用于生物医学应用的可重构循环ADC

Amandeep Kaur, Deepak Mishra
{"title":"用于生物医学应用的可重构循环ADC","authors":"Amandeep Kaur, Deepak Mishra","doi":"10.1109/BIOCAS.2019.8919110","DOIUrl":null,"url":null,"abstract":"Bio-signals such as electroencephalogram (EEG) contain low activity regions often called B-noise and high activity regions called active potentials. The high activity regions are more important as compared to their counterpart. In addition, the signals are considerably sparse in the low activity regions. Thus a full n-bit conversion of low activity samples into digital domain increases readout power and reduces data acquisition rate of analog to digital converter (ADC). To alleviate these problems, a reconfigurable cyclic ADC is presented in this paper. Input range and conversion cycles of the proposed ADC are varied according to the samples of the neural signal. The high activity region samples are resolved using conventional n-bits, however, the low activity region is resolved using less number of bits. This saves readout power and also reduces the digital data content. The proposed ADC is designed and fabricated in UMC 180 nm CMOS technology. The ADC operates at a sampling rate of 200 kS/s and consumes 61.8 µW of power. The chip occupies an area of 0.031 mm2. Using reconfiguration, the power saving of 28.6% is achieved compared to the conventional n-bit full conversion.","PeriodicalId":222264,"journal":{"name":"2019 IEEE Biomedical Circuits and Systems Conference (BioCAS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A reconfigurable cyclic ADC for biomedical applications\",\"authors\":\"Amandeep Kaur, Deepak Mishra\",\"doi\":\"10.1109/BIOCAS.2019.8919110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bio-signals such as electroencephalogram (EEG) contain low activity regions often called B-noise and high activity regions called active potentials. The high activity regions are more important as compared to their counterpart. In addition, the signals are considerably sparse in the low activity regions. Thus a full n-bit conversion of low activity samples into digital domain increases readout power and reduces data acquisition rate of analog to digital converter (ADC). To alleviate these problems, a reconfigurable cyclic ADC is presented in this paper. Input range and conversion cycles of the proposed ADC are varied according to the samples of the neural signal. The high activity region samples are resolved using conventional n-bits, however, the low activity region is resolved using less number of bits. This saves readout power and also reduces the digital data content. The proposed ADC is designed and fabricated in UMC 180 nm CMOS technology. The ADC operates at a sampling rate of 200 kS/s and consumes 61.8 µW of power. The chip occupies an area of 0.031 mm2. Using reconfiguration, the power saving of 28.6% is achieved compared to the conventional n-bit full conversion.\",\"PeriodicalId\":222264,\"journal\":{\"name\":\"2019 IEEE Biomedical Circuits and Systems Conference (BioCAS)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Biomedical Circuits and Systems Conference (BioCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIOCAS.2019.8919110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Biomedical Circuits and Systems Conference (BioCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIOCAS.2019.8919110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

生物信号如脑电图(EEG)包含通常称为b噪声的低活动区域和称为活动电位的高活动区域。高活动区域比对应区域更重要。此外,在低活动区域,信号相当稀疏。因此,低活度采样到数字域的全n位转换增加了读出功率并降低了模数转换器(ADC)的数据采集速率。为了解决这些问题,本文提出了一种可重构的循环ADC。所提出的ADC的输入范围和转换周期根据神经信号的采样而变化。高活性区域样本使用传统的n位进行解析,然而,低活性区域使用较少的位数进行解析。这节省了读出功率,也减少了数字数据内容。该ADC采用UMC 180nm CMOS工艺设计和制造。ADC的采样率为200ks /s,功耗为61.8µW。该芯片的面积为0.031 mm2。通过重新配置,与传统的n位全转换相比,节省了28.6%的功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A reconfigurable cyclic ADC for biomedical applications
Bio-signals such as electroencephalogram (EEG) contain low activity regions often called B-noise and high activity regions called active potentials. The high activity regions are more important as compared to their counterpart. In addition, the signals are considerably sparse in the low activity regions. Thus a full n-bit conversion of low activity samples into digital domain increases readout power and reduces data acquisition rate of analog to digital converter (ADC). To alleviate these problems, a reconfigurable cyclic ADC is presented in this paper. Input range and conversion cycles of the proposed ADC are varied according to the samples of the neural signal. The high activity region samples are resolved using conventional n-bits, however, the low activity region is resolved using less number of bits. This saves readout power and also reduces the digital data content. The proposed ADC is designed and fabricated in UMC 180 nm CMOS technology. The ADC operates at a sampling rate of 200 kS/s and consumes 61.8 µW of power. The chip occupies an area of 0.031 mm2. Using reconfiguration, the power saving of 28.6% is achieved compared to the conventional n-bit full conversion.
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
自引率
0.00%
发文量
0
×
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