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Development of an Integrated EEG/fNIRS Brain Function Monitoring System
In this study, a fully integrated electroencephalogram/functional near-infrared spectroscopy (EEG/fNIRS) brain monitoring system was designed to fulfill the demand for a miniaturized, light-weight, low-power-consumption, and low-cost brain monitoring system as a potential tool with which to screen f...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625300/ https://www.ncbi.nlm.nih.gov/pubmed/34833775 http://dx.doi.org/10.3390/s21227703 |
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author | Mohamed, Manal Jo, Eunjung Mohamed, Nourelhuda Kim, Minhee Yun, Jeong-dae Kim, Jae Gwan |
author_facet | Mohamed, Manal Jo, Eunjung Mohamed, Nourelhuda Kim, Minhee Yun, Jeong-dae Kim, Jae Gwan |
author_sort | Mohamed, Manal |
collection | PubMed |
description | In this study, a fully integrated electroencephalogram/functional near-infrared spectroscopy (EEG/fNIRS) brain monitoring system was designed to fulfill the demand for a miniaturized, light-weight, low-power-consumption, and low-cost brain monitoring system as a potential tool with which to screen for brain diseases. The system is based on the ADS1298IPAG Analog Front-End (AFE) and can simultaneously acquire two-channel EEG signals with a sampling rate of 250 SPS and six-channel fNIRS signals with a sampling rate of 8 SPS. AFE is controlled by Teensy 3.2 and powered by a lithium polymer battery connected to two protection circuits and regulators. The acquired EEG and fNIRS signals are monitored and stored using a Graphical User Interface (GUI). The system was evaluated by implementing several tests to verify its ability to simultaneously acquire EEG and fNIRS signals. The implemented system can acquire EEG and fNIRS signals with a CMRR of −115 dB, power consumption of 0.75 mW/ch, system weight of 70.5 g, probe weight of 3.1 g, and a total cost of USD 130. The results proved that this system can be qualified as a low-cost, light-weight, low-power-consumption, and fully integrated EEG/fNIRS brain monitoring system. |
format | Online Article Text |
id | pubmed-8625300 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86253002021-11-27 Development of an Integrated EEG/fNIRS Brain Function Monitoring System Mohamed, Manal Jo, Eunjung Mohamed, Nourelhuda Kim, Minhee Yun, Jeong-dae Kim, Jae Gwan Sensors (Basel) Article In this study, a fully integrated electroencephalogram/functional near-infrared spectroscopy (EEG/fNIRS) brain monitoring system was designed to fulfill the demand for a miniaturized, light-weight, low-power-consumption, and low-cost brain monitoring system as a potential tool with which to screen for brain diseases. The system is based on the ADS1298IPAG Analog Front-End (AFE) and can simultaneously acquire two-channel EEG signals with a sampling rate of 250 SPS and six-channel fNIRS signals with a sampling rate of 8 SPS. AFE is controlled by Teensy 3.2 and powered by a lithium polymer battery connected to two protection circuits and regulators. The acquired EEG and fNIRS signals are monitored and stored using a Graphical User Interface (GUI). The system was evaluated by implementing several tests to verify its ability to simultaneously acquire EEG and fNIRS signals. The implemented system can acquire EEG and fNIRS signals with a CMRR of −115 dB, power consumption of 0.75 mW/ch, system weight of 70.5 g, probe weight of 3.1 g, and a total cost of USD 130. The results proved that this system can be qualified as a low-cost, light-weight, low-power-consumption, and fully integrated EEG/fNIRS brain monitoring system. MDPI 2021-11-19 /pmc/articles/PMC8625300/ /pubmed/34833775 http://dx.doi.org/10.3390/s21227703 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 | Article Mohamed, Manal Jo, Eunjung Mohamed, Nourelhuda Kim, Minhee Yun, Jeong-dae Kim, Jae Gwan Development of an Integrated EEG/fNIRS Brain Function Monitoring System |
title | Development of an Integrated EEG/fNIRS Brain Function Monitoring System |
title_full | Development of an Integrated EEG/fNIRS Brain Function Monitoring System |
title_fullStr | Development of an Integrated EEG/fNIRS Brain Function Monitoring System |
title_full_unstemmed | Development of an Integrated EEG/fNIRS Brain Function Monitoring System |
title_short | Development of an Integrated EEG/fNIRS Brain Function Monitoring System |
title_sort | development of an integrated eeg/fnirs brain function monitoring system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625300/ https://www.ncbi.nlm.nih.gov/pubmed/34833775 http://dx.doi.org/10.3390/s21227703 |
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