可穿戴脑电图系统的微型化:记录硬件和数据处理。

IF 3.2 4区 医学 Q2 ENGINEERING, BIOMEDICAL
Biomedical Engineering Letters Pub Date : 2022-06-06 eCollection Date: 2022-08-01 DOI:10.1007/s13534-022-00232-0
Minjae Kim, Seungjae Yoo, Chul Kim
{"title":"可穿戴脑电图系统的微型化:记录硬件和数据处理。","authors":"Minjae Kim, Seungjae Yoo, Chul Kim","doi":"10.1007/s13534-022-00232-0","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":46898,"journal":{"name":"Biomedical Engineering Letters","volume":"12 3","pages":"239-250"},"PeriodicalIF":3.2000,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9168644/pdf/","citationCount":"0","resultStr":"{\"title\":\"Miniaturization for wearable EEG systems: recording hardware and data processing.\",\"authors\":\"Minjae Kim, Seungjae Yoo, Chul Kim\",\"doi\":\"10.1007/s13534-022-00232-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":46898,\"journal\":{\"name\":\"Biomedical Engineering Letters\",\"volume\":\"12 3\",\"pages\":\"239-250\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2022-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9168644/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biomedical Engineering Letters\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s13534-022-00232-0\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/8/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomedical Engineering Letters","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s13534-022-00232-0","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/8/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

摘要

随着越来越多的人希望通过在家诊断和治疗来改善健康状况,医疗保健设备也变得更加可穿戴、舒适和易于使用。从这个意义上说,脑电图(EEG)系统的微型化是开发日常生活保健设备的一大挑战。最近,由于脑电图记录和处理之间的相互关系,脑电图记录硬件和数据处理的共同研究受到重视,以实现一体化的微型脑电图系统。本文介绍了此类脑电图系统的模拟前端硬件和处理算法的微型化技术。为了实现脑电图记录硬件的微型化,研究了各种类型的紧凑型电极和毫米级集成电路(IC)技术,包括伪影抑制技术,以便以更小的尺寸记录精确的脑电信号。此外,还研究了有源电极和耳内式脑电图技术,以制造小型脑电图测量结构。此外,还讨论了脑电图处理的小型化技术,包括减少所需电极通道数量的通道选择技术,以及简化脑电图处理阶段的处理算法的硬件实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Miniaturization for wearable EEG systems: recording hardware and data processing.

Miniaturization for wearable EEG systems: recording hardware and data processing.

Miniaturization for wearable EEG systems: recording hardware and data processing.

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. 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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Biomedical Engineering Letters
Biomedical Engineering Letters ENGINEERING, BIOMEDICAL-
CiteScore
6.80
自引率
0.00%
发文量
34
期刊介绍: Biomedical Engineering Letters (BMEL) aims to present the innovative experimental science and technological development in the biomedical field as well as clinical application of new development. The article must contain original biomedical engineering content, defined as development, theoretical analysis, and evaluation/validation of a new technique. BMEL publishes the following types of papers: original articles, review articles, editorials, and letters to the editor. All the papers are reviewed in single-blind fashion.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信