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...
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| Published in | Sensors (Basel, Switzerland) Vol. 21; no. 18; p. 6106 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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12.09.2021
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| Abstract | 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. |
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| AbstractList | 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. 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.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. |
| Author | Uchitel, Julie Cooper, Robert J. Vidal-Rosas, Ernesto E. Zhao, Hubin |
| AuthorAffiliation | 1 DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; ju236@cam.ac.uk (J.U.); ernesto.vidal@ucl.ac.uk (E.E.V.-R.); robert.cooper@ucl.ac.uk (R.J.C.) 3 James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK 2 Department of Paediatrics, University of Cambridge, Cambridge CB2 0QQ, UK |
| AuthorAffiliation_xml | – name: 1 DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK; ju236@cam.ac.uk (J.U.); ernesto.vidal@ucl.ac.uk (E.E.V.-R.); robert.cooper@ucl.ac.uk (R.J.C.) – name: 3 James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK – name: 2 Department of Paediatrics, University of Cambridge, Cambridge CB2 0QQ, UK |
| Author_xml | – sequence: 1 givenname: Julie orcidid: 0000-0003-4568-5421 surname: Uchitel fullname: Uchitel, Julie – sequence: 2 givenname: Ernesto E. surname: Vidal-Rosas fullname: Vidal-Rosas, Ernesto E. – sequence: 3 givenname: Robert J. surname: Cooper fullname: Cooper, Robert J. – sequence: 4 givenname: Hubin orcidid: 0000-0001-9408-4724 surname: Zhao fullname: Zhao, Hubin |
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| Title | Wearable, Integrated EEG–fNIRS Technologies: A Review |
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