A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring

A low-power multi-functional electrocardiogram (ECG) signal processor is presented in this paper. To enable long-term monitoring, several architecture-level power saving techniques are proposed, including global cognitive clocking, pseudo-downsampling wavelet transform, adaptive storing, and denoisi...

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Main Authors: Liu, Xin, Zhou, Jun, Yang, Yongkui, Wang, Bo, Lan, Jingjing, Wang, Chao, Luo, Jianwen, Goh, Wang Ling, Kim, Tony Tae-Hyoung, Je, Minkyu
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2016
Subjects:
ECG
Online Access:https://hdl.handle.net/10356/81729
http://hdl.handle.net/10220/39656
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-817292020-09-26T22:02:46Z A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring Liu, Xin Zhou, Jun Yang, Yongkui Wang, Bo Lan, Jingjing Wang, Chao Luo, Jianwen Goh, Wang Ling Kim, Tony Tae-Hyoung Je, Minkyu School of Electrical and Electronic Engineering School of Physical and Mathematical Sciences Nanyang Environment and Water Research Institute Cognitive; ECG; multi-functional; nearthreshold; ultra low power ECG Multi-functional Nearthreshold Ultra low power A low-power multi-functional electrocardiogram (ECG) signal processor is presented in this paper. To enable long-term monitoring, several architecture-level power saving techniques are proposed, including global cognitive clocking, pseudo-downsampling wavelet transform, adaptive storing, and denoising-based run-length compression. An ultra-low-voltage ADC is designed for low-power signal digitization with adaptive clocking. Through these architecture-level techniques, the total power consumption can be significantly reduced by 63% as compared to the conventional design. Several circuit-level design techniques are also developed, including ultra-low-voltage operation and near-threshold level shifting, to further reduce the power consumption by 33%. In addition, a low-complexity cardiac analysis scheme is proposed to realize comprehensive on-chip cardiac analysis. Implemented in 0.18 μm CMOS process, the proposed cognitive ECG processor consumes only 457 nW at 0.5 V for real-time ECG recording and diagnosis. ASTAR (Agency for Sci., Tech. and Research, S’pore) Accepted version 2016-01-11T08:39:00Z 2019-12-06T14:39:18Z 2016-01-11T08:39:00Z 2019-12-06T14:39:18Z 2014 Journal Article Liu, X., Zhou, J., Yang, Y., Wang, B., Lan, J., Wang, C., et al. (2014). A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring. IEEE Journal of Solid-State Circuits, 49(11), 2422-2434. 0018-9200 https://hdl.handle.net/10356/81729 http://hdl.handle.net/10220/39656 10.1109/JSSC.2014.2338870 en IEEE Journal of Solid-State Circuits © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/JSSC.2014.2338870]. 31 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Cognitive; ECG; multi-functional; nearthreshold; ultra low power
ECG
Multi-functional
Nearthreshold
Ultra low power
spellingShingle Cognitive; ECG; multi-functional; nearthreshold; ultra low power
ECG
Multi-functional
Nearthreshold
Ultra low power
Liu, Xin
Zhou, Jun
Yang, Yongkui
Wang, Bo
Lan, Jingjing
Wang, Chao
Luo, Jianwen
Goh, Wang Ling
Kim, Tony Tae-Hyoung
Je, Minkyu
A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring
description A low-power multi-functional electrocardiogram (ECG) signal processor is presented in this paper. To enable long-term monitoring, several architecture-level power saving techniques are proposed, including global cognitive clocking, pseudo-downsampling wavelet transform, adaptive storing, and denoising-based run-length compression. An ultra-low-voltage ADC is designed for low-power signal digitization with adaptive clocking. Through these architecture-level techniques, the total power consumption can be significantly reduced by 63% as compared to the conventional design. Several circuit-level design techniques are also developed, including ultra-low-voltage operation and near-threshold level shifting, to further reduce the power consumption by 33%. In addition, a low-complexity cardiac analysis scheme is proposed to realize comprehensive on-chip cardiac analysis. Implemented in 0.18 μm CMOS process, the proposed cognitive ECG processor consumes only 457 nW at 0.5 V for real-time ECG recording and diagnosis.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Liu, Xin
Zhou, Jun
Yang, Yongkui
Wang, Bo
Lan, Jingjing
Wang, Chao
Luo, Jianwen
Goh, Wang Ling
Kim, Tony Tae-Hyoung
Je, Minkyu
format Article
author Liu, Xin
Zhou, Jun
Yang, Yongkui
Wang, Bo
Lan, Jingjing
Wang, Chao
Luo, Jianwen
Goh, Wang Ling
Kim, Tony Tae-Hyoung
Je, Minkyu
author_sort Liu, Xin
title A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring
title_short A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring
title_full A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring
title_fullStr A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring
title_full_unstemmed A 457 nW Near-Threshold Cognitive Multi-Functional ECG Processor for Long-Term Cardiac Monitoring
title_sort 457 nw near-threshold cognitive multi-functional ecg processor for long-term cardiac monitoring
publishDate 2016
url https://hdl.handle.net/10356/81729
http://hdl.handle.net/10220/39656
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