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469799/
https://www.ncbi.nlm.nih.gov/pubmed/34577313
http://dx.doi.org/10.3390/s21186106
_version_ 1784574029990985728
author Uchitel, Julie
Vidal-Rosas, Ernesto E.
Cooper, Robert J.
Zhao, Hubin
author_facet Uchitel, Julie
Vidal-Rosas, Ernesto E.
Cooper, Robert J.
Zhao, Hubin
author_sort Uchitel, Julie
collection PubMed
description There has been considerable interest in applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of brain function. EEG–fNIRS 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–fNIRS 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–fNIRS system. Significant marks of progress include the development of both discrete component-based and microchip-based EEG–fNIRS 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–fNIRS systems.
format Online
Article
Text
id pubmed-8469799
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-84697992021-09-27 Wearable, Integrated EEG–fNIRS Technologies: A Review Uchitel, Julie Vidal-Rosas, Ernesto E. Cooper, Robert J. Zhao, Hubin Sensors (Basel) Review There has been considerable interest in applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of brain function. EEG–fNIRS 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–fNIRS 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–fNIRS system. Significant marks of progress include the development of both discrete component-based and microchip-based EEG–fNIRS 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–fNIRS systems. MDPI 2021-09-12 /pmc/articles/PMC8469799/ /pubmed/34577313 http://dx.doi.org/10.3390/s21186106 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Uchitel, Julie
Vidal-Rosas, Ernesto E.
Cooper, Robert J.
Zhao, Hubin
Wearable, Integrated EEG–fNIRS Technologies: A Review
title Wearable, Integrated EEG–fNIRS Technologies: A Review
title_full Wearable, Integrated EEG–fNIRS Technologies: A Review
title_fullStr Wearable, Integrated EEG–fNIRS Technologies: A Review
title_full_unstemmed Wearable, Integrated EEG–fNIRS Technologies: A Review
title_short Wearable, Integrated EEG–fNIRS Technologies: A Review
title_sort wearable, integrated eeg–fnirs technologies: a review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469799/
https://www.ncbi.nlm.nih.gov/pubmed/34577313
http://dx.doi.org/10.3390/s21186106
work_keys_str_mv AT uchiteljulie wearableintegratedeegfnirstechnologiesareview
AT vidalrosasernestoe wearableintegratedeegfnirstechnologiesareview
AT cooperrobertj wearableintegratedeegfnirstechnologiesareview
AT zhaohubin wearableintegratedeegfnirstechnologiesareview