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Ultra-low power QRS detection using adaptive thresholding based on forward search interval technique
Ruping Xiao1; Mingzhong Li1; Man-Kay Law1; Pui-In Mak1; Rui P. Martin1
2017-12-01
Conference NameInternational Conference on Electron Devices and Solid-State Circuits (EDSSC)
Source PublicationEDSSC 2017 - 13th IEEE International Conference on Electron Devices and Solid-State Circuits
Volume2017-January
Pages1-2
Conference DateOCT 18-20, 2017
Conference PlaceHsinchu, TAIWAN
Abstract

We present an energy efficient QRS detector for real-time ECG signal processing implemented in ASIC. An adaptive thresholding scheme based on forward search interval (FSI) algorithm together with simple preprocessing is proposed to accurately detect QRS peaks. The Verilog HDL codes with improved hardware utilization efficiency are validated using FPGA, achieving 99.59% sensitivity (Se) and 99.63% positive prediction (Pr) using the MIT-BIH Arrhythmia database. A chip prototype is also implemented in a standard 0.18-μm CMOS process. Synthesized with a customized subthreshold digital library for minimum energy operation, the proposed QRS detector occupies an active area of 0.13 mm and consumes merely 93nW.

DOI10.1109/EDSSC.2017.8126486
URLView the original
Indexed ByCPCI-S
Language英語English
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000426985900088
Scopus ID2-s2.0-85043571325
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Faculty of Science and Technology
THE STATE KEY LABORATORY OF ANALOG AND MIXED-SIGNAL VLSI (UNIVERSITY OF MACAU)
INSTITUTE OF MICROELECTRONICS
Affiliation1.Universidade de Macau
2.Instituto Superior Técnico
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Ruping Xiao,Mingzhong Li,Man-Kay Law,et al. Ultra-low power QRS detection using adaptive thresholding based on forward search interval technique[C], 2017, 1-2.
APA Ruping Xiao., Mingzhong Li., Man-Kay Law., Pui-In Mak., & Rui P. Martin (2017). Ultra-low power QRS detection using adaptive thresholding based on forward search interval technique. EDSSC 2017 - 13th IEEE International Conference on Electron Devices and Solid-State Circuits, 2017-January, 1-2.
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