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Miniaturization for wearable EEG systems: recording hardware and data processing
As more people desire at-home diagnosis and treatment for their health improvement, healthcare devices have become more wearable, comfortable, and easy to use. In that sense, the miniaturization of electroencephalography (EEG) systems is a major challenge for developing daily-life healthcare devices...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Medical and Biological Engineering
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9168644/ https://www.ncbi.nlm.nih.gov/pubmed/35692891 http://dx.doi.org/10.1007/s13534-022-00232-0 |
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author | Kim, Minjae Yoo, Seungjae Kim, Chul |
author_facet | Kim, Minjae Yoo, Seungjae Kim, Chul |
author_sort | Kim, Minjae |
collection | PubMed |
description | As more people desire at-home diagnosis and treatment for their health improvement, healthcare devices have become more wearable, comfortable, and easy to use. In that sense, the miniaturization of electroencephalography (EEG) systems is a major challenge for developing daily-life healthcare devices. Recently, because of the intertwined relationship between EEG recording and processing, co-research of EEG recording hardware and data processing has been emphasized for whole-in-one miniaturized EEG systems. This paper introduces miniaturization techniques in analog-front-end hardware and processing algorithms for such EEG systems. To miniaturize EEG recording hardware, various types of compact electrodes and mm-sized integrated circuits (IC) techniques including artifact rejection are studied to record accurate EEG signals in a much smaller manner. Active electrode and in-ear EEG technologies are also researched to make small-form-factor EEG measurement structures. Furthermore, miniaturization techniques for EEG processing are discussed including channel selection techniques that reduce the number of required electrode channel and hardware implementation of processing algorithms that simplify the EEG processing stage. |
format | Online Article Text |
id | pubmed-9168644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Korean Society of Medical and Biological Engineering |
record_format | MEDLINE/PubMed |
spelling | pubmed-91686442022-06-07 Miniaturization for wearable EEG systems: recording hardware and data processing Kim, Minjae Yoo, Seungjae Kim, Chul Biomed Eng Lett Review Article As more people desire at-home diagnosis and treatment for their health improvement, healthcare devices have become more wearable, comfortable, and easy to use. In that sense, the miniaturization of electroencephalography (EEG) systems is a major challenge for developing daily-life healthcare devices. Recently, because of the intertwined relationship between EEG recording and processing, co-research of EEG recording hardware and data processing has been emphasized for whole-in-one miniaturized EEG systems. This paper introduces miniaturization techniques in analog-front-end hardware and processing algorithms for such EEG systems. To miniaturize EEG recording hardware, various types of compact electrodes and mm-sized integrated circuits (IC) techniques including artifact rejection are studied to record accurate EEG signals in a much smaller manner. Active electrode and in-ear EEG technologies are also researched to make small-form-factor EEG measurement structures. Furthermore, miniaturization techniques for EEG processing are discussed including channel selection techniques that reduce the number of required electrode channel and hardware implementation of processing algorithms that simplify the EEG processing stage. The Korean Society of Medical and Biological Engineering 2022-06-06 /pmc/articles/PMC9168644/ /pubmed/35692891 http://dx.doi.org/10.1007/s13534-022-00232-0 Text en © Korean Society of Medical and Biological Engineering 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
spellingShingle | Review Article Kim, Minjae Yoo, Seungjae Kim, Chul Miniaturization for wearable EEG systems: recording hardware and data processing |
title | Miniaturization for wearable EEG systems: recording hardware and data processing |
title_full | Miniaturization for wearable EEG systems: recording hardware and data processing |
title_fullStr | Miniaturization for wearable EEG systems: recording hardware and data processing |
title_full_unstemmed | Miniaturization for wearable EEG systems: recording hardware and data processing |
title_short | Miniaturization for wearable EEG systems: recording hardware and data processing |
title_sort | miniaturization for wearable eeg systems: recording hardware and data processing |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9168644/ https://www.ncbi.nlm.nih.gov/pubmed/35692891 http://dx.doi.org/10.1007/s13534-022-00232-0 |
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